DIAL

In Episode 7 of Series 2 of our podcast we talk with Professor Susan Harkness from the University of Bristol and PI of DIAL's EQUAL LIVES project about how economic disadvantage accumulates for single mothers and the impacts on their income and risk of poverty of having a child and splitting up from a partner.

The Accumulation of Economic Disadvantage: The Influence of Childbirth and Divorce on the Income and Poverty Risk of Single Mothers is research by Professor Susan Harkness of the University of Bristol and is published in Demography.

 

Transcript

Christine Garrington  0:00

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In this series, we discuss emerging findings from DIAL's Equal Lives project. Our guest today is Professor Susan Harkness from the University of Bristol and PI of Equal Lives. She's been looking at how economic disadvantage accumulates for single mothers, and the impacts on their income and risk of poverty of having a child and splitting up from a partner. I started by asking her about the background to her research.

Susan Harkness  0:28 

I think for a long time, there's been an assumption that single mothers are more likely to be poor or living in low income because they're not living with a male breadwinning partner. And I think one of the things that's been much less well recognised is that in the US, but also elsewhere, single mothers are much more likely to be poor than single fathers and I think one of the reasons for this is not just that they don't live with a partner, but also because they face an enormous economic hit because of motherhood. And I think the motherhood penalty. We know, we know it exists. We know mothers are much less likely to work than fathers. And when they do work, that they're more likely to be paid less. And what I wanted to do was try and connect to this research with research from single parenthood to see what the impact on single mothers' incomes was.

Christine Garrington  1:16 

So what was it here that you wanted to look at specifically and why then?

 

Susan Harkness  1:21 

Okay, so I wanted to think about why single mothers were more likely to have low income so what was the penalty to single motherhood? And in doing that, I wanted to think about single motherhood is a process that sort of evolves over the life cycle. So first of all, we know that mothers when they have children, they face this economic penalty in the labour market, and then when they separate, they're left in this very vulnerable position because their employment earnings have just declined so much.

Christine Garrington  1:49

And for this research, where did you get your information from? And can you tell us sort of why it is a good source for for looking at these particular issues? 

Susan Harkness  1:58 

Yes, so we looked at data from the Panel Study for Income Dynamics and it's a great source of data because it allows us to look at people over time. In the case of our study, we've followed them for over 10 years, since becoming mothers to look at what happened to their incomes around these kind of critical lifecourse transitions. One of the great advantages of it is that we can see how people were doing before they became single mothers and we can see how they were doing after and then we can kind of look at how each of these different life course events - motherhood, partnership dissolution - leads to changes in their economic circumstances. Another major advantage of this data is that it's got a really large sample size, and therefore we can think a bit more also about the heterogeneity the experience of single mothers. And what we mean here is that we can think about whether all single mothers effectively look the same or whether different routes into single motherhood have a different impact on their incomes. So what we did in this particular case was think about how single mothers differ according to whether they were previously married. They were previously cohabiting, or indeed they were married at the time at which they had a child. And this is a group which is accounting for a sort of growing share of births in the US and indeed in the UK over time.

Christine Garrington  3:18 

Right now you started by comparing the incomes of single, cohabiting and married mothers, what did you, what did you actually see there?

Susan Harkness  3:26

So one thing that we see is, is I think fairly fairly well known but we know that for example, married mothers start from a position of having higher incomes than cohabiting mothers and single mothers. So there's an income gradient with cohabiting mothers sitting somewhere in the middle. But what we also know is that the, the income composition of those families is quite different. So whilst in single mother families, women are indeed largely dependent on their own earnings, and to some extent on benefit receipts, in cohabiting and married mother families, there's a much greater dependence of women on partner's earnings. And indeed if you look at the earnings, of women within those different family types, they're actually relatively similar. Married and cohabiting mothers tend to be more dependent on partners, whereas single mothers tend to be more dependent on their own earnings and on the state. 

Christine Garrington  4:22

Yeah, right - so what was the earnings impact of divorce or separation for each of these groups and were they larger for some than, than others?

Susan Harkness  4:29

Okay, so one of the things that we thought was really interesting is that if we look at what happens to women's own earnings following the birth of a child, the biggest negative effect was for women who were previously married. So we're not looking at wage effects specifically we're looking at the combined effect of changes in wages and changes in working hours and indeed participation. What we see is that for married mothers, we find much greater reduction in self-sufficiency or increased economic dependence as a result of childbirth, amongst cohabiting mothers, among single mothers, we see a smaller earnings effect, so earnings declined by less. And what happens then if we look at the income within those families, is that if we consider what happens to the income of married mother families? In fact, what we find is that although earnings fall quite substantially amongst married mothers, these are compensated for by increases in fathers' earnings who to tend to work longer hours and work more often when they have a child and therefore the overall impact on income is relatively small, whereas in single mother families, the birth of the child is associated with the fall in earnings and a really large impact on overall income.

Christine Garrington  5:42

Okay, and you also considered how the loss of a male partner’s income affected these separated and divorced mothers, what did you see there?

Susan Harkness  5:49

So what we see for the loss of a partner's earnings is of course, married mothers tend to be partner to higher earning men and men who work more following the birth of a child and so when the partner leaves, we have a larger negative effect on their overall incomes. And part of this is because of the reduction in these married mothers’ own earnings following childbirth. And part of the reason for that is that the, they have, they have farther, further to fall. So the, the loss of father's earnings fall this is somewhat greater.

Christine Garrington 6:19

Yeah, so quite a lot of information there. What do we learn from all of this? That's new, Susan?

Susan Harkness  6:24

If we think about what happens within married couples, I think because marriage sort of provides some security, is thought to provide some security for those who have children that we tend to see greater levels of specialisation within those households. What this means is that women see their earnings fall farther than cohabiting are single mothers, and it becomes harder for them to recover those earnings should they, should they separate so the overall impact should they become single mothers on their own labour market income is greater than for these other family types. And what does this mean? It means that actually the separation from marriage tends to have worse consequences than it does if you become a single mother through separation from cohabitation or divorce. Whilst you might think, for example, that maintenance might help offset some of these costs associated with divorce. In fact, this is often not really, not really the case because the levels of maintenance payments are relatively small. What we find is actually that single parenthood, regardless of the route in by which you become a single mother, is really quite a leveller and women who were better off before see the largest falls in their income.

Christine Garrington 7:42

Okay, there was one other aspect of your research that really caught my eye and this was, these were your findings around what things are like for single moms who are living with parents. These are quite interesting, weren't they?

Susan Harkness  7:51

Oh, I think this is, this is fascinating. So one of the things that I think increasing research is looking at is how, how single mothers maintain those sort of standard of, standard of living, when they're not able to rely on their own earnings or indeed on the state. And we know that in the US around one in 10 single mothers are living with their own parents. And in in this study, we find that actually living with your own parents is a really important mechanism for boosting families' income. And in fact, living with your own parents provides as much protection for household income as being married and a little more than if you find a new partner, for example. So it's really, really important living with grandparents is a really important route to kind of maintaining your standard of living following parental separation. 

Christine Garrington 8:42

Important to acknowledge that the very rich data you used here is from the US but I wonder if you think that the picture might be reflected in the in the UK, where we are, and also possibly in other parts of Europe?

Susan Harkness  8:54

Yes, absolutely. So one of the things we know about the UK is that and indeed other parts of Europe is that motherhood is associated with even larger reductions in overall labour supply. So we know that women when they have children are perhaps less likely to work but also much more likely to work part-time. So the the numbers that are working full time are far lower, after having children in the UK and other European countries, many other European countries than in the US. So what we would expect to find is actually that the impact of single motherhood on income is going to be quite different. So in the case of in the case of the UK, what we might expect to see is that it sees large losses in earnings associated with losses in employment for motherhood, are probably going to have an even larger impact on their well being - their economic well being - should they, should they subsequently divorce. But on a more sort of positive note, I think what we have in many European countries is greater welfare support for, for single mothers which is, is much more significant for boosting their incomes. Although of course this has the further drawback that it can also discourage women from working or working longer hours because of the design of various welfare support systems.

Christine Garrington 10:18

Yeah, indeed. Now single mothers are a key area of interest for you as a researcher but also a really important group of people that policymakers are interested in and your research would seem to have quite clear and important ramifications and implications for welfare policy. Could you talk us through what you think those modifications are?

Susan Harkness  10:40

Yeah, so I think what one of the things we often see focused on when we think about single parents is what to do about father absence, in particular, how to make fathers pay maintenance, for example. But what our findings are suggesting is that actually, when we think about how to support single mothers incomes, we need to go much further than that. And in particular, one when we think about, for example, welfare to work policies, which focus on single, single mothers. It's really the case that in my view, that these policies are something that happened far too late in the life course. So if mothers have already lost their jobs and their earnings potential has already been weakened as a result of motherhood, then trying to do something about that at the point at which they divorce seems to me to be far too late. If we look at other studies, more recently, they suggest that when mothers do well, those in single parent families do well as well. And if we think about policies to ensure that women are able to maintain their economic position after having children in the labour market, then we would want to think much more widely about policies such as childcare provision, which would allow mothers to work, reduce their economic dependence and improve their prospects should they separate.

Christine Garrington  12:00 

"Accumulation of economic disadvantage: the influence of childbirth and relationship breakdown on mother's income and poverty risks" is research by Susan Harkness and is published in Demography. You can find out more about the Norface funded Equal Lives project at Equal-lives.org, and about the wider DIAL programme at dynamicsofinequality.org. Thanks for listening to this episode of our podcast which is presented and produced by Chris Garrington, edited by Elina Kilpi-Jakonen.

In the final episode of the DIAL podcast we’re looking at what’s been learned from DIAL projects about how and when inequality manifests in our lives and what its longer term consequences might be. We're joined by Elina Kilpi-Jakonen from the University of Turku in Finland. Elina is the Scientific Coordinator for DIAL and, as the programme draws to a close she reflects on some of the programme’s highlights,  key findings and implications for the future.   Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series four, we're looking at what's been learned from DIAL projects about how and when inequality manifests in our lives, and what its longer-term consequences might be. For this final episode of the series, we're delighted to be joined by Elina Kilpi-Jakonen, from the University of Turku in Finland. Elina is the scientific co-ordinator for DIAL and today, as the programme draws to a close, she's here to reflect on some of the program's highlights, key findings and implications for the future. So welcome, Elina thank you very much indeed, for joining us. Now, first of all, I'm guessing it's been no mean feat and indeed, I know, it's been no mean feat, keeping an eye across 13 fantastic research projects with researchers based all over Europe. But just take a minute or two, if you would to remind us of what exactly the DIAL programme is and what it's involved over the last few years.

Elina Kilpi-Jakonen  0:57 

So thanks a lot, Chris. The DIAL programme is, as you said, kind of transnational programme. And we've had 13 research projects involved. And all of those involve international collaboration. And it's based in the social sciences and behavioural sciences, financed by NORFACE, which is a research organisation bringing together different funding institutes across Europe. And so the focus of DIAL has been on inequality and in particular inequality across the life course and trying to understand some of the structures of inequality cross nationally and some of the mechanisms kind of producing inequality and and what that means to people and societies as a whole.

Christine Garrington  1:41 

Wonder if I can ask you why it has been so important to look not just at inequality, per se, as you were saying there, but at how inequality manifests itself over the life course, because this is an important thing, isn't it? And indeed how, when and where it sort of accumulates?

Elina Kilpi-Jakonen  1:57 

Inequality is a really complex and multifaceted issue. And so I think one one part of it is that inequality comes across in many different domains. So it's important to take into account inequalities, for example, in education, labour market, health, and so on. And then I mean, to really understand where it comes from and what it means it's important to look at the determinants across time, I mean, both across time for an individual and their parents, and so on, kind of that life course aspect, but also, for countries to see how it develops across time. Inequality isn't something that just is, I mean, it develops. And so kind of building on that kind of developmental process to really kind of inform us about how we can do something about it, or how we can really kind of understand where it comes from, it's important to take that into account.

Christine Garrington  2:58 

Now, you talked about the programme largely being based in the social sciences. But one of the key things about the project is that we've seen researchers from different disciplines as well as different countries coming together to try to tackle, as you say, as you rightly say, this incredibly complex area around inequality, what's been the thinking there?

Elina Kilpi-Jakonen  3:20 

Well, I mean, inequality is something that interests a lot of academics working in different disciplines. And, and they come from it from from kind of different angles. And I think, because it is kind of a complex issue, and it's an issue that kind of manifests itself in different ways. So really building on on the strengths of different disciplines, I think is a key key strength here. So we don't only look at inequality in one domain, for example, say, say something like education, which would then be kind of a subset of disciplines that tend to be interested in inequality in education, but also how education is linked to inequalities in in other aspects and, and in addition to the kind of different domains that come from different disciplines, also, the ways in which we, we analyse it and building on the strengths and knowledge of different disciplines. I think is key here, key to, to just building a comprehensive picture and learning from each other, as well as as then taking that knowledge forward.

Christine Garrington  4:34 

It would be remiss of us not to talk about COVID. And in some ways, it was something of a setback for plans to to stage events and meetings around the the programme of research to get the word out there about it. But it also provided in some respects, a rather unexpected opportunity, didn't it to use the programme to look at inequality in the context of COVID. So, so tell us a bit about that.

Elina Kilpi-Jakonen  4:58 

Yeah, so obviously the research programme began before COVID. And so the projects had their their kind of plans of what they wanted to do and the analysis that they were going to do. But given this massive impact that COVID had on on society and and on inequality as well. A lot of projects then decided that this would be a really important aspect to look at and an opportunity also to learn about inequality in a changing societal context. So different projects have taken this into account in different ways. But for example, there's been kind of really important work on on just what happened to inequality for example, due to lock down and and the economic upheaval of COVID, not just the health implications, but then also using that upheaval, to think about how inequalities might be changed. And for example, so work by Alejandra Rodríguez Sánchez, Suzanne Harkness and Anette Fasang, looking at what happened to housework, during COVID. People were having to stay at home, both parents and children and seeing what happens to inequalities between men and women. And how the, the the number and age of children influences that and kind of what they saw was that obviously, this change in in family habits changed house work habits, but at the same time, when locked down ended a lot of couples returned to normal. So so even though there was a massive shift, and and people behaved differently for a short period of time, we can see that these kind of entrenched habits, then then go back to normal quite quickly.

Christine Garrington  6:43 

Yeah, really interesting piece of work that so. And also, despite COVID, you were able to, nevertheless, to involve a great number of stakeholders in in the research, what messages did you receive from them, I wonder about what was emerging?

Elina Kilpi-Jakonen  6:58 

So yeah, we've had some really interesting discussions with stakeholders, both policymakers and then kind of non-governmental organisations involved in both practical work and lobbying as well. And they've been really interested in in the work that we're doing. So in particular, we've talked to stakeholders involved in kind of gender inequality work, and how participation in the labour market is unequal between men and women, and in particular, between mothers and fathers. And then we've also talked a lot to stakeholders involved in kind of childhood disadvantages, and how different types of children are put at a disadvantage. And what are some of the mechanisms kind of potentially either alleviating those disadvantages, or that are currently making those disadvantages larger, and that would kind of be important to look at. So we've kind of talked both about the the bigger picture of inequality, but also some of the mechanisms and obviously, stakeholders are, are often interested in what they can do. And then we've also had really good discussions about especially with policymakers also about the kinds of data that going forward, would be needed to, to kind of really analyse these things further. And I think there's a lot of kind of shared interest in collecting data or making administrative data available for researchers to be able to address inequalities in the future.

Christine Garrington  8:28 

Yeah, now a major part of your role, Elina has been to pull together all of these different strands of work in some way to ensure that we get to a, what we hope is a coherent picture of what's been learned from the programme as a whole. And I wonder whether it's possible in the short period of time that we have to say what has been learned from the programme as a whole?

Elina Kilpi-Jakonen  8:48 

Well, that's no mean feat. To then kind of say what's been learned because I think there's such richness in the research coming through and I mean, we've only kind of touched upon some of the aspects just now. And so we what we've been trying to do is, is bring together kind of thematically, things we've learnt in terms of, for example, gender inequalities, as I just mentioned. So So really looking at further at kind of motherhood, penalties and how, how those might be potentially for example, by by further training ameliorated although at the same time, we need to remember that women tend to nowadays have higher education levels than men. So education isn't always the key here. So also looking at kind of gender and sexual minorities, even though we've been making progress in terms of legislation and policy. The discrimination can still be kind of an ongoing issue for people and and kind of the legacy of the past is still a major issue for for LGBT citizens across Europe and even though legislation has progressed a lot to still the practices in terms of, of workplaces or educational institutions aren't aren't really catching up necessarily, to such a large extent. And then moving on to kind of a different area, I think there's been a lot of really interesting work in terms of, of the role of genetics, which is a big new area of research in terms of social sciences, and how that plays into the reproduction of inequalities across generations and over the life course, and how that changes depending on the environment that people live in. So, so we're learning a lot about so called gene environment interplay, and which is obviously kind of something that social scientists are really keen to look at is the the environmental aspect of, of how genes play out. So so we're learning a lot about the fact that genes aren't our destiny as such, but but the the context or the environment matters a lot for that.

Christine Garrington  11:00 

Yeah, lots of really fascinating and very, very innovative work that's going on in that area, for sure. Now, you're talking about stakeholders a moment ago, you've been responsible also for helping to ensure the dissemination of this research to to those non-academics as well as other researchers. So I'm interested to know and I think others will be interested to know what sorts of resources there are available. For those interested to know more, aside from the obviously, the dozens, and I know, there are dozens of journal articles and working papers that have have been produced if you'd like for the scientific community. But what else is there.

Elina Kilpi-Jakonen  11:34 

Starting from those journal articles, I think we've tried to make a kind of effort to make those more accessible in terms of both bringing them all to our website, but also providing summaries that are not just the academic abstract. So even looking at the journal articles, starting from from summaries that are more accessible to everyone involved, and not just researchers in those fields, I mean, abstracts can sometimes be a bit difficult to disentangle. Then bringing together the research we've we've been producing policy briefs that, I mean, obviously are aimed at policy audiences but I think those bring together thematically some of the research as well in a really nice way. So those are available on the on the website, then obviously, this podcast series, I think is has been a great way of disseminating the research. In addition to that, so we had our final conference last autumn. And some of those videos from the presentations are available still through the website. I mean, there's both recordings of presentations that bring together entire projects, but also kind of individual, more finely specified research topics. But But in particular, there's there's videos of researchers presenting their whole project at the final conference. So I think those are also a great resource.

Christine Garrington  12:57 

Yeah, indeed, a wonderful library of materials that people can dip into at their leisure and really catch up on and get to grips with the important things that have emerged from this, this work. So finally, Elina, the ultimate aim of a programme like this is obviously to improve our understanding and knowledge on the one hand and influence change for the good with the understanding on the other. And I wonder if you're able to say how, I know it's very difficult, but if you can say how all this important work might feed into the thinking and policies of those seeking to reduce inequalities today, and in the future?

Elina Kilpi-Jakonen  13:32 

At the same time as advancing academic knowledge, we definitely have wanted these research results to be relevant for policymakers and to reach policymakers and indeed, kind of other organisations interested in in these types of inequalities and processes. I mean, on the one hand, there has been really great comparative work on the kind of institutional influences that policies in different countries have and I think that's a really important thing to draw from in terms of, for example, education policy, or family policies for work life balance and the gender inequality in pay so, so looking at the across national differences and comparing countries and then learning from that. But then also, I mean, there's been really detailed work into kind of the mechanisms of inequality and more specific interventions for example, and how those influence inequality and and then really digging more deeply into how inequality is reproduced and what we might be able to do about that. So for example, work on on parenting and how that reproduces inequalities among children and and then thinking about well, how we might be able to to provide more equitable parenting for children and what we can do about that. So I think there's, there's been work on multiple levels that hopefully we'll be able for policymakers to draw on in terms of developing these things in the future.

Christine Garrington  15:07 

Thanks to Elina Kilpi-Jakonen, DIAL's scientific co-ordinator for joining us for the final episode of this fourth series of the DIAL podcast. You can find all the resources that Elina mentioned in this episode on the DIAL website at www.dynamicsofinequality.org. We hope you enjoyed this episode, which is produced and presented by Chris Garrington of Research Podcasts. And don't forget to subscribe wherever you find your podcasts to access all our earliest series.

In Episode 5 of Series 4 of the DIAL Podcast we’re in conversation with Andreas Peichl, Professor of Macroeconomics and Public Finance at the University of Munich and Principal Investigator of a DIAL project looking at the impact of childhood circumstances on individual outcomes over the life-course (IMCHILD). 

 

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series four, we're looking at what's been learned from DIAL projects about how and when inequality manifests in our lives, and what its longer-term consequences might be. Today, we're delighted to be joined by Andreas Peichl, Professor of Macroeconomics and Public Finance at the University of Munich, and Principal Investigator of a DIAL project looking at the Impact of Childhood Circumstances on Individual Outcomes over the Life-Course. So, welcome, Andreas, thank you very much for joining us. And I wonder if you can start by telling us a bit about what this project has been investigating and why?

Andreas Peichl  0:39 

So the project IMCHILD the Impact of Childhood Circumstances on Individual Outcomes over the Life-Course, had the aim to investigate how early decisions that usually parents make for their children's are really at the beginning of life, the early childhood, how these what we call circumstances for the child. So this is something that children typically cannot influence. Because these are decisions by made mostly by parents, how these circumstances affect decisions later in life. So for example, the transition to adulthood, be it educational or occupational choices, family formation, or later labour market outcomes. And the really, the idea was to see whether we find that the early childhood circumstances matter later in life. And then the next question, if this is the case, was what are the causal links? What are the mechanisms for this? And also, what can policymakers do about it if they aim at achieving something like equality of opportunity? So what can policymakers do to to level the playing field, so to say, later in life.

Christine Garrington  1:54 

Now, I'm interested to know as we record this conversation, COVID is something we certainly seem to be learning to live with right now, although COVID wasn't an issue, when you started this project, it certainly became one. And you've taken time to consider which children have been most affected by school closures for example. Can you tell us a bit about what you found there?

Andreas Peichl  2:14 

First, what we found is that in any country that we looked at, and especially in Germany, that was the main focus of this part of the analysis, but we also looked at other countries. That low achieving students, so students that were already not doing too well, in school, they were affected the most. And at the same time, students from non academic parents and lower socioeconomic status backgrounds, they were also affected the most. So sometimes, it's a combination of those two factors that are the same children, so low achieving, and low socio-economic status, but it's not exclusive. So, in general, low achieving students and lower socio-economic background, especially non-academic parents, those were the kids that were affected the most by, for example, school closures. But in general, we see that there was a large decrease in learning time for all students in school. And so basically, the whole cohort, were really affected by this.

Christine Garrington  3:21 

Right and, of course, as we, as we say, as we talked about learning to live with COVID, there are going to be already are, if you like longer term implications of this for children, educators and policymakers who are keen to ensure that any pre-existing inequalities don't become more deeply ingrained. Have I got that right?

Andreas Peichl  3:42 

Yes. So it's, it's really through it, we need to make sure that these existing inequalities don't become large. And right now, it looks as if they are becoming much larger actually. And we also see that this has long term impact. So if you lose some part of a school year, so for example, if you lose 1/3 of a school year, this, we can find or in the past, this was associated with a drop in lifetime income of 3, 4 or 5%. And so this, this can have huge implications for the generation of students affected. And so it's really important because we will have to live with COVID. And we need to make sure that we don't have to close schools, again, by investing in digital infrastructure and so on and making it possible that even when people are at home or this case, also not only for COVID, but also for other reasons that they can still participate in schooling. So this will be really important.

Christine Garrington  4:46 

Yes, indeed. Let's move away from COVID. One of the project's key aims was to investigate how the circumstances as we said that a child grows up in influences some of the most important decisions they make later on, you mentioned in your first answer about education and work and all of those key decisions that can take us down a certain path. Tell us a bit more about what you were hoping to get to really sort of get to grips with here.

Andreas Peichl  5:13 

So the starting point for research is rooted in the philosophical theories of distributive justice. And they, and also from an economic point of view, there's always the question, how to tackle inequalities. And in general, there are three ways to tackle inequalities. One is, the typical way is what we call redistribution. So this is, after all, the labour market outcomes, for example, are observed and we put a taxes and pay transfers and benefits to people to redistribute incomes. But the philosophical question then is, when we do this, how much do we want to redistribute how much inequality in the labour market do we want to have? And we know that for efficiency reasons, it's not good to have perfect equality, because then people don't have incentives to work and or to earn income. But we also know that very extreme inequality is not very good. But we don't know exactly where this optimal level is. But what we know is that there are other inequalities, where it's clear that this is something that we don't want. And this is what we in one paper, we call it unfair inequality, or this is inequality, where it's beyond your control your your poor, because there's something that you cannot influence. And this is what we wanted to investigate in this project. What are these circumstances, that children but also people later in life, have that make them for example, poor or rich? So is it the parental background, or we are in some work, we're also we're looking at the genetic endowment of people, but also other things, the places where you grow up could matter. And then it's important for policymakers, if you start tackling these inequalities already early in life, then maybe you don't need so much redistribution later in life. Because if there's a level playing field, and everybody has the same chances to achieve incomes, then typically inequalities in the labour market will be much less pronounced as they are today. So it was really the aim to see how much of the inequality that we observe today, for example, in labour earnings, labour market outcomes, how much of this can be explained by by early childhood circumstances already?

Christine Garrington  7:35 

And what were the key things to emerge from the work that you did?

Andreas Peichl  7:38 

The first thing is that, that we came up with some novel ideas and measures how to exactly measure this, this unfair bit of inequality to really disentangle this, not only in theory, but also empirically and, to some extent, also, using some some novel methods. For example, machine learning and big data ideas, in some ways or another. But also, the other thing was really trying to auto assemble also data, large datasets in paper in Sweden, really looking over several generations to see what is really the, the impact of these childhood circumstances. But what we see is really that childhood matters a lot. I mean, it's not surprising, everybody, I think, if you if you think back of your own childhood, or if you're, if you're having kids, you see how much impact parents can have have on children. And if there's inequality in let's say, how good parents are or how parents treat their children, then it's clear that this will lead to inequalities down the road. And so but I think what what's really interesting in our research was to put numbers on this to really see which inequalities seem to matter more and which maybe to a lesser extent, and then also trying to get at the main mechanisms and sort of the causal links between what it was what is it really that has an impact on on outcomes of children later in life?

Christine Garrington  9:15 

And you wanted to really sort of dig deep and see how those decisions that we've been talking about translate into later, later life social and economic outcomes, didn't you? What did you see there?

Andreas Peichl  9:27 

So yeah, we see that it's really that these these childhood circumstances matter in later life so it's, they matter directly in early childhood and then when when kids go to school or to high school, so really educational choices, but also educational performance is affected by these early childhood circumstances and then it continues, it's it's occupational choices, that matter it's but it's also we see impact on family formation - when to marry when to have children be it earlier or later in life, this is affected. And it matters for for labour market outcomes for career aspirations for, and then for for which jobs for which incomes people earn and so on. So it really matters all the way. We're also still working on projects to see whether it matters for early retirement decisions, for example, in general retirement decisions. So it seems to be that really the whole later life is affected by these early childhood circumstances.

Christine Garrington  10:39 

Yeah, that's so interesting. And I know that, you know, you are particularly keen to see whether you could actually, you know, really find causal links between early life circumstances and later life outcomes, you know causality, something that we know is always very, very difficult to show. But could you see that in any anything you did?

Andreas Peichl  10:58 

Yeah so we were looking, we were, of course, trying to establish causal links. But the perfect design research designed for to establish a causal link is to have some random allocation of the treatment and then have a control group. But it's, of course, not possible to randomly assign children to parents. So you need to come up with with different ways for for to identify these causal relationships. And typically, you can look at, at policy policy reforms and one policy that is affecting children are parental leave policies. So there's variation across countries, but also sometimes within countries. So for example, in Germany, there was a difference in these policies between former East Germany and West Germany. And what we see is children where the parents had more parental leave time, paid parental leave, when the kids were born, and were young, that these children later in life were happier. So they had a higher life satisfaction, then compared to children, where the parents didn't have as much paid parental leave, and then didn't take up as much parental leave. So it's really that also that these these policies at the very beginning at the start of the life, so like parental leave, has an impact. And so that's something where policy makers can start with. Another thing is what you can see is in schools, when you have, for example, all day schools versus only schools in the morning, or until until lunch, which is where there's a lot of variation, also within Germany, across states, you see that if you have these all day schools, there is a positive impact on on grades and also then later attending the university track. And in in the end on going to university for children. Which is basically also sort of to some extent levelling the playing field a bit because it's taking out the, the influence of part of the influence of parents on on the learning success of children. And so this is really this having this all day schools and parental leave and related policies can have an impact and can reduce inequalities later in life. So this is really important also for policymakers to think about it.

Christine Garrington  13:24 

Yeah, some really interesting and important findings from your project, Andrea's and I wonder for you, personally, if you like, was there anything that really surprised you or was a real standout?

Andreas Peichl  13:34 

So I think there were many interesting findings, and it was not completely unexpected that childhood circumstances matter. But I think what surprised me the most is that in a developed country, like Germany, it's these early childhood circumstances really matter all the way, basically until retirement. And it's and that a lot of policies are in place to with the aim of levelling the playing field, but they do not really succeed. So for example, in Germany, kids from parents with an academic background, about three quarters of these kids go to university, whereas only less than 20% of kids from non-academic background parents go to university. And it's all the schooling and the resources that are put into the system don't seem to help here. And so in many other countries, developed Western countries, it's not better in some countries like the US it's even worse. And so that's really something where I think the the policymakers in the in the next years need to put emphasis on to really make sure that we can somehow achieve equality of opportunities.

Christine Garrington  14:52 

Yeah, I wonder if you would say that there's anything that we've learned from your project that we really didn't know before?

Andreas Peichl  14:58 

We always knew that these circumstances matter, but we did not really maybe know how much and some of the causal links, but I think one thing, what we have also investigated and are still working on is also the impact of, for example, genetic endowment. And this is something where in recent years, there were advances where such data became available. And we can really see that, that this really matters for in their associations of your genetic endowment with other outcomes later in life. And this is really something to think about and what to do there. Because the policy implications there are not so clear.

Christine Garrington  15:39 

Yeah, that's such a fascinating area, for sure. Now, I mean, you've you've said a lot already about policy, which I think has been really, really interesting and important. But for all of those interested in tackling inequality through interventions in policy or practice, I wonder if there are any sort of essential takeaways or recommendations from this work that you would want to share?

Andreas Peichl  15:59 

So I think, if you want really want to tackle inequalities, much of the focus currently, I think, is on redistribution. So after all, the labour market outcomes are there and people earn incomes, but I think that's, that's really too late. Our project shows you need to start much earlier. So it's really you need to tackle it before people go to the labour market. So really education, and it's important and to to level, the playing field there. And there, especially it's the early childhood education so that other people have already shown that it's the first three or six years that are really, really important. And so for policymakers, they should put much more emphasis on, let's say, schooling and educating teachers for this early childhood education. And in a lot of countries. One thing is that child care, it's typically it's child care and not child education at these ages, as it's called, so it's making sure that the basically the kid survives the day, but it's, it's more important, so you need to really also make sure that the kids start learning something so this and then parents often have to pay for it, varying amounts depending on the country and so on. But so you should make this free for really from the beginning from starting with six, eight months old, this should be free and there needs to be enough educated teachers for the different age range. So to really start with very early ages, because typically what we see in many countries is that the children from from better off parents go to these these institutions, but not those from the from worse off parents and so it's really about the starting there to level the playing field because if you only do it later with redistribution, then it's too late and you've missed all the chances to change something.

Christine Garrington  17:57 

Thanks to Andres Peichl for discussing the findings and implications of DIAL's IMCHILD project. You can find out more about this and other dial research on the website at www.dynamicsofinequality.org. We hope you enjoyed this episode, which is produced and presented by Chris Garrington of Research Podcasts. And don't forget to subscribe wherever you find your podcasts to access earlier, the forthcoming episodes.

 

In Episode 4 of Series 4 we're talking to Professor Sakari Lemola from the University of Bielefeld and formerly from the University of Warwick. Sakari is one of the Principal Investigators of the DIAL project PremLife, which has been looking at what factors can provide protection and increase resilience for preterm children’s life course outcomes. 

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series four, we're looking at what's been learned from DIAL projects about how and when inequality manifests in our lives, and what its longer-term consequences might be. For this episode, we're delighted to be joined by Professor Sakari Lemola. He's from the University of Bielefeld and formally from the University of Warwick, and one of the Principal Investigators of the DIAL project, PremLife, which has been looking at what factors can provide protection and increase resilience for preterm children's life course outcomes. So Sakari, thank-you so much for joining us today. It's great to have you on the DIAL podcast. I wonder if you can start by telling us a bit more specifically what this project has been investigating and why?

Sakari Lemola  0:45 

So the PremLife project has been particularly focused on the role of protective factors for social and educational transitions after preterm birth. Preterm birth is defined as birth before the 37th gestational week. Then there are two further categories one distinguishes between moderately to late preterm children at its birth between the 32nd and 36th gestational week - moderately and late preterm children. But they're also very preterm children who are born before the 32nd gestational week. So in the PremLife project, we specifically look at both of these groups - the very preterm children and moderately and late preterm children compared to term born children and try to figure out what are their disadvantages they have in their lives? And also, what are protective factors that may improve their outcomes? In some domains they actually do really well when certain protective factors are present.

Christine Garrington  1:50 

Can you tell us something about how common preterm births are?

Sakari Lemola  1:54 

The incidence of preterm birth has been rising in the last few decades. So in the UK, around 7% of all babies are born preterm each year. This means that two children in an average sized primary school class are likely to have been born preterm and in spite of the advances in neonatal care of preterm birth in the last few decades, and also decreasing mortality rates, which is a very good thing. Negative long term, sequels and consequences of preterm birth have still remained, particularly for very preterm children, those born before the 32nd gestational week that means eight weeks too early or even earlier than that. That leads to medical complications, which often require distressing but life saving treatments frequent are, for instance, neonatal asphyxia, hypoxia due to immature lungs. Necessary treatment involves ventilation, continuous positive airway pressure, surfactant treatment, but also treatment with stress hormones, prenatal corticosteroids treatments to accelerate the long development.

Christine Garrington  3:10 

And so Sakari what does life look like for those children compared with their full-term born peers?

Sakari Lemola  3:16 

They often have an increased risk for poor cognitive development, they show poor educational outcomes, less favourable employment outcomes in adulthood and increased risk for developing mental health problems. And in the PremLife project, we try to specifically answer the question, first of all, of course, what are protective factors for those born preterm. But also we try to focus also to figure out out about what are the social and emotional development of the preterm birth, particularly related to social relationships, wellbeing and things like self-esteem and self-confidence.

Christine Garrington  3:58 

Now, there's considerable policy interest across Europe and indeed elsewhere and ensuring that obviously, that children get the best possible start and in helping those children who for whatever rate, whatever reason may not get off to the best start. How has your work tied into that sort of policy context would you say?

Sakari Lemola  4:17 

In the PremLife project, we particularly aim to answer what can be done by policymakers, by practitioners, stakeholders to improve preterm children's and adolescent development? So two focal points were, one was on preschool training in math and literacy. The second point was about how schooling should be organised in general. So we compared school systems in Germany, where so called school tracking takes place. That means children are sorted into higher or lower tracks after the first few school years and we compared Germany with the UK and Finland where no school tracking takes place. That means better and the lower performing children remain in their school classes in the UK and in Finland. But children with special needs they receive remedial teaching but they are not sorted into a different school or different school classes. A third focal point was related to physical activity in childhood and adolescence and what role physical activity actually plays for mental health and social emotional development.

Christine Garrington  5:32 

A key piece of work from the project involved the assessment of adults who had been born preterm. What was sort of the main thinking, the main driver for for this work?

Sakari Lemola  5:42 

Previous work has shown that preterm children have an increased risk for poor cognitive development and they also show poor educational outcomes. And particularly, most work has focused on childhood, but less work on later outcomes like adolescence and also in adulthood. In the PremLife project we have now also focused on adolescence and adulthood. And also particularly, we focused on differences in socio-emotional outcomes in adulthood, particularly regarding social relationships, a topic that has previously been neglected So, children who were born preterm in adolescence and in adulthood, they seem to be less satisfied with their social relationships, they are less likely to be partnered in adulthood, and they are also have decreased fertility so they are less likely to have children on their own later in life.

Christine Garrington  6:44 

Okay, and what were the key things then to emerge about how those people who were born preterm faired later on in life?

Sakari Lemola  6:52 

So we found out that children born preterm to still show differences compared to their term born peers, when they are grown up particularly. Yeah, they show more mental health problems, particularly anxiety disorders, they show lower wellbeing then full term born children in friendship relationships, they are less likely to experience intimate relationships in adulthood, they are less likely to become parents on their own. Somehow, it is likely that anxiety and shyness play a role which is increased in preterm children, they are more anxious about making a step for instance, in social relationships, and that may lead to lower rates of being partnered and becoming parents themselves.

Christine Garrington  7:47 

Okay, now, you made some key recommendations from this. Can you talk about those recommendations and just how practitioners, policymakers and those people born preterm might benefit from from those recommendations?

Sakari Lemola  8:00 

With regard to schooling and education outcomes a key recommendation is the importance of early training and early support in math and literacy. So what we found is that preterm children, they appear to disproportionately benefit from preschool training in math and literacy. So, preterm children who perform well in math, reading and writing when entering into school, so very early on age of five, six years, they were more likely to receive GCSE grades that qualify later to go to university than their term bond peers actually. However, it was exactly the other way around for preterm children who perform poorly in math, reading and writing at school entry, they were less likely to get sufficient GCSE grades compared to their term born peers with similar preschool skills. So their skills at school entry, the skills and math, reading and writing appear to be more important for preterm children than for term born children. And that highlights how important early support and rhythm medial teaching plays there. A second point is that school tracking as it happens currently, is it's the current policy in in Germany, is a negative thing for preterm children probably also for for other children with early difficulties. Where people from a migration background who are not as fluent in German, for instance, as German children so children with more difficulties in school should rather receive remedial teaching but they should not be sorted out into lower performing school tracks as it is currently the case in Germany. We compared it with the outcome of preterm children who go to school in Finland and in the UK, and they seem not to have that. There is no such a negative effect of the school tracking because there is a different policy in the UK and in Finland.

Christine Garrington  10:11 

And what about the social and emotional side of their lives? What did you find there Sakari?

Sakari Lemola  10:15 

Here we had focused on two factors that appear to be relevant for preterm children. So this involves sensitive parenting on one hand and physical activity and playing sports in childhood and adolescence and preterm born children benefit from both from sensitive parenting and physical activities, such as playing sports. So both factors seem to increase self confidence and have to be considered as protective factors against the negative outcomes of preterm birth, particularly negative outcomes regarding social and emotional development.

Christine Garrington  10:53 

So much interesting research to emerge from this project Sakari. I wonder what the key things have been for you, things that have really caught your eye or have been of particular interest to you, things that maybe surprised you?

Sakari Lemola  11:05 

I think the key findings and surprising findings are that this early training in math and literacy, writing and reading are disproportionately important for preterm children compared to term born children. And this may generalise also to other children who may have a more difficult start in school for them. Most probably it is important to have early support. A second important finding was related to the school tracking that means the grouping of the children to higher and lower performance levels in school. So this has a particularly negative effect on preterm children, as we found out in Germany with an effect that, of course, isn't present in the UK where there's no such good tracking.

Christine Garrington  11:53 

Okay, that's really helpful. Now, you've been really active in sharing your findings, not not just with academics, but health practitioners and policymakers. I know what has been the response from them, I'm interested to know.

Sakari Lemola  12:03 

So overall, we had very positive feedback from practitioners and policymakers and we are also confident that the messages will be heard, but of course, time will tell what will be applied and what not.

Christine Garrington  12:20 

Thanks to Sakari Lemola for discussing the findings and implications of DIAL's PremLife project. You can find out more about this and other DIAL research on the website at dynamicsofinequality.org. We hope you enjoyed this episode, which is produced and presented by Chris Garrington of Research Podcasts. And don't forget to subscribe wherever you find your podcasts to access earlier and forthcoming episodes.

  

In Episode 3 of Series 4 of the DIAL Podcast, we are in discussion with Richard Blundell. Richard is the Ricardo Professor of Political Economy at UCL, director of the ESRC Centre for the Microeconomic Analysis of Public Policy at the Institute for Fiscal Studies and the principal investigator of a DIAL project looking at human capital and inequality during adolescence and working life. In this episode we explore the work done by this project tackling inequalities in adolescence and working life.

 

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series four, we're looking at what's been learned from DIAL projects about how and when inequality manifests in our lives and what its longer-term consequences might be. For this episode, we're delighted to be joined by Richard Blundell, David Ricardo Professor of Political Economy at UCL, and director of the ESRC Centre for the Microeconomic Analysis of Public Policy at the Institute for Fiscal Studies. Richard is also the principal investigator of a DIAL project, looking at human capital and inequality during adolescence and working life. So welcome, Richard, thank you very much for joining us today.

Richard Blundell  0:40 

Thank you, Christine.

Christine Garrington  0:41 

I wonder if you can just start by telling us a little more specifically what this project has been investigating and why.

Richard Blundell  0:48 

Yeah, I'd be delighted to. What we're looking at in this project is the evolution of inequality through adolescence and working life. Relating to the education streams, people choose how it affects their outcomes going forward into working life, what happens during working life, what kind of training seems to work, what routes to better jobs are for people who don't, for example, go to higher education, university. Whether training can offset some of the gender gaps that we've been seeing opening up in the labour market, and whether choices in higher education matter for future labour market outcomes. So it's very much about not the early years of school - there's another project looking at that, that runs in parallel with our project, similar investigators, we're working together with them. What we're looking at here then is from adolescence onwards, and how the inequality evolves during adolescence and working life.

Christine Garrington  1:58 

So one area of focus has been women and work really very, very interested in in this, you've looked at the gender pay gap, the role of childcare, on women's ability to return to work, and indeed, on the role of job training, among other things. So what would you say for you are the key things to have emerged from this particular area of work Richard?

Richard Blundell  2:18 

Yes, this is obviously absolutely central, the kind of pay gap between men and women and how it opens up through working life is something that's been really hard to tackle and getting behind this, what are the drivers of it, and how to address it is really key to solving some of the most important inequalities that we see in working life. We're working with researchers, mainly economists, and education researchers in Norway, in the UK and in France. That's rather good, because those three countries have rather different systems of routes through education, into work, and different opportunities for women and men as they progress through their working life. And we wanted to understand what those differences could tell us about the gender pay gap. And therefore what policies could be perhaps most useful in addressing the gender pay gap.

Christine Garrington  3:25 

There are a couple of key things to come out of this one there.

Richard Blundell  3:28 

Some of its, you know, in some sense, pretty obvious. That is that work experience is really important for pay and for earnings as you go through your career for career progression. And of course, when children come along, women spend a fair amount of time not in work, perhaps still in employment on maternity leave, but not actually gaining the work experience that turns out to be so important in career progressions. We've kind of known that. But it's become really acute, even part-time work is really not sufficient for women to keep up at work with their male colleagues. There are two kind of routes to addressing this. One is to provide good quality childcare, that can have two major benefits. One is it can provide good quality inputs and care for children, which is particularly important, especially in disadvantaged families. But it can also allow women to spend more time at work and developing their career profiles. There's also a very large importance of mothers and fathers spending time with their children. And so when children come along, it's kind of inevitable, really, that work may take second place, and that there'll be less time engaged in work experience in progression. And remember, it's exactly these years in the 20s and early 30s, where all the big career progression is made in working life, and women really fall behind there. So an alternative we've been looking at, and it turns out to be rather interesting is to work instead of on work experience, but on the human capital itself, once women come back into work.

Christine Garrington  5:25 

So what might that look like in reality, then Richard?

Richard Blundell  5:27 

So you can imagine the following scenario, a woman or a man, but unfortunately, it's particularly typically, the woman who takes time off, once she returns to work, you can imagine her engaging in a training programme, and that can make up some of the loss. Well, we weren't that optimistic about that to begin with. But we've become more optimistic for two reasons, particularly in the UK and in Norway. In Norway, using the Population Register, we can follow people, right the way through their working careers, we can follow the whole of the Norwegian population. It's an exhaustive data set on everything everybody does - their qualifications, where they're working, their family structure, and so on. And what we found is that it's particularly successful for women to who've had a child early on in their career to return to some kind of schooling qualifications, and that can have a big boost to their career profiles and address some of the gender gaps that occur. In the UK it turns out similarly, women who returned to work spend quite a bit of time in training. And we found that that training, work related on the job training, it has to be accredited, and it has to be work related, those things have a payoff. And we feel that there's real room for improving this type of training. It's all part of designing education and training routes, during your working career, that work much better than the ones we currently have. And boy in in the UK, we've been training way behind in the organisation of formal routes into education and training through your working life, especially for those who don't go to university.

Christine Garrington  7:29 

Now, I want to move on to talk about COVID. And obviously, although not expected when your project began, the pandemic, obviously, as well as being a terrible thing for us all did provide, however, what I'm guessing was quite a fascinating and important opportunity to look at the impacts of COVID on on people's lives in this context of inequality. So what did you, what did you get to focus on there?

Richard Blundell  7:52 

Once we were into the first major wave of COVID, it was clear that it was going to exacerbate a lot of the inequalities during adolescence, during education and during working life, let alone health of course. The longer run impact that we're seeing is on learning - the loss of learning, the loss of school time, the loss of engagement in learning, because of being not able to go to school, those children from deprived families have had much, much more learning loss over this period, than the privilege than children in more privileged families. It suddenly became clear that space was really important. But for learning for children, it was absolutely critical. If children didn't have a quiet place with good digital access, a good setup for engaging in online classes, then that already put them behind behind. And there's many studies showing there's a huge gradient in space, in digital access, in access to these kinds of technologies across the income and and socio economic gradient. Losses have been extremely large, up to half a year of schooling loss for many, many children. The second point is that if you're at home with educated parents, who are working from home and still have time to interact with you, you're going to get that input from them. schooling is the great equaliser. It puts children from deprived backgrounds in an environment where they can learn perhaps things that they couldn't learn at home. And that was taken away. The work on Norway and France shows exactly the same there. So learning loss, huge. This doesn't usually happen in recessions by the way. This was very, very specific to COVID.

Christine Garrington  9:55 

And what about when you looked at matters related to work.

Richard Blundell  9:58 

All on the job training, apprenticeships just didn't happen. In fact, for those in their early careers, you know - 18, 19, 20 - there was an almost complete end to apprenticeships. Apprenticeships fell back by 70% or more for that younger group, exactly the group that I was mentioning before. It's vital that we get this on the job, accredited training, because they're the ones not going to university, those going to university have been served rather better. I know from my experience here that we've at UCL, we've been keeping online classes and activities going at a pretty high level, actually. And the kind of students that we have here, can engage in that quite fully. But that's very different for a student who didn't make it to university, and who's trying to gain their experience and training through apprenticeships, there's just been no engagement. So this loss of learning has been huge.

Christine Garrington  11:11 

I'm interested to know whether women were worse affected than men in this context?

Richard Blundell  11:16 

We thought it might affect women more but in fact, overall in employment and what have you, it's been pretty neutral in the UK, that's just because of the structure of industry we have here. But it hasn't been neutral at home. We've seen, of course, mothers and fathers both having to do more childcare, because schools have been closed during lockdown, or children have been at home during self-isolation, even in periods without lockdown. But mothers of taken, have borne the brunt of the childcare at home, we followed women and families in surveys throughout COVID. And found that although childcare activities have increased for both male and female parents, there really has been an extra load on women. And again, that's going to affect their careers, and other aspects of their life going forwards. All those things that we were concerned about before COVID. And that were the absolute centre of this project have all become all the more heightened through COVID. And I think the policy recommendations that have come out of this project are very, very relevant for the post COVID world that we're now entering.

Christine Garrington  12:41

Yeah, I wonder how how easy it has been? Or how difficult I guess it's probably the better question to to feed those recommendations in such a fast moving event that COVID has been and, you know, was it possible for that to feed through all of those findings, all of those important things into the policy sort of making cycle in order to try to mitigate some of those impacts? Or, or was that that must have been very challenging.

Richard Blundell  13:09 

For policy makers, at least civil servants have been very open, of course, to try and to figure out what's been going on. And remember, the initial policy responses, at least on simple measures of inequality have been remarkably successful. You know, we haven't ever had a recession, really, where there's been so much support thrown into the economy, of course, we're gonna have to pay for that. But some of the short run impacts, I think were mitigated, what we've focused on here, are the longer run ones, you know the the loss of learning, the loss of training, the loss of work experience, they're not showing up even yet, they're going to show up in the next few years. And it's critical, we have an opportunity now to address them. And there is a lot of interest across the whole policy world, and government and around the world. In addressing this. In fact, as part of this project, we fed into the G20 meetings last year in Rome, and a major part of our work was used to suggest a kind of coordinated approach to designing the best interventions now to address what's been going on with loss of education, and loss of work experience and training across more or less the whole developed world.

Christine Garrington  14:27 

Really great to hear that there's been such an appetite for findings like these important findings to feed into policy, but I guess the devil is in the detail, right?

Richard Blundell  14:37 

Unfortunately, these are gonna have to be huge programmes. And the thing about huge programmes is that they can be hugely expensive and not necessarily very effective. We need to get this right. We need to get these education interventions and these training interventions done in the most efficient and effective way. And that's where we can learn from other countries that do at least some things better, some things worse, we're all learning from each other. And this project which brought in, you know, Norway, which has a pretty effective system of education and training right across the board, not just for those going to university, which is where we tend to focus. And France, which has, again, a very different system. So we can learn, we can learn from that. But yeah, I see a long impact of COVID, not just long COVID. But it's hidden a bit at the moment, by the way, because of the uptick in the economy. You know, there's quite a demand for certain types of jobs, as you'd expect, when there's, you know, we're coming out of a big, big recession like that, but I'm pretty sure that that's hiding these big losses, they will turn up over time. So yeah, there's, there's a big hunger for this. We're feeding a lot of a huge amount and working a lot with Department of Education here with the Treasury on what what should be done with other policy groups. And similarly in Norway, and France.

Christine Garrington  16:08 

Now, I know we've talked about the labour market a bit, but I wonder whether there's anything else that you really would like to stress about that side of things, because this was a major part of your work?

Richard Blundell  16:19 

We had to invent things on the hoof and everyone was involved in that the furloughs remember, the furlough system didn't exist. In fact, in the UK, and in many other economies, we've not, we've not been particularly good at providing general what one might call social insurance. That is, if people fall on hard times get reduced earnings, you know, do we make up the difference? At least in the in the shortish run, we don't particularly do that very well, in the UK, we target very low incomes. We have a very targeted universal credit and benefit system. So it does prop up incomes at the bottom. And it does that actually quite well. Not always administratively perfectly, but it does it. But if you look at someone who's on a kind of lower middle income, which is the group that really was hit during COVID, there's very little support for them. Universal credit doesn't do a great job, it just doesn't replace their incomes - the furlough system did it replaced 80% of their income. And, and it was very successful in doing that, to the extent that as I said, you know, income falls and inequality increases didn't happen in the way they often do during recessions. So in that sense, these policies have been very successful. On the downside, you know, they're the things I mentioned, they've been very good at short run income support, at least for for many groups. But they've not been very good yet at addressing these losses in, in human capital investments. And work is about two things. It's about earning money today. And it's about in investing in skills that will earn you even more, or give you a better career profile, at least in the future. And it's those longer term investments that I feel, or a fear of being really left to one side.

Christine Garrington  18:17 

I wonder whether you've seen anything that relates to how these inequalities manifest in respect of where people live, where they come from, is there something around place that's quite important as well?

Richard Blundell  18:28 

We kind of knew there were geographical differences and differences by family background, it just, you know, we can see that in workings of our society. But I didn't realise how big they were. And I think it's been quite a shock to us. It's not surprising, you know, that the emphasis now is on levelling up, at least it's suggested it is in education is very important. What we found in this research, you know, looking at how well people do at school, and then into university, if they go there, and then into work is really striking, you know, some areas of the UK, for example, and this would be true in other economies as well, by the way, very few children actually make it to university. Take areas like Grimsby or Skegness those kinds of places we almost think of as left behind communities, children just don't do so well. And not only that, if they do manage to get into higher education, they often don't return to those communities. So those communities, once you look at people in work that just have many, many fewer people with higher education qualifications and skills to other areas. Let's call them the thriving areas, many of which are in the southeast or in the more successful cities. And these differences are really important because they're having huge impacts in the way people think about their well being levelling up political discourse.

Christine Garrington  20:07 

You talked earlier a bit about their fabulous data in Norway that you had available to you. But we've also got some great data here in the UK, haven't we, particularly when it comes to tracking young people through education?

Richard Blundell  20:20 

We have the National Pupil database that follows all children through school, through higher education, or through their education and training and into work right up to about the age of 28/29 now. So we're, and that will go on. So this is a remarkable, a remarkable dataset of the kind that you would typically think of finding only in a Scandinavian country. So this has allowed us to do these differences. And we can look at two children doing exactly the same courses in the same university, and just look at the differences of outcome by parental background and they're still there, they're still quite important. So parental background really matters. But so does course choices and university choices. These things, I guess we knew that have a big impact. All these things that people are doing through their their education, and early working lives and at university have a long lasting impact. And many of the differences you can take back to geography, and parental background, and the early education investments. This is really providing a real detail in what's driving the inequalities that we see at least in working, working careers.

Christine Garrington  21:47 

Yeah, on that note, I'd like to put a final question to you really about, you know, for those interested who in tackling inequality, obviously, including yourself and your fellow researchers, the wonderful team that you've talked about there. But for those who have responsibility for creating interventions through policy or practice, are there any essential takeaways, implications or recommendations for your project that you'd like to share?

Richard Blundell  22:11 

If there's something we're going to really have to address the in the UK and elsewhere it's these geographic divides. It's what is creating a lot of the political turmoil, I think, whether it be almost in any elections, we've seen the left behind areas. You know, the evidence is clear, these geographical divides, by socioeconomic background, and by areas are really important and long lasting. And it's really up to us to figure out the best ways now, to address them as quickly as possible. They've been exacerbated through COVID and so they become even more urgent, I think, in the policy debate.

Christine Garrington  22:56 

And I guess my final final question, is there something specific that we should be focusing on?

Richard Blundell  23:03 

There's a lot, but let me just pick on one, it's a kind of old topic, it's the it's the point about good jobs. You can have successful interventions for people who come from, you know, backgrounds or haven't been quite successful at education investments, you can make better choices during education. And we've seen how, with the data and work we've been doing, how that can be improved. But it's really the match of the skills, the firms and the kind of work related nature of these training investments that's so important. And what we have learned here is that, you know, small interventions on one aspect of this are not going to solve the problems. So you can think of the example of the, of just providing a job. What we've seen here is that just providing a job, say, Amazon warehouse job is not really going to help much with career profiles, you really need to match workers, develop their skills, and bring the right kind of firms that can enhance career profiles into these more left behind deprived areas. If we can get that to work, then there's great hope that we can do something for the careers and wage profiles of people who've been doing rather less well than we'd like in society.

Christine Garrington  24:39 

Thanks to Richard Blundell for joining us for this episode of the DIAL podcast. You can find out more on the DIAL website at dynamicsofinequality.org and also on the IFS website at ifs.org.uk. Much of the work of Richard and his colleagues has also fed into the Deaton Review on inequality so do take a look there as well. We hope you enjoyed this episode, which is produced and presented by Chris Garrington of Research Podcasts.

In Episode 2 of Series 4 of the DIAL Podcast, we are in discussion with Professor Hans van Kippersluis from the Erasmus University in Rotterdam. Hans, a professor of applied economics, is the Principal Investigator on the DIAL project, Gene Environment Interplay in the Generation of Health and Education Inequalities, which has used innovative methods and data to explore the interplay between nature and nurture in generating health and education inequalities.

 

Transcript

Christine Garrington  0:00  
Welcome to DIAL, a podcast where we tune in to evidence on inequality over the life course. In series four, we're looking at what's been learned from some of the DIAL projects about how and when inequality manifests in our lives, and what its longer term consequences might be. For this second episode of the series, we're delighted to be joined by Hans van Kippersluis, Professor of Applied Economics at the Erasmus University in Rotterdam. And Principal Investigator of the DIAL project, Gene Environment Interplay in the Generation of Health and Education Inequalities - put more simply nature versus nurture. So Hans, welcome to the podcast. And I wonder if you can start by talking us through what researchers working on this project have actually been looking into.

Hans van Kippersluis  0:42  
What we've been doing in this project is essentially incorporating the recent availability of genetic data into social science and most prominently economic analysis. And so most of our work has focused on the interplay between genes and the environment. So in the introduction, you mentioned nature versus nurture, but actually more accurately, what we're doing is nature and nurture jointly into how they shape essentially education and health outcomes. And I think this is also the main innovation of our project, because biologists have studied nature before; social scientists have  of course, extensively studied nurture, but not many have studied the interplay, the interaction between the two. And I think this was sort of the main innovation for why we got the funding some five years ago. And so what we have done is mostly studying this interplay. But along the way, we have also made some methodological contributions to a field which is very new. Then we've also used genetic data to test all their theories, and also, I think, enrich the framework of equality of opportunity.

Christine Garrington  1:35  
Yeah, fantastic project. And as you've just said, you've made unprecedented use of genomic as well as survey data in the research, tell us a bit more about the information that you've been able to access? And how you've been able to use it?

Hans van Kippersluis 1:47  
Yeah, sure. So the interesting thing is that more and more social science datasets, so data sets that have been traditionally used by social scientists, and these are mostly extensive surveys,  are now collecting DNA information from their respondents. And this is often from blood or saliva. And what they did is basically, so more than 99% of DNA is the same across human beings. And so what we are using is only this remaining less than 1% of the variation. And these are called snips. And snips are points of your DNA that differ across human beings. And there's roughly 1 million of them. And so what we do, basically also other people have done is sort of aggregating these tiny effect sizes into an index. And this is called the polygenic index. And this is telling us something about your genetic predisposition towards a certain outcome. And this is quite interesting, because this data, this new variable, essentially can be added to existing datasets. And so we have a wealth of information that has been collected in the past on surveys on existing data. And then we simply add one indicator, one new variable. This is telling us something about people's genetic predisposition. And just to be clear, this is not like a deterministic variable. It also exhibits quite a bit of measurement error and noise. But at the group level, and that's what we have been doing is it sort of does tell us something about your genetic predisposition, and it can help us understand how certain life outcomes like education, like health, are shaped by the interplay between your genetic predisposition and your environment.

Christine Garrington  3:07  
Indeed, let's talk a little bit now then about some of the research findings. And you know, what's come out of this now, one piece of research we've spoken about this actually, in an earlier podcast episode, actually drew links between mothers smoking in pregnancy and their baby's birth weight. I wonder if you can just sort of summarise that for you what actually came out of that what we learned

Hans van Kippersluis 3:28  
this was work with with my PG students, Rita Dias Pereira and colleague Cornelius Rietveld. And for birthweight we knew that maternal smoking is one of the key environmental risk factors. And we also knew from genetic studies that genes matter in determining your birth weight. And so what we did here was essentially looking at the interaction between the two. So can higher polygenic indices protect against maternal smoking? And the answer, unfortunately, perhaps was no, in the sense that we found very, very little interaction between genes and the environmental exposure of maternal smoking. So it seems that both matter, but there doesn't seem to be any meaningful interaction between the two. So that was, to some extent surprising, but on the other hand, also perhaps logical in the sense that maternal smoking is apparently such a devastating environmental exposure that even higher genetic predisposition cannot protect you from this.

Christine Garrington  4:16  
Yeah, really interesting. And anybody who's interested in that can listen to Rita actually discussing that in series three, Episode Seven, of our DIAL podcast called Mums Who Smoke and their Baby's Birthweight. So do check that out if you're interested to know a little bit more about what Rita and all of the all of your colleagues did. Now, there have been some interesting findings Hans from the project around the role of genes in a child's education and specifically around parental investments. I wonder if you can explain a bit more about what you were looking to understand there. 

Hans van Kippersluis 4:50  
Yes, yeah, so this is one of my favourites studies. It's joint work. Also with another PG student   Muslimova and my colleagues Stephanie von Hinke, Cornelius Rietveld and Fleur Maddens. And the starting point there was actually a theory of human capital formation from economics. And it dates back all the way to the work of Nobel laureate Gary Becker. And one of the crucial assumptions in that model is that parental investments are complementary to your genetic endowments. And this assumption is actually very hard to test because often we do not have a good measure of endowments. And if we do, it may already be contaminated by parental investment. So many people, for example, use birth weights. But of course, well as we just learned, maternal smoking may have a large effect on your birth weight, so it's not fully free of your parents' behaviour. And the other thing is that your parental investments often respond to endowments. So if you have a child with specific needs, of course, parents respond to this. So the problem of testing this assumption is that endowments and investments are actually always very closely entangled. And that makes it very hard to test whether they are complementary or not. So what we did here was using one's genetic endowment, and that is actually has a very nice property and that it's fixed at conception, so it cannot be affected by your parental investments. And what we did was using the child's birth order to proxy for parental investments. So what we know from earlier studies is that firstborns tend to get more parental attentions on average than later points. So this is one after all, because they have undivided attention until the arrival of later borns. And this extra parental investment is actually independent of your endowments. It simply derives from the fact that you have more time if you have one child as opposed to multiple children. So what we did in this study is looking within families comparing siblings that were first born to later borns, and then further analysing whether this firstborn advantage was stronger for firstborn siblings who randomly inherited the higher polygenic index for educatio. I think this was a nice, very unique setting to test this theoretical assumption that parental investments are complements to genetic endowment.

Christine Garrington  6:45  
What did you find here? Then what do we learn about the role of genetics in affording in affording certain children advantages later on in life?

Hans van Kippersluis 6:53  
So what we found was that indeed, the firstborn effect seems to be stronger for siblings who randomly inherited higher polygenic indices. And I think this is evidence in favour of this theoretical assumption of complementarity between endowments and investments. And it also means that your genetic predisposition cannot just give you a direct advantage. But it also means that this advantage may be kind of amplified by your parental or your teacher investments. And this complementarity, I think also suggests once again, that for disadvantaged children, so the other side of the coin, we need to start very, very early and follow up these early investments also with data investments to make them as productive as possible.

Christine Garrington  7:29  
So Hans, some fascinating research and findings. I wonder if there's been a standout or surprising finding for you from the project. 

Hans van Kippersluis 7:36  
I  think methodologically, what we've learned is that there's still a world to explore in terms of using genetic data in social science, because what we have seen is that polygenic indices can be a great tool to improve our understanding of the things we just talked about. But I think the way we use these polygenic indices, are shall I put this sort of a bit naive, in some sense, because what we do is we first construct a score or an index by regressing an outcome on all of these 1 million individual genetic variants. And as you can imagine, if you do these 1 million regressions, then it will be a lot of noise in  these coefficients, and these estimates also come with some uncertainty. And what is surprising to me, what I've learned is that many researchers simply sort of seek to use this polygenic index as if it's some kind of a transferable and deterministic index. And there's hardly any account in the literature on the uncertainty in this index. And I think what we have done in one paper is actually showing how this uncertainty is sort of leading to different conclusions, because what we did is basically looking at the polygenic index for cardiovascular disease. And in cardiovascular disease, more and more people are using these polygenic indices, this genetic data for personalised decisions regarding, for example, the use of statins. And what we did was sort of constructing six different polygenic indices using different discovery sample using different methods of constructing this polygenic index. And what was fascinating and actually maybe astonishing to see is that only 6% of the individuals are in the top quintile of the polygenic indices, if you look across these six different ways of constructing the same polygenic index. And I think this is fascinating, because it shows that even though polygenic indices are now increasingly being used, apparently it matters a great deal about how you construct these things. And this is one thing we have shown, I think this is quite remarkable, and also an important methodological contribution.

Christine Garrington  9:19  
A really important contribution to how this research might develop in the future. Right, absolutely. And then just finally, Hans, I wonder what this all of this work tells us about the interplay between genes in our environment, or, as we've talked about nature and nurture, not nature versus nurture, in better understanding and in tackling inequality.

Hans van Kippersluis 9:41  
So it's very hard, I think, to give sort of direct policy leads or implications, but there's a few leads. One thing is that I think we need to start early. We knew already that inequalities arise early in life. And I think this focus on genetics gives us yet another clue that it's very important to start early. And also because of the work I mentioned about complementarities, it's very clear that later investments are more effective if the person has had already more investments early in their life. So that's clearly one more general policy implication, I think. And I think our work is also showing how sort of genes and environment shaping jointly inequalities. And I think this has important implications for the discussions about equality of opportunity. I mean, if you look at politicians across the entire political spectrum, everybody seems to be agreeing that equality of opportunity is a great thing, and that your health and your income should not depend on your parental background. But let me ask two questions about this. One is, what about your genes? There's hardly any discussion about whether inequalities that are deriving from genetic advantages or disadvantages are fair or not. And what we've also shown in this project is that parental background seems to reinforce genetic advantages. So even if you believe that parental background should not be leading to inequalities and your genes may, then how do you treat the interaction between the two? So I think we should have a clear discussion here a societal discussion about what is fair here. And I think that's why our research is very important, because 30 years studies have already shown that people's preferences for redistribution, for example, depends strongly on whether they perceive inequalities as fair or unfair. So I don't think we are political activists here. But I do think that showing how genes and the environment jointly shape outcomes such as health, education, income, but really help people to make up their own mind as to what they regard as fair or unfair inequalities.

Christine Garrington  11:23  
Hans thank you very much some some big advances here. But still some big questions to answer, I guess is the is the summary but fascinating work and thank you for taking time to share it with us. So finally, thanks to Hans van Kippersluis  for discussing the findings and implications of DIAL dial project Gene Environment Interplay in the Generation of Health and Education Inequalities. You can find out more about this and other dial research on the website at www.dynamicsofinequality.org. We hope you enjoyed this episode, which is produced and presented by me Chris Garrington of Research Podcasts. And don't forget to subscribe wherever you find your podcasts to access earlier and forthcoming episodes.

 

 

In Episode 1 of Series 4 of the DIAL Podcast we're in discussion with Professor Kjell Salvanes and Dr Helen Wareham to talk about the impact of inequality on the lives of children. Kjell is the Principal Investigator on Growing up Unequal? The Origins, Dynamics and Lifecycle Consequences of Childhood Inequalities while Helen is a Research Associate on the project Social InEquality and its Effects on Child Development. 

 

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to inequality over the lifecourse. In Series 4 we're looking at what's been learned from DIAL projects about how and when inequality manifests in our lives, and what its longer-term consequences might be. For this first episode of the series, we're delighted to be joined by Professor Kjell Salvanes and Dr. Helen Wareham to talk about the impact of inequality on the lives of children. Kjell heads up a project called Growing up Unequal? The Origins, Dynamics and Lifecycle Consequences of Childhood Inequalities, while Helen is a research associate on the project, Social InEquality and its Effects on child Development. So Helen, let's start with the work that you and your team have been doing, looking at how young children are getting on and where inequalities might be occurring. I wonder if you can just start by explaining really a bit more about that the main focus of your project.

Helen Wareham  0:50 

So the main focus of SEED, that's the acronym we have the project is to identify the mechanisms that social inequalities have on children's, particularly their oral language development, and where we can try and identify what patterns there are in those inequalities, and the impact that it has, and whether those continue throughout children's lives, and into adulthood as well. We're a team of around 20 researchers, and we're quite a broad range of specialists. So we have everything from speech therapists, developmental psychologists, but also medical staff, so ENT, ear, nose and throat specialists. And we're spread across a number of countries, as well. So there's a sort of focus around the countries involved in the project. So that's Germany, the Netherlands and the UK, but also how we can look across those different countries and with broader collaborations with teams in France, the USA and Australia as well.

Christine Garrington  1:44 

So tell us a bit about what your team of 20 researchers in all these different countries has been actually doing over the last few years.

Helen Wareham  1:51 

In the three main countries for the project, we have really rich cohort data. So that's where people have been interviewed they've there's been kind of assessments that have happened with children, quite often from birth, and then they've been tracked at regular points throughout their lives. And these create really rich data sources. So we can look at what happens in children's lives and how that then changes over, over time. Because we have this rich data, we're able to look for really complex novel methods to try and understand the impact that inequalities have on children's lives over time. And a lot of the work in our projects has been driven by PhD students. They've been looking at everything from the impact of slight and mild hearing loss on children. So my colleague Lisanne who's based at Rostam University in the Erasmus Medical Centre there has found that there's a significant impact on behavioural and school performance in children where they have the kind of slight or mild hearing loss, that's all just so clinical, but just enough that it's obviously then impacting their later life. And then my colleagues, Natalie and Wei have been looking at the interactions between parenting behaviours, and children's language and behaviour development. And then my colleague, Claudia has been looking particularly at instances of sort of poverty and how that impacts on children's language development.

Christine Garrington  3:12 

I know you've been very successful as well Helen in engaging more broadly with this work outside of the research and the academic community.

Helen Wareham  3:20

While we've kind of been doing a lot of this very in-depth research, we've also been able to engage more broadly with policymakers. Right at the start of this project, through our partnership with the Liveness Association, we were able to meet with some members of the EU Commission to discuss our project. We were given the opportunity as well to comment on some early care and education guidelines that the Commission we're working on, and that that's since then been published. So well, yeah, quite a bit of over the last few years I suppose.

Christine Garrington  3:50 

So I guess what we're keen to know, what many people will be keen to know, that is, after all of this work, what would you say are sort of the key things that have emerged that that maybe we didn't know, before, now, you've had this opportunity to delve so deeply into these issues.

Helen Wareham  4:04 

There's sort of three key things that have come out of this. One has been, we've really been able to look really in depth at some of these relationships to kind of get an idea about how some of these relationships work. Some of the nuances I said, you know, about parental behaviours and interactions with children. And that's been great. But then also, I think one of the really key things we found is just how persistent inequality is, and how significantly it impacts on families and then children's lives and it's a really it's not just a persistent relationship. It's it's deeply entrenched, in that persistant-ness, it's very slow to change that. So when we think about inequality, we often think we can make a change and it will kind of happened within someone's lifetime, when we're looking at, you know, what happens over the course of a child's life. But actually to resolve certain inequalities, we're really looking at some of this being a multi-generational approach that no matter how good a start, we sometimes we're able to provide all the interventions we can deliver, that isn't going to necessarily manifest in that child's lifetime, it could be two, three generations later.

Christine Garrington  5:18 

Now that's all really interesting. I think we'll come back and talk about that a bit more in a second Helen. And Kjell, I'm guessing that quite a lot of what Helen has just said resonates with, with you. And I know there's a real synergy between what Helen and her team have been looking at and what your projects been investigating. So let's just take a step back here and get you to talk us through what it what it is that you've been trying to get to grips with.

Kjell Salvanes  5:39 

The background for our project is, you know, the increased inequality that we're seeing in many countries. What we are trying to do is to understand, you know, increase in the socio-economic gradient, as they say, you know, the difference between different groups of people. And in particular, we're interested in inequality, showing up both in education, but also, in terms of behaviour, you know, crime and stuff like that.

Christine Garrington  6:04 

Tell us a bit more about some of the specific things you were looking at, and why.

Kjell Salvanes  6:07 

Precisely we try to understand how shocks in a family are affecting their children in different stages of the life of a kid. The other part is, the importance of public policies, let's say day-care policies, family leave policies, and how that can affect the development of children, and especially what economists call investment in human capital or education or their skills. And also how the dynamics in the families how that is important how, you know, let's say there is an income shock, because Dad loses his job, how the dynamics in the family being changed, and the role or the mom and the dad, in affecting the children.

Christine Garrington  6:50 

I know, you have a fantastic team, largely economists from leading institutions in Norway, France and the UK, but you're interested in broader things, including health, you know, particularly around child development and, and outcomes. So tell us a little bit more about how you've gone about looking into these questions.

Kjell Salvanes  7:10 

I mean, we are using data - very detailed registered data from Norway, and France, and also partly now from the UK. And we are combining these type of approaches using registered data, which sort of consists of generations of families, and also combining it with experimental work, interventions, and also surveys.

Christine Garrington  7:35 

and what does all this fabulous data and these methods enable you to do?

Kjell Salvanes  7:40

You can look at the whole development of kids from, you know, pre birth basically to, then we can look at adults, but you can also look at up to, let's say, 60. A lot of what we have been doing is to try to distinguish between the impact of something that is happening early on. It could be a negative shock, it could be policy intervention, or it could be parental decisions early on preschool, you know, middle years of schooling, and then early teenage. We see a lot of differences, you know, before they start school. And then the question is how this interacts with what is happening in the, in the early and later school years. We looking at different types of skills. I mean, you know, so it could be, you know, more the cognitive types of school skills, but it could be also socio emotional skills, how you you know behave.

Christine Garrington  8:36

Indeed and can you talk us through what what's emerged that you think is of particular interest?

Kjell Salvanes  8:42

You know, one of my colleagues at UCL Gabriella Conti, her work and partly together with us have been looking at early health outcomes for kids, and how that can predict the performance of kids when they are teenagers, but also as adults. So I think that part of the project has been very important. The second thing that I will speak a little bit is that, you know, one of the teams in in Paris, they have looked at training programmes for the children in daycare. So they have actually looked at an intervention among daycare teachers, and trying to set up a programme where they can teach language acquisition skills, you know, from the age of three months to three years. And that also seems to be have had a very positive effect, because, you know, language skills, or skills at the age of five seems to be very predictive of what is going to happen with children as adults. And the third thing that, you know, we'll talk a little bit about a project that I've done myself where we look at the kids growing up that was born to teen moms, which is a big issue in many countries. In the UK, for instance, I think, you know, more than 20% of the kids are being born to teen moms. And how that effect their adult acquisition of human capital and how they how well they perform in the labour market. And what we find there. And I think this is a new finding is that it's not only the mom that is important, I mean, usually in the literature, you find that this has a negative on average effect on the kids in their later life. What you find here is that the role of the dad is also extremely important. The matching, so to speak in the, in the non-marriage market here, you know, who they get the kids with, is also not without selection. So the selection of kids, for these kids is important. And the role of the dad is also extremely important, not only the mums, which of course, has strong policy implications.

Christine Garrington  10:54

Absolutely, absolutely. I mean, on that note, I'd sort of quite like to ask you both really, whether there's a standout finding from, you know, the wide range of research that both projects have done that you think that everyone who's interested in tackling inequality from as early as we possibly can, should know and understand. Kjell you want to kick us off?

Kjell Salvanes  11:14

Yes, I mean, we put together these three teams for some reasons, because the let's say the family policies differs a lot across these three countries. The Norway is one of the Scandinavian countries have a very active family, family policies, parental leave since the mid 70s, and stuff like that, and also daycare coverage 100% now. France is a little bit in between and you know, and not so active family policy in the UK, I have to say so. So there are differences. And what we see is that the impact of family policies on child development seems to be very important. And I think that also has, of course, clear policy implications.

Christine Garrington  11:58

Yeah, Helen, is that I'm guessing that's something that possibly resonates with with you and your project as well. But is there one particular thing that you think is, it's really important that everybody takes away from all of this?

Helen Wareham  12:10

Yeah I think, particularly from our projects, and I think Kjell has been sort of saying this as well is about how important it is to realise that right from the start of children's lives, it's a vital time, you know, inequality doesn't wait. It's right there from the start. So I think, in tackling inequality, knowing and understanding that the inequalities that are there, in families, in parents to be, are then transmitted to their children, and that then affects children's later life outcomes. And I think what we've really learned from our work is we've learnt lots of sort of small pieces of information about the kinds of activities parents can be doing, particularly relationships in child development, you know, kind of between the relationship between children's language development and their socio emotional development. But ultimately, those things are mediated, they're heavily influenced by wider household opportunity and resource that's available. And if we aren't able to ensure that people have those opportunities to interact with their children, to spend time with them to be able to do activities with them. Either because their economic situation doesn't allow it, or they simply don't have the space and resources available to do those kinds of play activities, and talking and reading with children then continues the cycle of inequality.

Christine Garrington  13:39

Yeah, no, that's so interesting and important. And I wonder, so what are the wider implications of these findings? So we talked a lot here about, you know, about policymaking and policy makers and early intervention. But for those sort of seeking to design those interventions to tackle inequality, or even practitioners working in the fields, such as teachers in schools, who may also have a role to play in this, you know, what are the takeaways for them? Helen, you go first, and then I'll move to Kjell.

Helen Wareham  14:07

I think if I'm honest, this is actually quite a difficult question to answer at the minute. Because inequalities, you know, we see the landscape of inequalities, you know, I think the acronym DIAL referring to inequalities as dynamic, I think, is really useful and interesting, because inequalities react to global events. Which we, you know, we've experienced over the last few years and are continuing to see, but kind of inequality at the centre of that doesn't really change and it hasn't really changed. And I think that's something that's really important to acknowledge that we understand a lot about the nuance and the mechanisms and how inequalities affects people's lives. But there's still a fundamental issue at the centre of that about the key factors of inequalities that haven't changed. And I think then that means as a, as a researcher, I can sort of provide evidence about some of these relationships and even put together interventions that will help children catch up with their language development at a later point. But it doesn't address the fundamental issue. That kind of we've created as a society, you know, where parents aren't able to spend time with their children, because they're having to work three in four jobs. So you know, working 14 hour days, to ensure that children have a roof over their heads and are fed. I think it's a lot to ask of teachers, there's a lot of strain on teachers already know, they're kind of going above and beyond, when I think schools are struggling to even heat classrooms. It's hard to know kind of what to put out there as what policymakers can be doing and practitioners as interventions, when I think we have a kind of responsibility to address those fundamental needs. So I think that means as a researcher, what I have to do is kind of advocate for that greatest viable change. And let people know the you know, the evidence is there of what interventions we can deliver. But we've got to get people to a point where they can, you know, parents can spend time with their children, and talk to them and read to them. And children can go to school, and be in an environment where they're able to accept and receive learning, and people can go to work and feel that they can go and do the job and not have so many other concerns.

Christine Garrington  16:24

Yeah, absolutely. No quick fix no simple answers, right? And Kjell I'm guessing again, a lot of that probably feeds into your thinking too.

Kjell Salvanes  16:34

Yeah, you know, so at least partly, what I tend to find is that there has been strong improvements both along the differences across, you know, in terms of education, you know, from different children from different backgrounds, and also in terms of income. So there has been a lot of improvements, I think that is important to say, but are some areas where, we haven't seen so much gains, or there has been you know, it's more difficult, and especially among the very poor, you see also in the Nordic countries, that seems to be very difficult to get them sort of above a certain level. And so there's a lot of persistence at the bottom across generations. And also at the top, there's a lot of persistence, you know, the rich, do well independent and the poor do not do that almost independent of policy. So I think, to better understand these two mechanisms, and especially, you know, for the poor, what is it exactly? Why do don't they take more education? Why do they don't perform better in the labour market? What is it exactly? Is it lack of resources? Or is, do they have different expectations? They don't think that they can do it or is it information, they don't know about it, or they know about it, but cannot do anything about it, let's say because of the restrictions that Helen mentioned. So I think this is the area where I think we need much more to understand much more what's going on.

Christine Garrington  18:06

That brings me very nicely to my final question for you both, which is if you'd like is whether you have a feel for what needs to happen now? I mean, you've both alluded to it. But you know, both in terms of research, but in terms of how do we move things forward? How do we get to a point at which change can happen? And that's a difficult one I know, Helen.

Helen Wareham  18:25

It is a difficult one, because I think there's a lot of structural inequalities that exist. And those are difficult to change. And I think that that's thing as a sort of longer term view about what needs to happen. Now, and I think we are kind of globally at a very critical point. The pandemic, in particular, I think has highlighted to people the need for certain changes to happen, climate change has been another one where there's a real need and call for action. And for larger, more structural changes to happen. And I think that can go a long way to addressing kind of very fundamental structural inequalities. And that's it, it's, it's that need to look on a longer term beyond kind of quick wins and marginal gains. And that's where I think the research around child development, first couple of years of children's lives are so pivotal, an investment and a shift towards ensuring that children have the best possible start they can in life doesn't initially pay off. It's a long term strategy. But it means in 10-20 years time, what we get is a huge payoff in terms of a happier, healthier, more skilled workforce, and a real step towards breaking some of those inequalities. I think a shorter term thing about what could happen right now is I think the education gap we have particularly around those children who have kind of recently finished their kind of national standard level of education during the pandemic, you know, we've seen a widening in that education gap. Ensuring that as many children as possible have achieved a national standard of education, I think is is really key because we know that achieving that will create a shift and a potential to kind of open up opportunities for children to be able to go on to further study and improve their education or to be able to enter the workforce at a better point than we are seeing. So I think there's a real potential, there's a short term acting to make sure that the children, particularly those affected by the pandemic have been supported and are achieving at least a national standard of education.

Kjell Salvanes  20:33

And one of the things that sort of resonates what Helen is saying is that it has become clear that differences among kids is seen very early on, you know, before they start school. So that means that the family and early years are extremely important. And I think that was not the focus, let's say 10 years ago, it is the focus now. And I think we need to understand much more about that. So that is one thing you see also increased inequality, not only, you know, in a socio-economic dimension, but also regionally. Certain areas, let's say in England, Southern England, around London, you know, are prospering. I mean, while other places, let's say in the north of England, and the same thing in Norway, in the North of Norway and other places, they sort of are falling behind. So I think that dimension is also very important. It's not one thing that's going on the different things that are going on, and I think this is also has high has important implication for economic policies, you know, to stabilise those areas.

Christine Garrington  21:36 

Thanks to Kjell Salvanes and Helen Wareham for discussing what's been learned from their respective DIAL projects on this episode of the DIAL podcast, which was presented by me Chris Garrington of Research Podcasts. You can find a range of resources including working papers, journal articles, policy briefs, podcasts and blogs on the DIAL website at dynamicsofinequality.org.

In Episode 16 of Series 3 of the DIAL Podcast we’re discussing ability grouping in UK primary schools and how it affects children's enjoyment of certain subjects. Our guest today is Queralt Capsada-Munsech from the University of Glasgow, who as part of DIAL's LIFETRACK project has been looking at primary school children's enjoyment of English and Maths at age seven, and later at age 11 to see whether ability grouping positively or negatively impacts their enjoyment of those subjects. 

Does ability grouping affect UK primary school pupils’ enjoyment of Maths and English? is research by Vikki Boliver and Queralt Capsada-Munsech, and is published in Research in Social Stratification and Mobility.

 

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune into evidence on inequality over the lifecourse. In this episode, we're talking about how grouping children by ability at school affects their enjoyment of certain subjects. Our guest is Queralt Capsada-Munsech from the University of Glasgow, who as part of DIAL's Life Track project has been looking at primary school children's enjoyment of English and Maths at age seven, and later at age 11 to see whether ability grouping positively or negatively impacts their enjoyment of those subjects.   Queralt Capsada-Munsech  0:29 

There are people who are advocates of ability grouping, and their main argument is usually that high ability pupils improve their attainment, while there is no detriment in lower ability, once their academic performance mainly. But you know, the opponents in the general debate of ability grouping, what they say is that high ability students only do marginally better when they are grouped with a, yeah with a group of students that are homogenous to them. While lower ability ones are the ones that are substantially worse off from these ability grouping. And what we have seen mostly in previous research is that there is the main mechanism that we call that is the self-fulfilling prophecy of low attainment that you know, because you are grouping the low ability grouping and people, and students are aware of that. So they just know that they are not doing as well. And they continue to do more poorly while those that are in the high ability grouping, so they think better of themselves. And that leads them to better academic achievement. And usually, the way it has been measured has been based on what we call academic self-concept that basically is asking students, how good are you at maths, at English or at school in general? 

Christine Garrington  1:48 

So talk us through some of the policy context here - ability grouping as an education policy.

Queralt Capsada-Munsech   1:53 

In the gaze of the UK ability grouping was encouraged by the New Labour governments in the 1990s and in the 2000s. And the main idea was that it would raise standards generally, with higher grades in brightest kids in particular, that was something that was quite influential in past decades. And that had clearly an effect in policy because, you know, the prevalence of grouping practices still remains in place. And it increased quite a lot for the past few years. And we see in the UK, even that ability grouping is becoming increasingly common in early years, you know, at ages three and four and even in Key Stage One ages five to seven was, which was something that we didn't see in the past. While you know, in the 1990s, there were fewer than 3% of primary schools who reported that they were streaming students by 2008 16% of seven year olds, were being streamed by ability for all subjects and 26% were being taught in ability sets for English and Math so that's quite the change.

Christine Garrington  3:01 

What was it for you that you wanted to look at exactly about the way in which children are grouped by ability at primary school? What was it you wanted to look at and why?

Queralt Capsada-Munsech   3:10 

Empirical evidence what did show us that at least for the UK suggested that there weren't many benefits of practising ability grouping. Mainly at the secondary level was most of the studies and it did little to raise the school's standards, and it was more detrimental for socioeconomically disadvantaged students. And it was through that, you know, measured ability at the early ages is predictive of ability group placement. But so were also a lot of socio-economic indicators. So there were also a few mechanisms, you know, that people were looking at. So for instance, teaching practices or teaching learning environments. So the reason why this happened, that it was more detrimental for some instruments to the individual than others because teacher quality is correlated with ability grouping, meaning that mainly you know, teachers that are more qualified, more experienced tend to be a placed with a high ability grouping, while less experienced in the lower one, which maybe should be the opposite. But also because of students self-perception, so they internalise these labels of consequences for their self-esteem. We could see that there were many studies that had been undertaken at secondary level, but not that many at the primary level. So what we want to talk that was that academic enjoyment so that it would be different question like, how much have you enjoyed reading or doing number work or English or maths more, more precisely.

Christine Garrington  4:45 

So why was it important to look at how much children enjoyed subjects? What was it about that particular concept or idea that was was important in your research?

Queralt Capsada-Munsech  4:56 

Academic self-concept, the question how good you are at? It's informed by students awareness of their test scores or their ability group placement, but it's also a relational construct, you know how good you are compared to the rest of your pupils in your group or in your class. While academic enjoyment, we thought that it was a more an intrinsic motivation and is more of a personal preference, you know, you might like or dislike reading, even if you are very good at English or not. So it's more of an independent one. And it's less relational. So it's not that you enjoy reading compared to your peers, it's more they do you enjoy it more? Yes or no, or to what extent.

Christine Garrington  5:39 

So talk us through what you actually did.

Queralt Capsada-Munsech  5:40 

The question that we wanted to look at was looking okay, for instance in primary school at age seven, how much did pupils enjoy Maths or English and school in general? And then to look later on, you know, at age 11, before going to secondary school, how much they enjoy again, Maths, English and school in general. And to see to what extent it had changed from age seven to 11, depending on the ability group that they were in. So we were expecting that, okay, maybe your academic enjoyment of Maths might be different to those that are in the top or bottom ability group. But our hypothesis was that, theoretically, there is no reason for people to change how much they enjoy or not enjoy reading, for instance, from age seven to eleven, regardless of the relative group they are in.

Christine Garrington  6:38 

So where did you get your information from? And why was it a good source of data to help you address these questions that you were interested in?

Queralt Capsada-Munsech  6:47 

So we use one of the cohort studies that are called, that its the Millennium Cohort Study. But basically, it's a longitudinal survey that follows about 19,000 people born in the UK in 2000 and 2002, approximately. You have the same people, the same individuals, and they have been surveyed throughout their lifetime. What it was important for us in order to make this comparison is that we would have that data about the same individuals, but also that we would have like similar questions at two points in time. So in this case, for instance, because if we want to check if there is a change or not in academic enjoyment, from age seven to eleven, we needed to have this very same question of academic enjoyment at those two points in times. And in addition, obviously, we had some information about ability grouping. And so.

Christine Garrington  7:41 

And when it came to this question of whether being grouped by ability did in some way influence whether a child liked a subject or not, what did you see?

Queralt Capsada-Munsech  7:50 

If we start just with the descriptive statistics, we already saw, obviously, that there were some differences. So maybe it's worth starting by saying that, you know, overall, there was quite a lot of academic enjoyment among students. So the majority of them like a lot Maths, or reading or English, and most of the students so in most cases above 35%, were placed in the high ability one. And students that were placing the low ability one was usually smaller numbers like below 20%. That already gave us an idea of the distribution. But more importantly, yeah, when just looking at some bivariate descriptive statistics, we could see that those that are in high ability groups, tended to enjoy more Maths, for instance, than those that were placed in the low ability group. And that has stayed like, quiet similar when we look at it both at age seven, and eleven. So that's something that we could see just from the descriptive statistics.

Christine Garrington  9:00 

Now you had some very specific findings around maths didn't you? I wonder if you can talk us through what it was exactly that you saw there.

Queralt Capsada-Munsech  9:07 

Being placed in a lower rather than a high ability group at age seven, depress the probability of coming to enjoy continuing to enjoy or even to increasing your enjoyment of Maths by age eleven. And that stayed like this way even after controlling for you know, students measured ability in Maths, sex and social background at age seven. So we found that yeah, really being placed in ability grouping has an influence in your academic enjoyment of Maths. However, we didn't find quite the same for English and school in general. So, you know, there was this tendency, but once we control for socio-demographic and socio-economic variables, the results weren't statistically significant. So, we would say that, it's mainly for maths that we would find some differences or some effects of ability grouping.

Christine Garrington  10:05 

Yeah, really, really interesting, though, and I'm gonna take you right back to the beginning of our conversation when you were saying, you know, just how much policy interest there is in this area around, specifically around education policy. What do you feel that we must take away from from this piece of work? And do you think there are any key takeaways specifically for education policy and practice?

Queralt Capsada-Munsech  10:25 

Overall, I would say that our findings are very much in line with much of the existing research, which indicates that ability grouping is detrimental to those judged to be of lower ability. And at least we find it in relation to Math. So it's something to be worried about. And ability grouping by measured ability has a negative influence for those that label as that, as lower ability. And we can see now that it's for both for academic self concept this idea of how good I am at maths, but also for academic enjoyment is like how much do you enjoy maths? So that can be detrimental if you are put in a lower ability group.

Christine Garrington  11:08 

Okay, so that's the key sort of takeaway message, but what recommendations might you have in this area then?

Queralt Capsada-Munsech  11:14 

We are aware that it's difficult to be in a classroom and that we don't mean that because they are doing ability grouping they are bad teachers or bad educators. But yeah, I guess it's something that we'll have to continue exploring. And while some parts of ability grouping might work for some students or for some teachers overall, I wouldn't encourage the policy of ability grouping, at least in the UK.

Christine Garrington  11:45 

Does ability grouping affect UK primary school pupils’ enjoyment of Maths and English? is research by Vikki Boliver and Queralt Capsada-Munsech, and is published in Research in Social Stratification and Mobility. Thanks for listening to this episode of the DIAL podcast, which was presented by me Chris Garrington of Research Podcasts. You can find out more about all the DIAL projects at dynamicsofinequality.org.

In Episode 15 of Series 3 of the DIAL Podcast we’re discussing LGBT discrimination, harassment and violence. Our guests are Sait Bayrakdar from Kings College London and Andrew King from the University of Surrey who, as part of DIAL’s CILIA project have been using a large cross national survey to look at the experiences of nearly 29,000 people living in Germany the UK and Portugal.

LGBT discrimination, harassment and violence in Germany, Portugal and the UK: A quantitative comparative approach is research by Sait Bayrakdar and Andrew King and is published in the journal Current Sociology.

 

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the lifecourse. In this episode, we're discussing LGBT discrimination, harassment and violence. Our guests are Sait Bayrakdar from King's College London and Andrew King from the University of Surrey, who, as part of DIAL's CILIA project have been using a large cross-national survey to look at the experiences of nearly 29,000 people living in Germany, the UK and Portugal. I asked Andrew first to talk us through the background to the research.

 

Andrew King  0:30 

This piece of research is part of the larger CILIA LGBTQI project, which has been exploring inequalities across the lives of LGBTQI people in four European countries - England, Scotland, Germany, and Portugal. We had a large research team from four different institutions on the project. And they brought expertise from different disciplines, as well as different methodologies. So the main aims of the CILIA project were to study LGBTQI inequalities from an intersectional and lifecourse perspective and bring some comparative dimensions to this. We started with a literature review and survey mapping exercise, which helped us document what had been done so far in the area, then we went on to analyse various sources of data, as well as collecting a large qualitative data set from LGBTQI individuals in the four countries. But this research article reports on the research, which was a part of our quantitative strand.

 

Christine Garrington  1:43 

Okay, that's great. Thanks Andrew. I'm going to come back to you a little bit later in our discussion for your sort of reflections on what was was found. But Sait you were the lead author on this, and what was it specifically that you wanted to try to get to grips with and why in this particular paper?

 

Sait Bayrakdar  1:58 

We were aware from our qualitative research that despite over 10 years of equality legislation, issue of discrimination, harassment, and violence we're still very significant to LGBT people, but we wanted to look at this both quantitatively and cross nationally. In a nutshell, we were mainly interested in understanding the patterns of discrimination, harassment and violence experienced by LGBT individuals in these countries. But this was quite tricky, because most survey studies still do not collect information about sexual orientation or gender identity. And it is even more difficult to find an international study that collects data from individuals across different countries. One exception to this was the LGBT survey conducted by the European Union Fundamental Rights Agency. And this data allowed us to do a comparative analysis across the countries in the CILIA project. In fact, this really was the on the Pan-European data set that spoke to these inequalities. Also, we wanted to document the diverse experiences and patterns within LGB and T communities. Partly because of data limitations, and small numbers in surveys, these different groups are often merged in a single category as LGBT. Although their experiences differ quite a lot. And our results also come from these differences. Qualitative researchers are quite ahead in this regard. And they have done amazing studies showing the diversity in experiences and outcomes. We hope this research will help us show these differences quantitatively and highlight the need for better survey data collection that allows researchers to study LGBTQI plus lives in this way.

 

Andrew King  3:37 

So although we, there were four countries involved, actually, the dataset just puts everybody into a UK group. So we couldn't separate out England and Scotland. And the other thing is that the dataset doesn't include specific questions relevant for intersex people either. So we weren't able to include intersex people in the quantitative analysis that we did.

 

Christine Garrington  4:01 

Okay, yeah, understood. Now, what sorts of things were people asked about in the Fundamental Rights Agency survey then Sait? It just sounds, it sounds a really useful resource for this.

 

Sait Bayrakdar  4:12 

Yes, absolutely. So the respondents were asked about many things, including their demographic data and social identities, their experiences of discrimination or other kinds of unfair treatment, whether they report these incidents, whether they change their behaviour in public to avoid discrimination. They are also asked about their views about equality policies and their relationships with people they interact in their daily lives. It's quite a rich study, and I believe it is terribly under used by researchers. In this research, we looked at LGBT individuals experiences of discrimination, harassment and violence, and the survey was asking whether they had experienced any of these as a result of the person's sexual orientation and gender identity. We looked at how these differences differ for LGBT individuals separately, and how their social background affects their likelihood of experiencing this incidence.

 

Christine Garrington  5:07 

Yeah and large numbers of people took part in this survey as well. So, Sait let's dig a bit deeper now and move on to you know what everybody is interested to hear about, which is what you actually found - can you talk us through that?

 

Sait Bayrakdar  5:20 

Sure. So earlier, I said that we were interested in bringing forward the diverse experiences within and between LGBT individuals, and between different countries. And I can confidently say that we found out that there are quite striking differences across LGB, and T individuals. First of all, in all countries, trans individuals are more at risk of experiencing negative incidents of discrimination, harassment and violence. Compared to their cisgender, gay, lesbian, bisexual counterparts. This is perhaps not surprising for many, but this wasn't explored quantitatively previously in an academic study. And another interesting finding for me was that different groups were more prone to experience different kinds of negative incidents. For example, lesbians seem more at risk of discrimination and harassment, and gay men are more at risk of violence. We do not know why this is the case. But there is definitely an observable gender pattern here. And my feeling is that this might be related to the ways these identities may be seen as a threat to masculinity. And I think we should definitely need more research to look at these intersections of sexuality, gender, and maybe also other, other social identities.

 

Christine Garrington  6:38 

Yeah, some really, really interesting and important findings emerging here. And was the story the same across all of the three countries that you, you looked at?

 

Sait Bayrakdar  6:47 

Not quite. In the first instance, all three countries showed similar patterns in the likelihood of experiencing these incidents across different groups. In all countries, reports of discrimination and harassment were more common than reports of violence and trans individuals were more likely to experience all three forms of negative incidents but there were some interesting differences when we dug deeper. For example, the rates of violence are higher in the UK, which begs the question why the UK is less able to protect these individuals despite being a front runner in equality legislation? Perhaps another thing is that the reports of violence are particularly high for trans individuals and gay men in the UK. These two groups in the UK are more likely to experience violence than those in Germany and Portugal. And I think this suggests that contextual factors may be shaping some part of these experiences or the likelihood of experiencing these incidents. This is something that comparative data can help us understand a bit better.

 

Christine Garrington  7:47 

Okay, Sait so was there anything else at play? Any other factors that we should take into account or that you took into account that were important or relevant?

 

Sait Bayrakdar  7:55 

Yeah, so we included quite a few other variables relating to social identities and individual characteristics. I think the most important but perhaps not so unexpected finding was that those who have greater socioeconomic resources are less likely to experience these negative incidents. And this implies that class based social inequalities may have a role here as well. So for example, a more economically advantaged person may be able to protect themselves a bit better, whereas other less advantaged might unfortunately, be more vulnerable to such incidents. We found this effect to varying degrees in all countries. I think this is very important because it points out that intersections of class, sexuality and gender identity are creating unique experiences. Depending on one is positioned across different social demographics, the likelihood of experiencing negative incidents change. We also find that LGBT individuals with disabilities and minority ethnic or religious backgrounds are more likely to experience discrimination. It is really very important that we create more empirical evidence on these intersections looking at different life outcomes, not only discrimination, harassment and violence, but maybe also the outcomes of education, labour markets, and other domains of life.

 

Christine Garrington  9:15 

Yeah, no, absolutely understood. Now, what would you say then say, Sait that we take away from all of this in an era where, you know, many people assume or think, believe that discrimination on the grounds of sexuality and identity as somehow a thing of the past? I mean, your your research tells us otherwise?

 

Sait Bayrakdar  9:32 

And this is a very interesting question, which I also find difficult to answer. I think there has been an immense advancement in the equality legislation in the UK, as well as the other countries in our research. And public attitudes have also progressed significantly in recent years. And I think maybe, possibly because of these recent changes, some people may think that the struggle has now been won, and equality has been achieved. However, having legislation is one thing and putting it in effect is another. LGBT individuals still experience discrimination in their day-to-day lives, and the things heterosexual cisgender individuals take for granted are usually not available or accessible to the same extent to LGBT people. And I think that is because the norms and cultures in workplaces, social lives, families are shaped by cis-heteronormativity. So I think those with lived experiences have a better understanding of discrimination and whether or not it is a thing of past.

 

Christine Garrington  10:33 

And on that note, do you have any thoughts on the implications of all of this for, for policy, especially around efforts to promote greater equality, and diversity, you know, wherever we're at in the world, but particularly in these countries.

 

Sait Bayrakdar  10:47 

In this piece we provide quantitative evidence for many issues scholars have been discussing for a while. And we do this by providing further original comparative evidence, we knew that the discrimination, harassment and violence was there. But for me, the most important take home lesson is that there are country differences in the likelihood of experiencing these incidents. And we see that violence is more likely in the UK, particularly for trans individuals. We do not test the effect of potential factors, but our study does show that trans individuals are more more vulnerable to these attacks. So I think policy should really prioritise this. Trans rights have become a very heated topic for some years now. I must say, I think the way trans rights are discussed in the UK is not helping. As a policy priority the government and other policymakers should prioritise addressing trans people's very immediate needs and ensure that everyone regardless of their gender identity is protected from discrimination, harassment and violence. And another issue. Police documents don't always take account of diversity in terms of gender identity, sexual orientation, or variations in sex characteristics and intersex status. They often assume that LGBTQI plus communities are a homogeneous group, despite their characteristics and needs being quite different. I think there should be more engagement from policymakers with communities themselves, so they can see that they are working with diversity and difference. This should also take account of differences related to other social backgrounds, such as education, class, ethnicity, disability, religion, and possibly any other significant difference that people may feel or identify with.

 

Christine Garrington  12:30 

Yeah, thank you Sait for those really interesting reflections. And Andrew, I wonder if there's anything that you'd like to add to that?

 

Andrew King  12:36 

Yeah, an overall recommendation from the CILIA project is the need for intersectional policymaking. So policies tend to address people as single subjects and adopt a one size fits all approach, which in a way, erases differences. And as we've demonstrated in our article from an intersectional lifecourse perspective, this is really problematic. This means that we need policymaking that focuses on multiple and contextual marginalities as well as inclusions and exclusions and how privilege and oppression are created in multiple ways. So not recognising this intersectional diversity in policymaking, or perhaps only doing so in limited ways means people who embody the intersections of different and multiple marginalities get overlooked. So while some policies need to be specific, they should also recognise intersections. And we very much hope that our article and the wider CILIA project contributes to a new policy agenda in this respect.

 

Christine Garrington  13:46 

“LGBT discrimination, harassment and violence in Germany, Portugal and the UK. A quantitative comparative approach” is research by Sait Bayrakdar and Andrew King, and is published in the journal Current Sociology. You can find out more on the DIAL website at dynamicsofinequality.org. And don't forget to subscribe to the DIAL podcast to access earlier and forthcoming episodes. Thanks for listening to this episode of the DIAL podcast which was presented and produced by me Chris Garrington of Research Podcasts.

In Episode 14 of Series 3 of our podcast, we talk with Professor Andrés Rodríguez-Pose from the London School of Economics about his research looking at who propelled Donald Trump to power and what the future holds for populist politicians, politics and policies?  

 

Transcript 

Christine Garrington  0:01 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the lifecourse. In this episode, we're discussing the rise of populism in the US with Andres Rodriguez-Pose at the London School of Economics. He has been asking the intriguing question of who exactly propelled Donald Trump to power and what the future holds for populist politicians, politics and policies?

 

Andres Rodriguez-Pose  0:25 

I've always been interested in populism and the rise of populism. And I do it feel that many of the explanations of why people vote for, let's say, anti-system parties and anti-system options, were probably not the most adequate. Of many voters of populism have been considered to be uneducated, poor, rural and white men. And very often, it has been said that we just have to wait for these people to die and then the problem will sort itself out. I think that's first macabre and not a joke. And second, I do feel that that is also wrong. Because the people that are voting for anti-system parties, both in the US and in Europe, probably have got and certainly have got you know grievances that are related very often, to the long-term economic, social, cultural, and surface decline of the places where they live. But urban elites have tended and political elites have had a tendency to tell them that they are rednecks, that they are despicable, that they live in flyover states and in places where there's no opportunity, and the best solution for them is just to get on their bikes and move to a place where there's opportunity, which mainly means the big cities in from that perspective,

 

Christine Garrington  1:48 

Indeed, and so what was it about Trump's election and obviously near re-election, that you wanted to sort of hone in on and look at specifically and why?

 

Andres Rodriguez-Pose  1:57 

Trump, in my view, represented from his arrival, a threat to democracy and to American democracy that traditionally was the beacon of democracy across the world. It also represented the radicalization of the Republican Party that had been traditionally mainstream. And for me, that was really interesting trying to understand what had driven voters in certain parts of the US to vote for Trump, especially in the light of what Robert Putnam, probably the best known political scientist in the world from Harvard University, had written 20 years ago, well in 2000, about the potential threats. to threats to American democracy, which was where coming from, on the one hand, the rise of inequality in the US a country that is far more polarised interpersonally than Europe, but where territorial disparities are significantly lower. And the other challenge, which was the parallel declines since the 1970s, and 1980s of what is he called social capital, which is the sense of interaction, community, and cohesion within localities and within American cities, towns and rural areas.

 

Christine Garrington  3:15 

Now you went about this by carrying out an econometric analysis. For those of us who might not sort of immediately understand what that looks like, in reality, I wonder if you can tell us what you actually did?

 

Andres Rodriguez-Pose  3:25 

Well, I wanted to explain what is known as the Trump margin. So the additional votes that Donald Trump received in 2016, and then in 2020, relative to the votes that a perfectly mainstream Republican candidate in the 2012 election, like Mitt Romney had received. So trying to explain the additional extra percentages of votes in specific counties in the US on the basis of a series of factors I thought, and my co-authors thought that the additional vote for Trump was very much related to economic and demographic decline in particular parts of the US, but also I introduce, we introduced a number of what we call controls, which are the factors that either from political science or economics, or sociology have been regarded as the main drivers of the swing and the vote for Trump. And these are mainly related to individual characteristics, what I said before - levels of education, age and ethnicity of the voters in the case of the US, but also related to the places where they live. And there has been a lot of work that has highlighted the divide in the vote in the vote between big cities in the United States and small towns and rural communities.

 

Christine Garrington  4:49 

So what did you find then when you looked at the types of communities that it was thought propelled Donald Trump into into the presidency? What did you find there?

 

Andres Rodriguez-Pose  4:57 

Well we started with a hypothesis launch by Robert Putnam in 2000, about the idea that the threat to American democracy and therefore the vote for an extreme outsider like Donald Trump was coming from, on the one hand interpersonal inequality and the decline of social communities. What we thought is that just by looking anecdotally, at what had happened in the US that it was not the poorest of the poor, or the richest of the rich that were voting or voted in 2016 for Donald Trump. In fact, they voted together for Hillary Clinton, whereas it was mainly people living in declining communities, in places that had been seeing that people leave, jobs go, that their salaries were being depressed, etc. Those were the ones that were casting the vote. So our hypothesis was clear. It was not interpersonal inequality, and declining social capital, it was probably long-term economic decline in places that were still relatively cohesive. And this is what we found that on the whole, a country with strong interpersonal inequalities, the vote for anti-system candidates in this case, Donald Trump was not related to huge salary polarisation, although this might explode in the future. It was mainly related to long-term economic decline, in the form of loss of employment, but also to long-term demographic decline in the form of loss of population. By contrast, we saw no connection between declining wages and declining salaries and vote for Donald Trump.

 

Christine Garrington  6:41 

Really interesting. And now, it's also been said that the global financial crisis of 2008 was was a key driver. Did your research support that or not?

 

Andres Rodriguez-Pose  6:52 

Yes, we've done the research for every decade. So economic decline since the 1970s, until 2016 and 2020. The dates of the elections that we look at. 1980 to those years 1990, 2000 and 2010. Until then, and the 2008 financial crisis is the fuse, it's probably the last drop that actually made the glass on the water overflow, in places where that were very hard hit by the crisis in places where they have seen the loss of jobs accelerated to, for example, competition by trade, mainly coming from China. Those are the places where the switch from Mitt Romney to Donald Donald Trump, where the Trump margin increase the most those are the places that actually led to Trump winning the vote. But having said that, this is a far, far longer decline. That is there, we find evidence that for every single decade that we control all the way back to 1970, that in all cases, the decline in local population and decline in local employment is positively and significantly correlated, to more votes for Donald Trump.

 

Christine Garrington  8:05 

Okay, and what other key things emerge that you think, you know, really might be important in these years where we're looking back on we're living through still this incredibly intense period of American politics and European politics, global politics, and what what is played out?

 

Andres Rodriguez-Pose  8:22 

We saw the events of the 6th of January 2021 and the risk it has represented to democracy. But we have seen in the case of the UK, that something that is, probably hasn't happened for centuries, like proroguing Parliament took place without virtually everyone batting an eyelid. We're seeing how countries like Hungary, and Poland are moving away or drifting away from democracy. So what we have is a really, really serious threat to a system that with all its problems, and it's needed of reform has generated greater prosperity, greater equality. And I would say in the last 70 years in the developed world, the longest period of peace we have ever experienced. So with all its flaws, is probably by far the best system that we have. That what these anti-system let's call them populist politicians are offering might be apparently simple solutions, but in reality are far more dangerous and likely to just exacerbate polarisation and lead to conflict because these people feed on external enemies, whether real or imaginary. So there was a need for me to try to find potential solutions to this problem. And what has emerged from the research is that lack of opportunities, long-term economic decline, long-term demographic decline, long-term decline in service provisions to many communities in the US but also across most of Europe are at the root of the problem, we have a territorial problem. This is the situation we have, for example, in the UK where there, the need to level up is not just to reduce disparities, but mainly to tap on the potential of places that whether in America or in the north of the UK, for the past, where the motives of the US and the British economy and now are languishing mainly because of lack of political attention, but not just a lack of political attention, lack of belief, from political elites, and often from the population in big cities, but also from themselves, that they have got significant potential, and that this potential can be mobilised in order to lift their economies or lift their quality of life.

 

Christine Garrington  10:46 

Some really important insights there, Andres, thank you. But I just wonder if we might finish by asking you whether you feel that the research tells us anything about what the future might hold in respect of continuing support for Trumpism and more populism and populist policies?

 

Andres Rodriguez-Pose  11:02 

This is a deeply rooted problem, that it has been brewing for a very long time. And it requires sustained and serious policy solutions. We have seen in the situation in recent days in the UK with the publication of the levelling up white paper, that this has become centre stage of UK politics. But I do still feel that whether it is in the case of the UK, or in the case of the US or elsewhere in Europe, what we're finding is that many decision makers are paying lip service to the idea that there's a need to mobilise resources that there's a need to invest in areas that have been declining that there's a need on to tap on those resources. But in reality, there's a strong lack of belief that place based, place sensitive policies that respond to local challenges, but also mobilise local needs local potential, they think they're not going to work.

 

Christine Garrington  12:01 

And what from your point of view, would you say are the ramifications of continuing down that road?

 

Andres Rodriguez-Pose  12:06 

If we keep on doing this, we are in a situation where many people in our countries have said enough is enough, we have had enough of a system which seems to benefit someone else. And not us. That if we are asked to do let's say, an environmental transition? Well, we have. And this is the situation in France, what has happened is that diesel fuel taxes have increased, and we were told 15 years ago that diesel was the future. And now our ageing diesel cars, we have to pay for it. Whereas the people living in Paris, for example, they have alternative transport, they're richer so they can very often afford electrical cars. And we are paying for a transition that is driven by an urban elite that is aloof to our needs. If this is not addressed, these people have now have decided that they want to shake the tree and they want to shake it hard and they are doing it and they have found their champions. So if this is not done seriously I'm afraid, we might see that the prospect of a 2024 re-election of Donald Trump and it would be the first US president since Grover Cleveland to when non-successive terms, or someone of that ilk, either in the US or in many across parts of Europe and other parts of the world is likely to become something that is common. And in my view, that would be very dangerous for the reasons I said before. We have a system that is flawed, but a system that with all its flaws is far better than any of the alternative we have at the table.

 

Christine Garrington  13:45 

"Golfing with Trump. Social capital, decline, inequality, and the rise of populism in the US" is research by Andres Rodriguez-Pose, Neil Lee and Cornelius Lipp. It's been produced as part of DIAL's project Populism, Inequality and Institutions. You can find out more on the DIAL website at dynamicsofinequality.org. Thanks for listening to this episode of the DIAL podcast, which was presented and produced by me Chris Garrington of Research Podcasts.

 

In Episode 6 of Series 2 of our podcast, we talk with Professor Anette Fasang from Humboldt University and Professor Silke Aisenbrey from Yeshiva University about their research looking at how inequality plays out in the parallel work and lives of black men and women in the United States.

Transcript

Christine Garrington  0:00 

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In this series, we discuss findings from DIAL's Equal Lives project, which looks at how inequality impacts the lives of young adults. Our guests are Anette Fasang and Silke Aisenbrey, they've been looking at the parallel work and family lives of black and white men and women aged 22 to 44 in the United States. I started by asking Anette to explain the background to their work.

Anette Fasang  0:27 

So recently, or for a longer while actually there has been quite a bit of talk about intersectional inequalities, so overlapping categories of inequality, very prominently, gender and race that we also look at in our paper. And here the ideas that black women, for example, face specific disadvantages that white women don't, but that are also different from the challenges that, for example, black men face. And this is a type of our field of research that often works with qualitative data, for example, or is quite theoretical also activism oriented. And that's actually not at all where Silke and I come from, we are more sort of quantitative statistics oriented people do inequality research in this area. But we found this new intersectionality approach extremely important, and tried to get sort of a quantitative what we call life course, perspective on intersectional inequalities. And for us, the life course perspective here is really important. Because when you think about differences between social groups, if you measure them at one point in time, for example, their incomes at age 30, you will, of course, find differences, and you'll find inequality. But what we try to do is follow people really from age 20, to age 40, to see how different types of advantages and disadvantages accumulate, because what accumulates over the life course, tends to be much larger than disparities measured at any specific time point. And we think that's particularly important when you're trying to assess differences between social groups, to not understate the actual extent of disadvantages and advantages that people accumulate over time,

Silke Aisenbrey  2:17

Where we are coming from, it's really to look at at the life of a person in terms of a movie, like understand it really, as this bigger concept and understand every step of the way, as a result of what happened before. Anette and I did like a big project where we did something similar, where we addressed similar questions about the intersection of careers and family careers, so to speak, where we compare Germany and the US. And in that research, we found that there's a lot happening within the US that we actually can't get a grip on. So that was the start off point for this project, where we're like, there's so much race segregation in these life courses happening in the US that we actually want to kind of look deeper into that.

Christine Garrington  3:07

Anette then just take us a little bit more deeply then into what it was you were looking specifically in this paper to get to grips with and why?

Anette Fasang  3:15 

Yes, we used a great data source, the so called National Longitudinal Study of youth for the United States, which has followed individuals for many years, re-interviewing them every year. And here we could for men and women born in the 60s, we could reconstruct their entire life courses from age 20 to 40. So their educational and work careers, when they were in school, when they finish, whether they were unemployed, whether they were on family leave, and which types of jobs they were in, where we could also distinguish was this sort of a low level low paying lower skilled job or a higher level highest high skilled job? So that's how we could reconstruct their careers and for their family lives we also know exactly - were they living with a co-residential partner? When did they have children? Did they separate? Did they re-partner? And so we were able to reconstruct these entire life courses for black and white men and women to assess what kind of advantages and disadvantages accumulate over time for these different social groups.

Silke Aisenbrey  4:24 

We're talking about comparing black individuals to white individuals in this paper, and that, of course, leads to this question - so why is that our focus? There are more groups than that in the US. And for us, it was that we really wanted to clearly focus on the on the white privilege and not kind of on the underprivileged group, and compare those to the group that we had the most data on and that were black women and black men. So we excluded Hispanics and other minorities in this specific research, so that's why you're having the comparison of black and white individuals here.

Anette Fasang  5:00   

What is often done, especially in this quantitative inequality research is that you have one point of reference and that's typically white men. And then you interpret differences of white women, black women, black men, all referring to the white male experience and this in a way normalises it that the intersectionality approach or intersectionality theory criticises and we kind of jump on this paradigm by comparing all four groups visa vie as each other. So we compare black men to black women, to white women, to white men, and so on, and have all these pairwise comparisons to contextualise each group situation much more than only using this one reference point, as is often done.

Christine Garrington  5:44 

You talked about the normalising there Anette - what are the advantages? What makes it better if you like by taking this approach? Perhaps Silke you want to pick up?

Silke Aisenbrey  5:52 

Anette has said this beautifully. And I think your question is exactly on point so that the idea is that it normalises the privilege by not talking about the privilege. So in a way, if you compare every group to white men, the privilege that white male careers inhabits it basically gets unseen. So our commitment here and also the commitment of intersectionality research is really to say like, point out the privilege also describe the privilege and don't only focus on those who are underprivileged. And we were very committed to that approach throughout the paper.

Christine Garrington  6:29 

That’s so interesting. Now, let’s dig right in now and look at the comparison that you made between white and black men, what were the key things to emerge there?

Silke Aisenbrey  6:38 

I think that the one thing that comes over and over is really when we look at the group of white men is really, basically they can have it all in the sense that they can have the high prestige career. And they can combine this high prestige career with any kind of family formation, they can be like single, they can have three kids, they can have one kid. So all of that is possible for white men, whereas for all the other groups, I know you just asked about black men, all of these variations are not open in the same way.

Anette Fasang  7:12 

A core focus of our paper was that we wanted to have these both aspects of the life course - work and family - and also look at the interplay between the two. And the idea here was that if events for example, in the family life strongly constrained economic opportunities. For example, if typically women but also men have children very early, that really limits their career prospects later on, especially if this is single parenthood. So this would be one way how an event in the family life course can constrain opportunities in the work life course. And the other way around, for example, for men, and we see this especially for black men holding a stable job, at least a stable job, even if it's not a high stakes high earning job at at least a stable job is almost a precondition for then forming a stable partnership and having kids. So the two life course domains are interrelated in these many different ways that play out in mutually affecting each other over these entire 40, 20 years, that we observe the life course. And here our idea was is that if the connection between the two life domains work and family is very strong, that means that events in one life domain condition and constrain what is possible in the other life domain. So this is a in a sense, a sign of disadvantage, because there are more limited opportunities economically, but also for different family lives. And if they are unrelated, that means whatever happens in the work and family domain, whatever disadvantages or advantages there are, doesn't spill over into the other life domain. And there's just a wider set of possibilities for how life courses evolve. And indeed, what we found was that this interrelationship between work and family lives, was really, really low for white men. So basically non-existent, as Silke just described, it doesn't mean that everybody gets what they want. Not all white men get get what they want. But for them, everything is possible in the sense that it actually occurs empirically, you have these very many different combinations of work and family lives. And this was quite different for the three other groups. And here we found that the strongest interrelation between work and family lives where they sort of condition and constrain each other was evident for black women.

Christine Garrington  9:43

Yes, on that note, I’m really interested to know because the picture was slightly different, wasn’t it for for black and white women.

Anette Fasang  9:49 

Yes, that is also I think an important point of our paper, that there's a lot of research showing how the for example, family lives of lower educated black and white women are quite different. But we see equally large differences among highly educated black and white women. There's really a lot of evidence that initial economic resources and then economic opportunities along the life course - so education, access to high quality jobs and so on - but also resources in the parental home. Those, those all have really strong effects on family lives. And then there's also evidence showing how events and family lives like becoming a parent has repercussions for careers. So here there's this whole literature on motherhood penalties how mothers make less money than childless women. But overall, the evidence that economic starting conditions are stronger predictors for family lives, is more convincing, and just broader than for the other way around that family events restrict their opportunities and work lives. And so what we argue here is that black men and women's family options will be limited because they, on average, have worse economic starting conditions. And then for women, on the other hand, compared to men, there will be more repercussions of their family lives for their careers, which is also based on previous studies. And so if you take those two together, then of course, white men will have the most options because they are on average in economically privileged situations compared to the other groups on average. And their work events in their work lives, even unemployment have relatively modest effects on their family lives. Whereas when you go to the other end of the extreme here, black women, they're both disadvantaged because they are black and face, on average, lower economic resources that limit their family options. And then because they are women, their family lives have stronger repercussions on their work careers. So that's how the strongest interrelation in this long term interplay between the two life domains plays out according to our data,

Silke Aisenbrey  12:01 

I just want to go back to what I said earlier that one of the like, important things about our research is that we really also want to look at privilege. So I think it's worth kind of just looking at this high prestige group to kind of make that comparison and what you can really see when we look at black women that there is this double under privilege happening, that you can't even find empirically any black women in this high prestige group. So you you do find white women, and there mainly have no kids or have a kid later in life. And you do find some black men who also only have one kid and later in life, but you can't even find black women. And I think that's something that needs to be pointed out and needs to be underlined.

Christine Garrington  12:46 

No that's a really important point to make Silke thank-you. So when you were thinking about the policy intervention implications of all this, then you sort of started to consider what might work best, what was your thinking Silke?

Silke Aisenbrey  12:59 

It's a very complicated question because you you will see that when you look at at the medium prestige group and at the high prestige group that a lot is attached to having children or not having children and for women also, to have partners. And as we know, a lot of work in home still falls on the burden of women. So I think childcare is definitely like a very, very big thing. And especially in the US, where like most childcare for smaller children is private, it is hardly accessible for anyone who is not working in a high prestige career. So I think childcare is really one of the like main things that we need to like look at.

Anette Fasang  13:37 

So another thing that I found really striking was when we looked at these work, family life courses, and which ones are most prevalent for black men, but we found as Silke said, there is a smaller group of black men who have that highest earnings, one or two children, usually late or classic, successful upper middle class life course. But these are only 12% of black men. That means the remaining 88% have low, in our case really low prestige jobs with low earnings. There are no stable middle class careers among black men of these generations that we're looking at. And what I found particularly striking and this is something you can only see in this longitudinal process perspective, that 62% of them have unstable low prestige, low income careers. So that means they are frequently interrupted by periods of unemployment or being out of the labour force entirely. So that means 62% of black men in these cohorts have really precarious careers. And all of them actually have family lives that are either childless or they're single fathers. So these precarious work careers really go along with having sort of non-traditional or at least family careers that don't go along with stable co-residential partnerships. And how this bridges into the policy point is that I think one thing our findings, if you take them all together really support quite strongly is that the lack of initial economic opportunity sets, especially black men and women on a difficult path early on, and really limits their family opportunities. So what is implied and this of course, is if you want to equalise work family life courses among these four intersectional groups, then equalising economic starting conditions would be quite important early in early childhood or in early adulthood. And this is these early interventions are particularly important because then you can break cycles of increasingly cumulatively, increasing advantages or disadvantages like these vicious or virtuous cycles that we know from many different studies tend to play out over time in these life courses.

Silke Aisenbrey  16:00 

I also think that the access to education is just still very, very segregated for different groups in the US. So I think that's also always something that needs to be said.

Anette Fasang  16:09 

What also was interesting about these findings is actually how the large proportion of people who remain in similar career tracks that they entered early on, there is of course, some upward mobility there is also some downward mobility. But we see many people are kind of locked in the same precarious careers over 20 years from age 20 to 40. That never make it out. So I think many things are missed. If you only look at, for example, people’s work situation at age 25. When you take into account how many of them who are in disadvantageous positions actually remained in those for very extended periods of time.

Silke Aisenbrey  16:52 

Parental leave also, of course comes to mind when we think about these full careers. And this is also important because when we talk about cumulative advantages, we see that in the US parental leave is often only accessible if you have careers and medium or high prestige jobs. So if you're once on this career track, the advantages just cumulate between like childcare, and parental leave, all of these things are accessible, much easier to people who are already in privileged positions.

Christine Garrington  17:25 

"Uncovering Social Stratification; Intersectional Inequalities in Work and Family Life Courses by Gender and Race" is research by Anette Fasang and Silke Aisenbrey and is published in the journal Social Forces. You can find out more about the Equal Lives project at www.equal-lives.org and subscribe to the DIAL podcast to access earlier and forthcoming episodes. Thanks for listening to this episode, which was presented and produced by Chris Garrington.

In Episode 5 of Series 2 of our podcast, we talk to Alejandra Rodríguez Sánchez from the University of Berlin and Susan Harkness from the University of Bristol about research from the DIAL funded Equal Lives project on the gendered division of housework during lockdown and whether or not changes that happened were temporary or long-lasting.

Gender division of housework during the COVID-19 pandemic: Temporary shocks or durable change? 

is research published in Demographic Research by Alejandra Rodríguez-Sánchez, Anette Fasang and Susan Harkness.

Transcript

Christine Garrington  0:00

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In this series, we’re discussing findings from DIAL’s Equal Lives Project, which looks at how inequality impacts the lives of young adults. Our guests in today's episode, are Equal Lives’ Principal Investigator Susan Harkness, and Aleja Rodríguez Sánchez. They've been looking at the gender division of housework during the COVID-19 pandemic, to see whether any changes are temporary or longer lasting. I started by asking Susan to explain the backdrop to the research.

Susan Harkness  0:32 

So this research fits into a larger body of research looking at how inequalities evolve over the lifecourse. And so when COVID came along, we realised it revealed that there are really important changes going on and new inequalities and growing inequalities we needed to think about so a part of that we're looking at what is happening within families, and in particular, how households divide their labour because that has implications for what happens in the labour market and what happens to broader inequalities.

Christine Garrington  1:01 

Aleja what exactly was it that you're hoping to get a better handle on, a better understanding of in all of this?

Alejandra Rodríguez Sánchez  1:09

Yeah, we started with the idea that maybe the effects of the pandemic and the lockdown on the division of labour were going to affect some people more than others. We intended to look at what couples would do differently if they had children or didn't have children. We also further wanted to look at whether the age of the child would make a difference in how the pandemic impacted the division of labour. But then we realised that there were a lot of things going on at the same time and it wasn't going to be easy to sort of look at one moment in time and before and after. And so we wanted to give it a more dynamic look and see how the situation evolved over time as these further changes in the furlough scheme, childcare and school closures were put in place and then lifted. 

Christine Garrington  1:55 

Can you talk us through exactly what it was that you that you did?

Alejandra Rodríguez Sánchez  1:58 

We opted for a very, first, very descriptive type of study, looking at the share of housework done by women, and here we look at the percentage or the proportion or the share that it's done by women of the total amount of number of hours spent on housework, cooking, cleaning, but does not include childcare in this case. So we want to know how that share of the work done by women changed. So we wanted to look at this quantity at different moments in the pandemic. We wanted to look at it first shock but then we also wanted to look at what happened after that first shock, whether those same things, the same effects would have stayed over time or were they, whether there would need some sort of change. And for that we use a technique called kernel density estimation, which helps us to see how the distribution of a variable in the population has shifted over time. So we wanted to first estimate pre-pandemic distribution and then we wanted to see how the distribution has shifted over time. Then secondly, we wanted to sort of further those descriptive analysis with a fixed effects type of regression, which basically we tried to compare couples to their own selves in the past to sort of get rid of some of the heterogeneity that it's unobserved. 

Christine Garrington  3:13 

You got your information from an especially conducted COVID survey, what sorts of things were people asked in that that made it possible to look really closely at these questions?

 Alejandra Rodríguez Sánchez  3:23  

Yeah, the COVID survey - it's really like a special very special or very unique study, in a way even for other in comparison to other UK studies that were done during the first year of COVID. The sample is basically a sub sample of this Understanding Society study, which is this much larger study that has followed UK households for more than 10 years. And there were lots of questions on how the COVID pandemic affected sort of the general welfare of households and individuals and there were questions about socio-economic conditions, I think, unemployment stuff, and there were also things about family dynamics. So it's quite comprehensive. And I think there's a lot more to see in there.

Christine Garrington  4:02 

How and why do surveys like this help us gain such important insights into what is going on in people's lives and how that's changing over time?

Susan Harkness  4:11 

Okay, so there's two things that are really valuable about surveys like the UK household Longitudinal Survey, or Understanding Society, as we call it. First of all, it's a survey that's conducted at the household level so we can see what's going on. Not just amongst individuals, but how, how relationships within the household pan out. And then the second thing that's valuable about it of course, is the longitudinal aspect. So that really allows us to look at changes over time. And that allows us to understand much more about why we have inequalities and how they affect different people. So in the case of the COVID studies, we can see where change happened, where they relatively, families where things were relatively equal before became more unequal? Or which particular groups were most affected? So we can see these changes over time. And I suppose if we look at the COVID Understanding Society surveys, and what's also really valuable about this survey is that whilst there have been a lot of other surveys which have given us a sort of snapshot of what's happening at a particular point in time, with the COVID surveys with Understanding Society, we can see how these inequalities are emerging as we move through the pandemic so we can see who is being affected and how that is changing for them over time.

Christine Garrington  5:30 

Yeah, really important and Aleja so let's get down into the nitty gritty then - when you, when you looked over time at how men and women were dividing housework or sharing housework at different times during the pandemic. What did you find?

Alejandra Rodríguez Sánchez  5:44 

Yeah, well, we found a remarkable first data set that is seen as a sort of shift in the distribution towards more equality between couples. So the original pre-pandemic distribution it's quite was quite unequal and therefore sort of skewed looking like more women, we're doing more. So visually, it really looks like a bump around like 65-70%, which means really, women do the majority of this housework. And so the first shock is that the shape of that bump to the left, so to say towards more equality, so it's close to 50/50 but it's not quite there yet. And then after, after that first shock with the data for further and further waves revealed was a gradual, but a clear return to previous levels, that we're seeing pre-pandemic where women started to do again a higher percentage of the total housework over time. And this sort of return to normal was especially clear for couples with children, whereas couples without children, we saw that this higher equality achieve after their lockdown or during the lockdown was more sustained. And these results were also confirmed with the fixed effects regression that I mentioned. So we think that the results basically show us that there were different trends, depending on the lifecourse stage in which the family was.

Christine Garrington  7:07 

Yeah, so it looks to be fairly robust doesn't it? And Susan, is that what you expected to see? Or were you surprised that having children made a difference to whether couples continue to share housework more equally, or revert to their pre-pandemic habits as it were in this, this area?

Susan Harkness  7:23 

Right, well of course, I mean, COVID has been an enormous shock, I think. Especially in the early months where we had people's work was affected, and for those who had children schools were closed. And I think that shock meant that couples changed their behaviour, whether they had children or not. And of course, there was a lot of early optimism that, that those changes would mean a bit more gender equality. But what we've seen is I think that as people have adapted, we've seen the sort of patterns emerge in a way that's quite similar to what happens for example, when children, children are born. And we have this specialisation, where women tend to revert back to taking on more of the roles involved in sort of looking after the house whereas men tend to specialise more in work. So sadly, and I think for those with children, I think we see these greater specialisation - so children are often a trigger for more specialisation within households with, with men doing more paid work and women doing more of the housework. And I think to some extent, what we're finding reflects these, these old patterns that we've seen previously in the data before COVID. So perhaps early optimism was, was not as well placed as it might have been.

Christine Garrington  8:31 

Hmmm I will ask you a bit more about the implications of that in a moment, but Aleja what would you say that we've learned from this piece of research that you've done and I wonder if you have plans to look further at this particular area, this particular aspect of people's lives?

Alejandra Rodríguez Sánchez  8:45 

I think one key message besides what Susan has already said is that before and after comparisons, sort of they can be informative, but they're only showing us like a snapshot of what actually happened. And longitudinal data is really key because for us, we gained a lot of information by actually looking at how things evolved over time, which gives a different take on this, on how, when we claimed, those early claims on how the pandemic would change at all for the better or worse we are definitely looking at working already further on the COVID-19 effects. But this time, we're going to, we're shifting the perspective from the couple to the children in particular to teenagers. We’re interested in understanding what factors may explain some preliminary findings on what was found as the serious deterioration of mental health among teenagers, especially teenage girls. We want to see what factors about their families but particularly about mothers who were also having, were having a hard time during the pandemic may explain what happened to teenagers. And so we're working with Susan and Annette on this.

Christine Garrington  9:52 

Yeah, no really interesting, more really important work to come by the sounds of things. So Susan, just to wrap up really a lot has been said about how COVID-19 has negatively affected the lives of women more than men. Fears have been expressed around the reversal of any sort of pre-pandemic trends towards a greater gender equality. Would you say that this piece of research and, and other work that you're doing tells us anything about that, do you think?

Susan Harkness  10:17 

Well, I think certainly other studies have, have shown that women's mental health has been particularly adversely affected by the pandemic and particularly by the lockdown measures, so we know that some of the responses to the COVID crisis have really negatively affected women more than they have affected men. We’ve also, I think seeing some trends in the labour market where particularly mother's employment is perhaps recovering a bit more slowly than that, that of men to pre-pandemic levels of employment and hours of work. So I think there are some indications that there are implications for gender equality, and that those are not necessarily going to be reversed in the short term. I think the longer-term consequences are much harder to tell of course. You know, what effect this, these, these closures has on women and their careers is, it's something that we don't yet know, but it's, it's not hard to imagine reasons that parents may feel that they're going to fall, fall behind in the labour market because of the extra roles they've had to take on over this crisis. And I suppose the question remains about whether in the longer term, they'll be able to catch up with where they may have been otherwise.

Christine Garrington  11:31 

“Gender Division of Housework Furing the COVID-19 Pandemic: Temporary Shocks or Durable Change” is research by Alejandro Rodriguez Sanchez, Annette Fasang and Susan Harkness and is published in Demographic Research. You can find out more about the Equal Lives project at www.equal-lives.org. Thanks for listening to this episode of our podcast, which is presented and produced by Chris Garrington. Don't forget to subscribe to the DIAL podcast to access earlier and forthcoming episodes.

In Episode 13 of Series 3 of the DIAL Podcast, Professor Nicky LeFeuvre from the University of Lausanne discusses findings from DIAL’s DAISIE project (Dynamics of Accumulated Inequalities for Seniors in Employment, which has been exploring the gendered impacts of policies aimed at extending working life. 

Transcript

Christine Garrington  0:00  

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series three we're discussing emerging findings from DIAL research. For this episode, we're talking to Nicky LeFeuvre from the University of Lausanne about findings from DIAL’s DAISIE project, which has been exploring the gendered impacts of policies aimed at extending working life. I started by asking her to talk about the policy backdrop to the research

Nicky LeFeuvre  0:25  

Over the last 10 or 12 years there has been this quite widespread consensus about the need to extend working lives and this consensus has existed at national levels, you know, government initiatives, also across international organisations like the OECD, and the dominant narrative has been based on kind of two or three basic assumptions this inevitability of increasing full pension age, to keep pace with life expectancy. Questions about the sustainability of our existing welfare systems, pension systems, and also a discourse around personal individual choice and personal responsibility. You know, this idea fielded by the OECD that people are increasingly free to construct their own biographies and so there has been this sort of focus on rewardingly later retirement or penalising early retirement in actual fact, and relatively little concern for the inherent, I would say dynamics of accumulated inequality that lie behind this policy objective. And so this was very much something that we wanted to address in the in the DAISIE project and of course, it was completely in line with the overall aims of the DIAL programme. And our sort of particular focus was to say okay, individuals are receiving this policy discourse which is relatively homogenous across the board, and what are they doing with it? Okay, how is this really impacting on their lives? And notably, how is this being interpreted and acted upon by their employers, by the occupations that they're in? And to what extent their past life experiences, particularly their employment histories, and the way that their past employment has been articulated with their care duties if they happen to be women? How is all this coming together to produce a, what we presume would be quite a varied experience of what extended working life actually means for individuals and for organisations, to be honest.

Christine Garrington  2:28  

Yeah, now that brings me very nicely on to my next question, actually, because in recent years, policymakers have really recognised the need, the importance of taking, you know what we talked about as a life course approach to this issue, something you've just hinted at, and, and this is something that really resonates with your research. Tell us why this is so important.

Nicky LeFeuvre  2:45  

I think there has been it's been slow to come, but it is there, I would say, perhaps emerging recognition that rather than full-fledged recognition at the moment of the need to avoid the accumulation of individual disadvantages over the life course in terms of extended working life and this is related to health issues. You know, we do not age equally, people are not as equally able to envisage extending their working lives and they're also not as equally motivated to do so. So that this recognition has come or is coming slowly. And in the most recent OECD document, for example, which is entitled working better with age, there is this idea that perhaps there has been too, too much of focus on these financial incentives. So making it you know, financially penalising people for leaving the labour market too early with the too being in speech marks and the need to address what is often termed demand side barriers to extended working life. And I really do like this this quote from the OECD that now recognises the fact that we need workers who want to work longer and also employers who want to employ them, and I think this is really the crux of the issue here. You know, there's there is this emerging shift towards the recognition that this is not just about individual choice that these extended work, working life issues are related to a whole host of structural constraints and opportunities. And this is really what we were wanting to do in the DAISIE project. It does really resonate with us because we were arguing that it is important to look beyond macro level policies and to study exactly how they are being interpreted how they're being applied by employers and by individuals according to the you know, particular histories and their particular circumstances. So yes, this this really was very exciting for us, because we did see this policy shift on the horizon, as we were, you know, preparing to to address those issues in the project.

Christine Garrington  4:58  

Yeah, that's great. That's a really neat summary of the backdrop to this work. So let's move on then. And if you could give us an outline an overview of what the DAISIE project has actually been doing?

Nicky LeFeuvre  5:12  

We set out to adopt what we called a multi-level research design, because we wanted to integrate as I just said, the policy background obviously you can't completely abstract this out of your reasoning. So we did want to look at the similarities or the variations in these extended working life policies across countries and see whether there were some best practices or some policy recommendations that were being really adopted across the board and others that were perhaps, you know, more localised in certain contexts or certain countries. So we wanted this macro level analysis of working life practices, but also the objectives that were that were being defined by by different policymakers, either at the EU level or in particular countries. We also wanted to sort of micro socio sort of individual analysis. So we wanted to explore particularly the well-being, the health and the work life balance issues that older workers were facing. So we knew we wanted to use biographical accounts we wanted life history interviews, we wanted really to be able to get at the experiences of older workers, which are kind of slightly invisiblised in the policy documents. And in order to integrate those two levels or those two scales of analysis, we needed the mezzo level which is the sort of intermediate level the occupational and the organisational level, as I said previously, often sort of left out of existing analyses in order to look at what was happening in different employment sectors. And therefore, we adopted this case study method where we selected three different occupations or three different sectors: finance, health and transport. And with our sort of cross-national comparative perspective, we then looked at these three sectors that we could compare both within with other sectors within the same country and across countries to see whether these extended working-like issues were being addressed and implemented to the same extent and in the same ways in different sectors and in different countries.

Christine Garrington  7:20  

Such an ambitious programme of research and also at a very challenging time with everything going on with COVID.

Nicky LeFeuvre  7:27  

Carrying out empirical fieldwork during the COVID pandemic was a little bit challenging for us. But what we've actually done is cross country and cross sector comparative analysis using case studies that we carried out in the five countries and in three different sectors as I said, health sector, health sector, finance and transport. We have collected a huge amounts of empirical data, qualitative data to a large extent. We've used biographical interviews with older workers, male and female workers, and we have about 500 of these interviews across the board. We have of course prepared English language summaries of these interviews because we have to now compare them comparatively and they were not carried out all in the same language. So as you can imagine, this is slightly challenging. And we've also done about 60 expert interviews and we met up in each country and each company we went into we met with the human resource managers, we we talked to line managers, trade union representatives, and so on, to get a feel of how ageing at work was being framed in these different institutions. And we have a collection of about 500 life course grids, which enable us to kind of visualise the life course events that led up to people ageing at work, if you like. So the family events, the residential ability events and of course, their employment histories that frame the ways in which they are now thinking about whether they're going to retire at what age they want to retire, whether they could envisage extending their working lives and under what circumstances. So quite quite a wealth of data. We're starting to get to grips with along with a secondary statistical analysis that we did previous to the to the case studies.

Christine Garrington  9:12  

So what are the sort of the first things, most the things that you did early on Nicky I think was to map older workers employment trends, what were the key things to emerge there?

Nicky LeFeuvre  9:22  

We were really interested in looking at cross national differences here. And of course, we do see and that's not you know, that's unsurprising given given the convergence in the policy measures that I mentioned earlier. We do see a convergence of the employment rates, basically in the 55 to 64 year age group, I would say. So if we look at the data over the past 10 years, the differences between countries have been reduced. We still have about, you know, up to 20% difference in employment rates at 55 to 64. So this is not negligible at all, but the differences across countries are becoming smaller. So there's there's this idea of a kind of norm of extended working life, but remember, I'm talking about 55 to 64 here so what we're really looking at is actually encouraging people to work up to full retirement age and very little actually about encouraging people to work beyond full retirement age. I think that's a you know, quite an important point to remember when we're talking about ageing at work. In actual fact, we're looking at 55 to 64. And that's where you know that the changes have been over recent years. The other important thing to remember is that there has been a slight reduction in the gender gap in retirement timing. Over the same period, women do continue to retire earlier than than their male counterparts in in almost all of the countries we've looked at. And of course, that's why they they are to a certain extent the prime targets of many extended working life policies in recent years. But the the gap in the retirement, the actual retirement age of men and women has been falling. And that's also very interesting because it means that the gender dimension of what it means to age at work becomes particularly important to look at in detail.

Christine Garrington  11:18  

So although as you said, you looked across a number of employment sectors, we're going to be focusing in on the finance sector for our interview today. So my first question is why the finance sector?

Nicky LeFeuvre  11:28 

We were trying to decide which sectors to focus our case studies on. Several criteria were taken into consideration. One of them was of course the gender composition so we wanted sectors that was sort of contrasting in terms of the share of male and female workers. So healthcare was our sort of highly feminised sector transport our highly masculinised and finance our sort of gender balanced sector. Then we wanted sectors where the share of older workers was quite variable. And finance actually is the sector where we have the lowest share of older workers of the three sectors we looked at we have more or less depending on countries there is some variation around 20 to 30% of over 50 year olds in the finance sector, which is let's to give an example half the rates of older workers in employment compared to the transport sector for example. So quite a low share of older workers in finance. And this is obviously related to the history of the of the sector of the occupation. Which is an occupation which has been downsizing and restructuring for the past 20 to 30 years. And where older workers have in most countries been targeted during these restructuring, downsizing operations and have often been offered various early retirement packages, or at least some older workers, mostly male managers, in fact, have been offered packages. And so the finance sector has kind of lopped off a whole generation. And this means that today, it is one of the sectors were that were older workers are relatively underrepresented. But it's a sector that is now facing a number of challenges whether these rather generous early retirement packages have become financially non-viable, and where there's also been some recognition that the accumulated experience of older workers, actually the banks actually needed that experience in order to face the new challenges. And so there is a shift in policy and this was also very interesting for us.

Christine Garrington  13:39  

Okay, let's move on to some numbers then. What were you able to see in terms of the share or the proportions of the numbers of older workers in the finance sector?

Nicky LeFeuvre  13:47  

So, the moment we have a very, very small share of older workers, if I give you just you know, some figures for example, in in the Czech Republic, only 10% of men working in the finance sector are aged over 50 in 2019, but 20% of women in the Czech finance sector are aged over 50. So this is also interesting. It's one of the rare sectors where, proportionally speaking, the share of older women, as compared to the whole female workforce is greater than the share of older men as part of the male workforce. And this is quite a rare configuration in sort of the European labour markets at the moment. So that was also something that we were very interested in exploring further.

Christine Garrington  14:31  

So let's dig now into some of the rather wonderful data that you've been collecting, especially that qualitative data so when you asked workers about their experiences of being older employees in this sector, what were some of those key things that come out of that? Of what they told you?

Nicky LeFeuvre  14:46 

Well, perhaps I can, I can start with a rather eloquent quote from one of our Swiss interviewees, and I mean you have to take this against the backdrop of this very sort of systematic offloading of older workers over the past 30 years from the banking sector, and one of our interviewees said sort of almost in a whisper “ageing is something we just don't talk about in this bank”. And this really I think, translates quite nicely how stigmatised the question of ageing is within the banking sector. We came across a lot of negative stereotypes about older workers. Older workers are systematically presented as lacking skills, being unable to keep up with the pace of organisational and technological change. And to a certain extent, this is of course the banks justifying their past age management policies which were almost entirely based on externalising ageing at work if you like, getting rid of their older workers, before they actually had to deal with ageing at work. And so in a lot of our interviews, ageing was seen as either something that could possibly enable one to leave the finance sector well before reaching retirement age. So you know showing that you were not able to adapt was seen as as a as a good reason to to leave early, or as something that was quite risky in that the bank could therefore consider you to be too old and and not flexible enough to face the challenges of this digital revolution that's going on in in banking, and therefore you could be made redundant because you were not keeping up with the pace of things. So basically, there was this idea that age is something that we don't talk about and older workers are a great pains to prove to their employers and to the themselves and to their colleagues, that they are actually not part of this terrible stigmatised group that one would call older workers.

Christine Garrington  16:56  

So some quite unexpected views expressed there about this whole issue of being an older worker, and what are the implications of that for any sort of age management policies that any business might want to put in place in this sector?

Nicky LeFeuvre  17:10  

Any kind of age management strategies that are adopted in this in this context, are destined to fail basically, because people refuse to be identified with a stigmatised group. That would be the target of you know, these age management policies, and therefore, even when there are minimal measures, I mean, we didn't have a huge range of age management measures that we came across in our case study banks but most of them were related rather to the transition to retirement. So you know, accompanying workers in the transition to retirement, which we consider not really to be age management policies at all because this is you know, this is thinking about how to get rid of your older workers still, rather than thinking about what you do with them when they stay. But even in in those cases, there was a very, very low take up rate because nobody really wanted to run the risk of being identified as an older worker, because this was such a, you know a stigmatised category, and no one wanted to be demoted, or no one wanted to be encouraged to leave because they were part of that group.

Christine Garrington  18:13  

So Nicky, there seems to be a real disjunct - a real mismatch here between the sort of policy top level policy narrative that you outlined earlier and what you're actually hearing on the ground from workers. You know, what, what's your take on all of that? How does this chime with that policy narrative that you were outlining?

Nicky LeFeuvre  18:29  

Yes, so I mean, I think these results do, really do tell us that any serious attempt at extending the duration of our working lives requires the active involvement of employers in the business sector as a whole. It's it's quite incredible I think that we should find such a small share of older workers in a non-manual sector like banking, where the physical limitations to you know working longer in terms of health and well-being should in theory be far more limited than in the health sector or in the transport sector, but actually, we find the opposite. We find that finance, in finance we have a small share of older workers. So this really does confirm that postponing retirement is not only about health, it's not only about financial incentives, and it is very much about how older workers are perceived within particular sectors, how they are treated by their employers, and particular I think in those parts of the job market that are looking to reduce staff costs that are looking to scale down their activities or who are confronted with technological change or organisational restructuring. Then, then we really do have to accompany I think companies in in looking at how they, how they frame the whole issue of, of ageing and working.

Christine Garrington  19:51  

Something I found quite extraordinary in in your research was that when you spoke to companies they expressed, expressed a reluctance or hesitation to introduce any age related policies for fear that this would somehow be seen as discriminatory in some way. What's your take on that?

Nicky LeFeuvre  20:08  

We had a number of examples where HR managers line managers went to great lengths to explain to us that they couldn't offer any positive support to their older workers because this would be seen to be discriminatory towards other groups of workers. And so we were kind of left a little bit speechless at this thinking, but what interpretation of equal opportunity is being developed here? And why is it that companies believe and they do apparently strongly believe that any accommodation of ageing in organisational structures in the way that work is shared  out or the way working time expectations or or shift work organisation - anything that would facilitate the experiences of older workers identified as a group with potentially some needs that are different to those of other age groups. This should not be seen as discrimination. This should be seen as equal opportunity policy, and it shouldn't be seen as coming into conflict, for example, with gender equality policies or with parental support policies or whatever other objectives companies are seeking to meet. So I think, really applying or emphasising the need to think equal opportunities in an intersectional way looking at how gender and age and ethnic origin and disability and so on, interact across the life course and how employers can deal with these in innovative and creative and complex ways. I think this would be really something very useful because we were struck by this, this difficulty that that organisations were facing in thinking through what they could actually do to support their, their older workers.

Christine Garrington  22:05  

You did make a number of quite clear recommendations for employers and policy makers in the work that you've done. Can you just talk us through those?

Nicky LeFeuvre  22:12  

The need for organisations I would say, you know, policymakers at the national level, international level, but also within companies to recognise that there is a potential mismatch. In fact, in the older workers we are talking about as a target group for extended working life policies. Spontaneously when we when we talk to to employers about the kind of older workers that they would be interested in keeping on that they would be interested in training or that they would be interested to target for bridge schemes or for unretirement schemes as they call it and so this possibility of employing retirees back perhaps on a on a reduced rate. Companies do have quite clear, clear image of the kind of worker that they would be interested in in involving in those kinds of schemes. Unfortunately, those images do not equate very well with the profiles of the workers who are actually motivated and interested in extending their working lives. Who tend not to be the most highly qualified or who tend not to be the workers who have continuous employment histories. Who have had haven't had any major health events during their adult life course, who haven't had any significant care commitments that have taken them out of the labour market, who have relatively comfortable financial arrangements made for their latter years and so on and so forth.

Christine Garrington  23:37 

So among the people you spoke to then, who was motivated to extend their working lives and why? 

Nicky LeFeuvre  23:45  

Workers can also be motivated because for example, they have developed their careers quite late on in life. So maybe they are just moving into a management position because they've had, if they're women, they have had some years out of employment for family reasons. We also had a number of very interesting testimonies from older women saying that continuing to work longer was actually very attractive to them, because it was one way of avoiding being swamped by care duties that they could be expected to take charge off in later life. So either you know, being on call for grandchildren or being available for elderly dependent relatives. This idea that continuing to work was actually a way of avoiding being overwhelmed by by these care expectations was something perhaps something we were not expecting to find to such a wide extent. And so quite clearly, women like that who are interested in extending their working lives as long as their working conditions are adapted to their needs are not being identified at the moment as resources that employers could call upon, and people that the employers could have in mind when they think about how they are going to manage age. You know what strategies they're going to put in place and how they're going to start, operationalizing their age management policies before people become old you know before people get to within two or three years of retiring.

Christine Garrington  25:20  

So is there a simple message in all of this?

Nicky LeFeuvre  25:22  

Making it clear that they're the kind of people that employers would spontaneously think about as their target group for extending working lives are not necessarily primarily the people who are interested in extending their working lives, but there are other groups who are highly motivated to work for longer. I think this is you know, one message that we can pull out of the research that could translate into some quite exciting and quite innovative policy decisions on the ground as it were.

Christine Garrington  25:55  

Dynamics of accumulated inequalities for seniors in employment is a DIAL research project, looking at the gendered impacts of policies and an extended working life. You can find out more on the DIAL website at dynamicsofinequality.org. Thanks for listening to this episode of our podcast, which was presented by me, Chris Garrington and edited by Elina Kilpi-Jakonen.

 

In the fourth episode of  our Podcast looking at research from the Equal Lives project, we talk to Michael Grätz from the University of Lausanne and Swedish Institute for Social Research. He discusses research published in Demography involving Equal Lives team members Jani Erola and Aleksi Karhula which looks at siblings to to see whether educational opportunities are equal for all in and across 6 countries.

In Episode 12 of Series 3 of our podcast, Jamie Hentall MacCuish from University College London and the Institute for Fiscal Studies discusses findings from DIAL's TRISP project on the intergenerational elasticity of earnings or why rich parents have rich children. 

The Intergenerational Elasticity of Earnings: Exploring the Mechanisms is a DIAL Working Paper. 

Transcript

Christine Garrington  0:00  

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series three we're discussing emerging findings from DIAL research. For this episode, we're talking to Jamie Hentall MacCuish from University College London and the Institute for Fiscal Studies. He's been investigating why rich parents have rich children. I started by asking him to explain the background to the research.

Jamie Hentall MacCuish  0:26  

If you will permit me I think it's a bit hard to answer that question without very quickly saying what the paper is about. So in it, we decompose the intergenerational elasticity of earnings or the IGE, which is the correlation between parents and children's earnings. And we do this to try and understand what mechanisms transmit privilege from one generation to the next. We were using this dataset - the national cohort data study or NCDS - for another paper with a slightly different focus, and we realised the data set offered a unique window into the mechanisms affecting the IGE. Now the NCDS follows a single cohort of people born in a particular week in 1958. From the moment of their birth, up until now as they approach retirement. And it really is a globally unrivalled resource for social scientists due to its combination of information about family background, parental effort and time investment in their children and children's ability, educational outcomes and later life earnings. Having this information allows us to disentangle the relative importance of family background parental investments in children, further education and ability in explaining the correlation between parents’ and children's earnings. Now, I mean, I've said it's a globally unrivalled data set what really makes it globally unrivalled is how forward looking this policy was in 1958. I mean, other countries have since introduced similar datasets, but much later meaning that now we don't have data that covers really most of the working life of these group of individuals, which really makes it a fascinating window into what explains that intergenerational correlation in earnings or IGE.

Christine Garrington  2:10  

What exactly was it about having wealthy or poor parents that you wanted to  get to grips with specifically in this piece of research?

Jamie Hentall MacCuish  2:19  

Why wealthy parents have wealthy children and vice versa? So the children of rich families tend to differ from the poorer peers in multiple ways. They have fewer siblings and a more and more educated parents, their parents spend more time with them and send them to better quality schools. Their cognitive skills are higher at the end of compulsory education, and they complete more years of total education. All these channels have been found to affect an individual's earnings. But in order to design policies to improve intergenerational mobility, we need to understand the relative importance of these channels and how they interact with each other to generate correlations in lifetime earnings.

Christine Garrington  3:00  

Okay, so what did you actually do then once you know, once you sort of started digging into the data, what did you actually do?

Jamie Hentall MacCuish  3:06  

A multi-level mediation analysis. Basically, that means we work backwards to see how much of the IGE is explained by each mechanism. So that's probably pretty cryptic. But in the first level, that we started at we only allow for direct effects on a child's earnings of the years in education, their cognitive ability, the quality of the school they attended, and the parental investment they received and their family background. So in this first level, for example, we find that education accounts for 43% of the IGE amongst females. However, in the next level, we account for the fact that other channels refer to events earlier in the child's life, than total years of education because really, total years of education is determined by further education decisions. And so other events plausibly impact on the years of education. Once we account for both the direct effects as well as these indirect effects through years of education, the fraction of the IGE explained for females by education collapses to just 2% to continue with the example given earlier, and cognitive abilities at the end of compulsory schooling really explained most of this difference.

Christine Garrington  4:22  

Can you help us unpack that a little bit Jamie? What does that actually imply?

Jamie Hentall MacCuish  4:25  

Once you account for cognitive ability at the end of compulsory schooling, the fact that children of richer parents spend longer in education doesn't account for much of the persistence in earnings between generations. And then we then extend the analysis back to more levels to account for the fact that parental investments and stalling might, like school quality, might impact cognitive ability at 16. And that family background might impact parental investment decisions, or the parents’ choice of school.

Christine Garrington  4:52  

You mentioned a little bit earlier about, you know, the amazing data resource that the NCDS is. Are we able to sort of tease out a little bit more about the sorts of things that people are asked in that study that would help you with, with this research?

Jamie Hentall MacCuish  5:07  

There are multiple things asked and multiple tests. So it's not just survey questions. There were tests; reading tests, math tests administered to these children in schools. They measure their weight at birth, the researchers went into the children's school and ask the teacher their impressions of how interested the mother and father are in the child's education. With, it was asked how many outings the parents took their children on, and these are I mean, we combine all of these measures about parental investments into sort of using a latent factor analysis to tease out a measure of how much the parents invest in their children. And similarly, with the child's ability, we have measures of reading scores, math scores, and then teacher ratings of these children on maths and reading ability. So I mean, it's it's a very, I could go on. It's a very, very rich data set. And it's yeah, it's not just survey data. It's tests administered medical information. Yes, it's really quite detailed.

Christine Garrington  6:11  

You've touched on this a little bit already. But when you looked at the data what were the key differences? Tell us more about the key differences that emerged between the children of wealthier and poorer parents.

Jamie Hentall MacCuish  6:23  

The children of richer families tend to differ in multiple ways from their poorer counterparts: fewer siblings, more educated parents, better parental time investments and school quality investments, higher cognitive skills, and more years of total education. But for us, that was really just the jumping off point to then analyse which of these differences matter most to explain this correlation of earnings between parents and generations from this persistence of inequality from one generation to the next.

Christine Garrington  6:51  

And you took into account obviously a range of other factors as well what factors mattered most in all of this and how did they play out?

Jamie Hentall MacCuish  6:59  

So once we accounted for all the levels of analysis, so the for the effect of a family background and early investment on cognition and years of education, what we found is that family background and investment in early childhood mattered the most, the relative importance being different for men and women. For women, the most important was family background followed by school quality. And for men, parental time investment mattered most followed by family background.

Christine Garrington  7:24  

So this is all very interesting, but I'm wondering now you know what are the important takeaways from the research about this relationship between how well off a parent is and their child's life lifetime income prospects, for example?

Jamie Hentall MacCuish  7:38  

It simply what factors we found mattered most? It seems that to explain the persistence of inequality in earnings across generations, early childhood investments and family background really matter the most. And higher educational choices, for example, aren’t one of the mechanisms generating persistence in inequality in earnings across generations.

Christine Garrington  8:02  

Right, I wonder if there's any more to say there about from a policy perspective, if you like for those committed to want to seek and create a more equitable, a fairer playing field for all children, regardless of their background and how rich their parents are, what sorts of things are most relevant? Are they the things that you've outlined already? Or is there anything more that they can take away from this?

Jamie Hentall MacCuish  8:21  

Obviously, you want to be careful making too many policy suggestions off one piece of research, but that said, I think our research really is in alignment with a large and growing literature that says early childhood investments are one of the best levers available to reduce intergenerational inequality. I think anything the government, our research would say and so I think with a large growing body of research say, that anything government could do to reduce the inequality in investments in early childhood would be one of the most powerful mechanisms to reduce intergenerational inequality.

Christine Garrington  8:56  

The Intergenerational Elasticity of Earnings: Exploring the Mechanisms is a DIAL Working Paper by Uta Bolt, Eric French, Jamie Hentall MacCuish and Cormac O’Dea from the Trends in Inequality: Sources and Policy or TRISP project . You can find out more on the DIAL website at dynamicsofinequality.org. Thanks for listening to this episode of our podcast, which was presented by me, Chris Garrington and edited by Elina Kilpi-Jakonen.

 

 

 

 

In episode 11 of the DIAL podcast, Professor Gabriella Conti from University College London discusses two pieces of research part-funded through DIAL's Growing up Unequal? The Origins, Dynamics and Lifecycle Consequences of Childhood Inequalities project.  The first investigates socio-emotional inequalities in children born in the UK in the 1970s and the Millennium and the second investigates the long term health benefits of the UK Government's high profile Sure Start programme. 

Transcript

Christine Garrington  0:00  

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series three we're discussing emerging findings from DIAL research. For this episode, we're talking to Professor Gabriella Conti from University College London, about two pieces of research. The first compares the behaviour of children born in the 1970s with those born in the millennium, the other looks at the long-term health benefits of the UK government's Sure Start programme.

Gabriella Conti  0:26  

So we know that early human capital is a key determinant of lifecycle outcomes. And by now we also know that if there are early life inequalities that can perpetuate and amplify a person’s life cycle. And so it's really important to document existence of early inequalities if they're present, thinking about what we can do about them. So there was one starting point we ha. Another one was that we know that inequality has been increasing throughout the developed world and in particular in the US and the UK in the recent years. And there is likely less evidence for inequalities in child development. In particular, we were interested in the dimension of child development whose importance is being increasingly recognised which is child social emotional development. And so this is why then we started looking into data and see what we could do to document the evolution of inequalities in the social emotional development of children as early as we could.

Christine Garrington  1:26  

So how did you go about the research tell us what you actually, what you actually did?

Gabriella Conti  1:30  

You know, the documenting evolution inequalities for a long period of time requires that you have data which can be compared across time. And in the UK we're fortunate enough to have British Cohort Studies, which essentially follow the life cycle of cohorts since birth. And in particular, we use the data from two of these cohorts. The British Cohort Study, which has followed the cohort born in one week in 1970. And the Millennium Cohort Study which has followed a cohort born throughout 2000. So these were like, a thirty years apart. And we had pretty big sample sizes more than nine thousand for the 70 Cohort, more than five thousand for the 2000, so called Millennium Cohort. So we were able to extract from these two data sets, relatively similar questions on child behaviour as to the mothers in the two cohorts. At age five so relatively early in life, and mothers were asked questions about whether for example, the child is restless? The child is solitary? Child is screaming or fidgety? And we construct the comparable skill so for two important dimensional social emotional skills, which have been used widely in an interdisciplinary literature on child development, namely, externalising and internalising.

Christine Garrington  2:51  

Can you explain in simple terms, a little bit about what we mean by those types of things?

Gabriella Conti  2:55 

Such emotional skills internalising refer to the child ability to focus their drive and determination and externalising relates to interpersonal skills. So a child with better externalising skills is likely less restless, hyperactive, less antisocial and a child with better internalising skills in less solitary, neurotic and worried. And one important thing that it's good to notice at this point is that while you know the same questions have been asked to the mothers across the two cohorts, and we were super careful and just used the questions which were worded in a similar way of course it could be that what is perceived as a hyperactive child has changed in thirty years. And so we use reasoned methodological advances to take this into account to make sure that we're effectively comparing the same constructs that showing the development of children and this methodology can be used in other settings. And we'll show that it's really important to use as we show in our application.

Christine Garrington  4:01  

Just talk us through then the key things that sort of emerged once you'd gone through all of this, once you'd look so closely at that data, once you'd put those methods in place and once you'd used those really robust approaches.

Gabriella Conti  4:12  

Yeah, so actually, we find that inequalities in social emotional development - this externalising internalising behaviour of these very young children of five years did increase in this 30 years between 1970 and 2000. So this kid we're measured in 1975 and 2005. And it's important to notice that we're not able to say whether one cohort was better or worse than another because we weren't able to compare the levels. Because thanks to our methodology, we were able to compare the difference so the inequality between these two cohorts but no whether one was better or worse than the other. But we saw very clearly that the inequality in the cohort born more recently, so the one born in 2000 was greater than one born in the seventies. So in particular, we see increasingly this early gap between the children with the highest and the lowest social emotional skills. So for example, no matter which measure we used we saw that for example, if you looked at the difference between the 19^th and 13^th percentile, this has widened substantially in 30 years. And this increase was particularly pronounced for boys. For example, for boys, the gap is increased by 19% for externalising skills and even more 30% for internalising skills. So inequality in the social emotional skills so very young children are five years of age was much lower among the children born in the 70s than among those born in the 2000.

Christine Garrington  5:50  

I will ask you what you make of all of that in a moment, but you also took a number of sort of different factors into consideration, didn't you including the mother's level of education, what did you see there? That was important?

Gabriella Conti  6:00  

Yeah, indeed, because as we know there have been several changes in the composition or the population composition or the workforce but also changes in women's experience, especially in the labour market. And so we wanted to look not only what happens in these gaps across the groups but also zooming in on particular groups. And so in particular, we found that even when we compare children or mothers with different characteristics, we found increases inequalities and in particular, while having more educated mothers or mothers with healthier behaviour was an important determinant to the skills in both cohorts. We found that the benefit of having the mother we higher levels of education or a mother in employment was significantly larger for both boys and girls in the most recent cohort than in the cohort born in 1970. So in other words, the difference between the children are more or less educated mother was greater among those born in 2000, as compared to those born in the seventies. And we found this for children’s mothers with respect to mothers education, with respect to mothers employment, but those inequalities increase between children and mothers who smoked and not during pregnancy.

Christine Garrington  7:19  

Okay, so some really interesting findings. I'm interested to know whether you were surprised by what you found? And if so, how you explain what you found?

Gabriella Conti  7:26  

I might sound a bit cynical but I am going to say I wasn't actually surprised about the findings per se, because we do know that there have been many increases inequality across different dimensions. What I found really surprising was the extent of the increase and the fact we could see that so early across such an important measure of development. So we did spend a lot of time in trying to tease out the various determinants of this increase in inequality and as I mentioned before, there being significant societal changes in these thirty years so for example, it's also documented in the paper across the two cohorts. The average age of women have children has increased by approximately three years from 26 to 29. The proportion of women in employment has increased in our data we see from 42% to 62%. And especially the proportion of unmarried mothers is increased dramatically from 5% in the 70 cohort to 36% among mothers in the 2000 cohort. So mothers are having children on one hand at an older age and when they're more engaged in the labour market, which is good for social emotional skills. But on the other hand, mothers are also more likely to be unmarried at birth, which is more stressful, and so it's less good for social emotional development. And we have used the methodology to decompose these factors. And we found the changes in these factors explain about half of the cross cohort increasing inequality when it comes to externalising skills. 

Christine Garrington  9:02  

Okay, so let's consider them the, the implications of these widening inequalities that you're hinting at here and talking about here, especially in the you know, recent context of the COVID-19 pandemic. What would you say overall Gabriella that we learn from this work?

Gabriella Conti  9:17  

So first of all, let me remark that we've seen during the pandemic because there's been increases in inequalities in learning experiences at all level by the children in the home environment. So the children would have been better able to have learning for example, at home or will have had the parents will be better able to cope. They certainly been affected less severely than children in a more disadvantaged situation. And so now it's starting to be documented that in particular, children's social emotional skills have been affected by the pandemic. And on the other hand, as have documented those in other work, support especially for the more disavantaged is also diminished during the pandemic. So for example, done work on the Universal Health Visiting therapist showing that they're in addition to the cuts of course for many years, they've been an unequal in widespread deployment across local authorities. And so the pandemic there has been a double hit on the one hand families that have been unequally affected depending on individual circumstances. On the other hand, also, you know, public services so which are supposed to help families and to help preventing inequalities have been also unequally affected. And so it's really crucial that the government takes stock of this and hopefully, in the upcoming annual review, it provides more support for the earliest and prevent at least the widening of these inequalities.

Christine Garrington  10:47  

Yeah, on this whole idea of the importance of early intervention being key to reducing inequalities. We're really fortunate to be able to talk to you today about another piece of research that you've been doing, and looking at one of the best known really policy innovation interventions in this era, particularly here in England, which is called Sure Start. Now, I think many people are familiar with it, but for those who are not I wonder if you can just talk us through what Sure Start is?

Gabriella Conti  11:11  

Yes, thanks so much for this question. Indeed, with colleagues at the Centre for Fiscal Studies we have been working for a few years now on Sure Start and Sure Start is really a major early education initiative in UK, which was originally area based. And for those who don't know, it has quite a long history. It was indeed first introduced by the Labour government in 1999, so called Sure Start local programmes, and the idea was to give quality services for under fives only in disadvantaged areas then it was so popular and so well accepted by families that the government gave it the major change in 2003 and changing it to Sure Start Children's Centre which were gradually rolled out across England and at the peak they reached more than 3500 of these centres. And what was really nice about the centres was first they provided a physical place for parents to go to bring their children to interact with other parents and it has a wide variety of services which the parents can use. Ranging from early education services, parenting support, childcare, there were health visitors providing the visits there in the Sure Start centre. There were signposts for job search assistance. So think of it really, as a one stop shop for families with children under five. If you had a child and you needed help for health, for other reasons - so you wanted a childcare place, then you could just go to Sure Start centre. And it's also to be said that at its peak in 2010 Sure Start also received a third overall earlier spending as much as £1.8 billion a year. But then unfortunately after 2010 spending has fallen by more than two thirds, many centres have been closed, they've been scaled back or they've been renamed children's centres. Now you don’t even hear Sure Start  or they have been integrated into family hubs.

Christine Garrington  13:10  

Yeah, so big changes over, over the piece there and your research on Sure Start has looked quite specifically at its effects on children's health which is, you know, really important and you started by looking at hospitalizations and links with that. What did you, What did you find there?

Gabriella Conti  13:26 

So we have a data set which contains the exact address and opening date of each Sure Start both local programs and children's centres so we were able to look at the origin of the programme and its expansion up to 2010. And then in England, we have a very good dataset called Hospital Episode Statistics where there is collected data on the universal patients using English public hospitals. So this is important because we can really have a very comprehensive look at the effects across all Sure Start centres for all England the local authority so it wasn't like a selected or a small sample. It was quite good administrative data. And so what we did - we essentially will be focused on the expansion period of Sure Start so as I say, 1999 up to 2010. So where there were all these centres opening up. And then we're looking at what happened essentially when you have access to Sure Start since they're in your area. And what we find, that we find very interesting effects which changed across the life cycle of the child. So first of all, greater access to Sure Start in your area initially increases hospitalization at age one and this shouldn't be really surprising, given that it's common in other studies as well and my reflect the fact that the programme would help referring the parents to proper health care in the case of childhood illness, but also brings their exposure to infectious illnesses from other kids being all in the same setting. However, what is really remarkable is that these early increases are more than outweighed by longer term effects. So as we look throughout childhood adolescence, we find that there is a reduction in hospitalizations.

Christine Garrington  15:18  

And there were even longer term benefits for these children as they got older weren't, weren't there? Talk us through, talk us through what those benefits were.

Gabriella Conti  15:25  

So we found is that exposure to an additional centre per 1,000 children at ages 0-4 average around 7% of hospital admissions at each file. Which goes up to 8% by the end of primary school, so age 11 and 8.5% by age 15, which is the final age of this study. Now this represents approximately 2800 fewer earlier hospitalizations at age five and over 13,000 hospitalizations prevented of 11 to 15 year olds each year. So that's quite a substantial number. It's pretty much an 8% reduction on the pre-Sure Start hospitalizations rate and this is all completely looking essentially at the peak level of Sure Start provision where there was one centre per 1000 children available throughout England. And what is really interesting, while Sure Start was for children under fives, we're able to detect impacts which are increasing over time and are able to detect them essentially 10 years after the children have aged out of eligibility. And if we look at the drivers of these reductions hospitalizations, we see that it's important conditions such as external causes, so things like injuries and also mental health related admissions in addition to infectious illnesses.

Christine Garrington  17:00  

Those are just really striking findings Gabriella and I know that you also tried to get a feel for the potential cost savings that Sure Start would have generated. What were you, what were you able to say about that?

Gabriella Conti  17:11  

Yeah, I think it's quite important is this not only to provide evidence so that a programme is effective, but that it also provides enough bang for the buck. And with Sure Start it is particularly important given as I said before all the money, which was spent at the peak of the expansion. So what we did in this case, essentially, we had on the one hand, the money that the government had provided, and so we computed in this way a cost per child which is really more like the amount of money that the government spent on Sure Start per child, and we computed this amount to be approximately £415 per eligible child which is lower by the way than the cost of other programmes. And then what we did we looked at our estimates, and we considered first of all, we costed only the results, which for which we found significant impact. So as I said, subset of external conditions in particular injuries and also poisoning, then infections. So respiratory, parasitic and then mental health as you can imagine, you know, those have huge cost. And we considered three different types of costs. So on the one hand, the reduction in hospitalization has a direct cost saving in terms of the healthcare sector, so you will have less money essentially spent because fewer kids are going to be in the hospital. And this is more like a short-term cost, the cost at the time at which we estimate the impacts. Then there are assorted indirect costs, so if parents don't have to spend time taking care of the sick child, they are not going to be absent for work. So it's all savings in terms of averted the loss of productivity, and also in case the parents need, for example, to buy additional drugs. And on the other hand, we also included the long-term cost. So, for example, injuries experienced by a child can have a serious long-term consequence. Mental health conditions, especially experience in adolescence, which is the time at which you will find that Sure Start significant to reduce hospitalizations also have very costly long-term consequences. And so when we add up all this benefits together - all this averted cost, we come up with number which is around £330 million. Now of these, approximately a little bit over 10% like £3.9 million is attributed to the direct cost saving to the NHS and the rest is from the longer-term averted cost. And given that we've computed the cohort, this is going to be a total cost of a little bit over £1 billion then these represent approximately a third of the spending on the programme. So taken together, the savings from reduced hospitalization offset around 31% of spending on the programme. And importantly, this is only considering health benefits. Our calculations haven't included yet any potential benefits in other domains such as for example education, social care or crime.

Christine Garrington  20:34  

Goodness me so just looking at health benefits alone some, some really important good things that would change and, and help children grow up to live better, healthier, happier lives, but also an incredibly cost-effective programme. One which really doesn't sort of exist in the same way anymore. So what are the key takeaways for policymakers here would you say? 

Gabriella Conti  20:56  

Yeah, unfortunately it's not been good in my opinion, that Sure Start has been dismantled so quickly. So first of all, I think a key takeaway. So one key message for policymaker and not that this is a hard one to deliver. Because there are policy cycles and usually policymakers work based on these policy cycles but good programmes might take time to deliver their benefits, but it's crucial that when a policy is decided, it has to be looked at the evidence and also it has to consider the long term benefits not only the upfront cost. Another important lesson I think, is that what probably made Sure Start so successful. Well, there are different components. I think one key component is to have everything in one place and to make it easier for the parents to access it. So having this suite of possible interventions and providing a place for parents to congregate and have access to resources. I do believe it's key and it's also the case that if you provide a variety of services, they are you know, their combined effects is not only the sum of the different ones, there are interactions and there are synergies. Among them. So now, you know unfortunately, Sure Start does not exist anymore. So there is this family hubs which are being shaped up and at least my hope is given that Sure Start no longer exists all these lessons will be considered into the shaping on the family hubs. And a particular part in this regard, there is a lot of talking about proportion at universities. Now one key finding that we have is that all the benefits that we find, for Sure Start are concentrated in the poorer neighbourhoods. So we don't find the particular benefit in the richer ones. And so this is important why? Because on one hand Sure Start did help to reduce inequalities but also because going forward an important lesson for the new services such as family hubs is that the model combining universal services with a narrow base focus of disadvantaged neighbourhoods can be a successful approach to earliest interventions.

Christine Garrington  23:10  

Inequality of socio-emotional skills: a cross-cohorts comparison and The health effects of Sure Start are research part funded by DIAL’s Growing-up Unequal? The Origins, Dynamics and Lifecycle Consequences of Childhood Inequalities (GUODLCCI). More information is available on the DIAL website. Thanks for listening to this episode of our podcast, which was presented by me, Chris Garrington and edited by Elina Kilpi-Jakonen.

 

In episode 10 of Series 3 of the DIAL Podcast, Professor Steffen Schindler from the University of Bamberg discusses findings from DIAL's LIFETRACK project which is looking at how different education pathways impact the type of job young people go on to secure. 

Further information

• Educational differentiation in secondary education and labour-market outcomes

Transcript 

Christine Garrington  0:00

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In series three of the podcast we're discussing emerging findings from DIAL research. For this episode I caught up with Professor Steffen Schindler from the University of Bamberg, at DIAL's final conference to talk about the LIFETRACK project, which has been looking at how the type of Secondary Education experienced by young people in seven different countries affects the type of job they go on to do.

Steffen Schindler  0:28

This is the period when education systems start to sort their pupils or students into different paths, different tracks, different streams. And we were interested in how much the sorting that takes place in secondary education already predicts inequality in later life outcomes when the students are in the labour market when they're grown up.

Christine Garrington  0:53

Although you were looking at a number of different countries, you weren't looking to compare across them but within them, weren't you? So tell us about the thinking behind that.

Steffen Schindler  1:01

There's already some research out and we know that countries that are considered as having comprehensive education systems such as the UK for example. They tend to have lower levels of education inequalities than countries that track their students such as Germany for example, that have different schools where they go to. The new thing that we wanted to look at in our project was even though the level of inequality might be different between countries, we were interested does the differentiation in secondary education within a country still predict inequality in that country - is it important for the formation of inequality? So in the end, we have some sort of idea whether it contributes a lot or not so much to inequality.

Christine Garrington  1:50

So working across seven countries must have posed some challenges - how did you go about organising all of that?

Steffen Schindler  1:57

Yeah well we had a very structured approach. So we had project meetings two times a year, and where we made a plan what we wanted to achieve till the next meeting. So basically, we started off with making a plan how we measure certain things such as social origin, or the labour market outcomes such as income or social class and we want to observe when people are grown up or in their 30s or 40s even So that we standardised across all the teams and then we made a plan for what we want to analyse. And we were very standardised in the beginning and the more the project was progressing the less standardised we were - the more freedom we gave to the project teams for their analysis.

Christine Garrington  2:44

Yeah, that makes sense. So at first look all of the research teams in the countries that you were looking at, identify this differentiation between academic and vocational routes. Can you talk us through, through that?

Steffen Schindler  2:58

Basically, each education system has this distinction between academic tracks or streams that eventually lead into higher education on the one hand, and more vocational tracks that don't lead into higher education. But the systems differ, how that looks like. So we have separate schools, for example, in Germany and Germany starts very early with that separation. We have separate schools in other countries such as Finland, for example, in Denmark, were the separations a bit later. Then we have England, which is a comprehensive system, but we also have some sort of academic stream, which is defined by taking a certain number of A Levels at the end. So the systems differ a bit - what the academic stream actually is, but each of them has one academic stream. And it turned out in our analysis that it's always the separation between the academics and the non-academic stream, and that students that on academic stream always end up with better labour market outcomes in the end.

Christine Garrington  4:08

Yeah, let's talk about that a little bit. So when it came to those labour market outcomes for the young people concerned, what was the main implications of the differences?

Steffen Schindler  4:18

Well, first of all, the people from the academic streams end up let’s say higher social classes with a better higher income, a better paid job with a more prestigious job in the end. So this is one result, which was pretty obvious. But another implication is that it's also related to social inequality or social reproduction. Because if we consider who enters those academic tracks and who doesn't, and then this is again, a question which is related to social origin. So the selection into the tracks is heavily based on social origin in all of the countries.

Christine Garrington  4:56

And I'm interested to know if there were any advantages to being on the vocational path compared with being on the academic path.

Steffen Schindler  5:03

I think the distinction is not so much between the academic and the vocational path but between being in upper secondary education or completing upper secondary education. So we have many countries which have an upper secondary stream, which is a vocational stream. And if we compare those students to students who haven't been in upper secondary education, they might even have done vocational training, but the distinction is between upper secondary vocational training and lower secondary careers. And there we see advantages where people in the vocational stream in upper secondary education, indeed have labour market advantages.

Christine Garrington  5:45

So some of the studies also look back over people's life courses to their social backgrounds. That's really interesting. What were the key things to emerge around that?

Steffen Schindler  5:53

What we saw in all of the countries is that differentiation in secondary education is a mediator of social reproduction, as we call it. That means that on the one hand, the selection into the academic secondary tracks is highly based on social backgrounds, family background. So this is the one part and the other part as I already said, since academic tracks lead into the better labour market outcomes, and this produces social inequality in the end.

Christine Garrington  6:25

Yeah, indeed. And it really is a fascinating and important body of work that's been carried out. What would you like those who are interested in reducing social inequalities to take away from all of this?

Steffen Schindler  6:38

I guess the core message of our project is that we have to look at differentiation in a broader sense. So usually, we were distinguishing educational systems based on very formal criteria, whether it's a formally comprehensive system, or whether it's a track school system. But what we've seen is that even in comprehensive systems there is some sort of internal differentiation, such as ability grouping, or other things that we call the hidden differentiation. That's not very obvious. So another example would be the distinction between private education or state funded schools which is another dimension of differentiation. And I guess the core message would be to look at more carefully, those more hidden things, the more hidden differentiation in school systems

Christine Garrington  7:32

Yeah and where do things need to go from here then? So more work to be done as always, presumably?

Steffen Schindler  7:37

Yes, it is always more work. Our project was heavily based on longitudinal data where we could observe students from the day the entered the school system into adulthood and this is quite complex data. And what we saw is that when we are interested in those hidden forms of differentiation, we need better measures. So I think if we want to follow up on this path, we should think about how we could incorporate those measures in in those data so that would be a message also evolving from our projects that is more directed to our research.

Christine Garrington  8:15

Educational differentiation in secondary education and labour-market outcomes is a special issue of Longitudinal and Life Course Studies by Steffen Schindler at the LIFETRACK project team. Thanks for listening to this episode of the podcast, which is presented and produced by me, Chris Garrington and edited by Elina Kilpi-Jakonen.

 

 

In Episode 9 of Series 3 of the DIAL Podcast, Professor Andrew King and Matt Hall from DIAL's CILIA-LGBTQI+ research programme discuss their work exploring how Agent Based Modelling (ABM) can contribute to the study of LGBTQ lives, and conversely, how theory and insights from LGBTQ studies can inform the practice of ABM.

Further links

• Queer(y)ing Agent-Based Modelling: An example from LGBTQ workplace studies is a DIAL Working Paper

Transcript

In Episode 9 of Series 3 of the DIAL Podcast, Professor Andrew King and Matt Hall from DIAL's CILIA-LGBTQI+ research programme discuss their work exploring how Agent Based Modelling (ABM) can contribute to the study of LGBTQ lives, and conversely, how theory and insights from LGBTQ studies can inform the practice of ABM. 

Queer(y)ing Agent-Based Modelling: An example from LGBTQ workplace studies is a DIAL Working Paper

Christine Garrington  0:00  

Welcome to DIAL a podcast where we tune into evidence on inequality over the life course. In series three of the podcast, we’re discuss emerging findings from DIAL research. For this episode, I'm joined by Professor Andrew King and research fellow Matt Hall from the University of Surrey, to discuss new research, exploring how Agent Based Modelling (ABM) can contribute to the study of LGBTQ lives, and conversely how theory and insights from LGBTQ studies can inform the practice of ABM. Before Matt walked us through what they did, I asked them both to explain the backdrop to the research. 

Andrew King  0:35  

When we were putting the project together in the first place, I'd become aware of the potential of Agent Based Modelling to explore ideas and theories and policies, especially on topics with populations where there were quite different data sets available which could be combined and synthesised. And in the case of LGBTQ people. There are quite a lot of smaller qualitative studies using interviews and focus groups and other qualitative data. And then there are some surveys with quantitative data. There are also areas where data is very limited and missing, particularly in relation to bisexual, trans and queer people. Hence, Agent Based Modelling really offered the CILIA project a new way of addressing these issues and trying something quite different, and quite novel, but there is much more to it than that, as Matt will go on to explain. 

Matt Hall  1:43  

Yeah we're also keen to address what's previously been termed methodological binarism within the field. So as Andy's just mentioned, there are numerous smaller qualitative studies and some larger quantitative data sets available, but there's very little conversation going on between the two of them. So each of these types of study tends to form its own stream, and then with its own limitations, and we identify this as a particular barrier for forwarding intersectional insights within policy domains and responding to how unique inequalities can emerge at the intersections of different social identities. So, where the quantitative research isn't engaging enough with intersectionality, or smaller sub populations within LGBTQ qualitative research is then limited in its ability to demonstrate the wider implications or significance of the details that it focuses on. So, it needs to be able to demonstrate the cumulative impact of those details like intersectional experiences. And although it's complete misreading of intersectionality theory, there's this tendency for conversations about intersexual inequality, particularly in public and policy spheres, is to treat inequalities as simply additive to where experiences of inequality of just the sum of those afforded by each of the persons identities.

Christine Garrington  3:10  

Yeah, that's really interesting now you propose something that you describe in the paper as a double querying approach which clearly has a bit of a double meaning but I wonder if you can just explain to us what exactly you mean there?

Matt Hall  3:23  

Well, although this paper was mainly written with LGBTQ scholars in mind as our audience were really keen to not just make this a paper encouraging the uptake of Agent Based Modelling within the field. We wanted just as much to explore what insights the rich theoretical traditions of LGBTQ scholarship can bring to ABM as a developing methodology. So many of the normative methodological practices and judgments surrounding Agent Based Modelling are shaped by the academic fields that most frequently use it like artificial intelligence research, ecology and epidemiology, and we wanted to clearly present ABM as more of a tool that's flexible for the needs of different disciplines. So kind of demystifying it for many of its more quantitative oriented applications. And in doing this, we were particularly interested in exploring its compatibility with intersectional and queer perspectives, which are currently quite dominant paradigms within LGBTQ research. So although the paper introduces our own LGBTQ workplace model, and briefly summarises some of the results we found interesting. It is intended much more as a methodological paper, demonstrating what Agent Based Modelling can bring to LGBTQ research, and in turn, some of the challenges we had to negotiate in integrating it with intersectional and queer insight. 

Andrew King  4:47

Yes, we were very much wanting to speak to too often quite distinct audiences with this paper, and try to create space for thinking and dialogue, and we hope that this podcast will help with that sort of knowledge sharing and provoke new dialogue and engagement.

Christine Garrington  5:09  

So Matt, you're going to walk us through the detail of the research and then we'll get some final reflections from Andrew. So can we talk a bit more about what all this looks like in day-to-day life you use the example of career progression in the workplace. What was it here that you actually examined?

Matt Hall  5:23  

So, as well as intersectionality, the wider CILIA project is particularly focused on life course inequality. And to us, this means exploring how inequality emerges at different key stages in the life course and how these then intersect. So for example, someone may enter the workforce with a good education and strong mobility, and then face x amount of discrimination within their workplace. So we could then simply look at their final career outcome as a product of their ability and exposure to discrimination over time. But people's careers, just like the rest of their lives don't really fold out like that in such a linear way. There are key stages where being exposed to discrimination may have a larger impact than other stages, like when seeking a promotion or when aligned with other non-work-related experiences in someone's life, such as undergoing a gender transition, experiences of racial discrimination or in the case of bisexual employees, even the gender dynamics of their current relationships. Similarly, employees have a bounded agency in how they respond to and protect themselves from experiences of discrimination at work. Those able to move to less discriminatory workplaces. Some may be able to create straight or cisgender aliases for themselves, while others. Others try to avoid situations where gender or sexuality are discussed at all, and others still may even feel empowered to make themselves visible, and even instigate change within their workplaces. And then each of these strategies that someone chooses has its own consequences for that individual, but also cumulatively on their workplace environment. Of these options presented to LGBTQ people are also often contingent on the alignment of many of those other workplace and life course experiences that we've just spoken about. So rather than just a simple model predicting someone's final career outcome based on their assets and demographics. We wanted to explicitly model career progression as this process. Specifically, complex linear process involving interactions between people and their workplaces, various degrees of autonomy and outcomes that are somewhat path dependent. We also wanted to explore the extent to adding complexity, particularly intersectional would impact overall outcomes, in essence, demonstrating how small qualitative details, often omitted from simpler linear models can have significant affect in terms of quantifiable outcomes.

Christine Garrington  8:04 

So imagine this was no straightforward process how exactly did you go about it?

Matt Hall  8:10  

So because of conceptualising career progress as a complex and interactive process using simulation methodology, in this case Agent Based Modelling just made complete, complete sense to us. However, we did still need to significantly simplify, how we represented career progression in the model. So in order to keep the model simple enough to explore and to understand the causal mechanisms behind any interesting emergent behaviours, we ended up representing three idealised stages in an individual's career – so school to work transition, a mid-career transition, and then a transition into retirement. And each LGBTQ citizen in the model, so our agents, were all distributed an LGBTQ status, so whether they were lesbian, gay, bisexual, male, trans, female, etc, and an ethnicity and social class, and then also with other characteristics like ability and access to social capital being proportionately distributed according to these identities and based on existing survey data. Then during each time step in the simulation, or every year, each agent has a probability of entering one of these career transitions based on their age. And the success of each of these transitions are based on a number of factors such as their ability for success of their last transition experiences of discrimination, and in some scenarios, we also included social capital, and individual's identity management practices as additional factors, and we were then able to explore the cumulative impact of these career transitions on overall career outcomes for individual agents, across the whole population of agents, for particular identity groups, and across the different intersections of those identity groups as well.

Christine Garrington  10:00

And what did you see from the different scenarios that you modelled?

Matt Hall  10:04  

Firstly, when exploring the impact of the different model scenarios on workplaces, and their discriminatory practices, we found that increasing complexity and the agency of LGBTQ workers to for example move workplaces if unhappy, and manage their identity in different ways, didn't have that much impact on reducing the discriminatory practices of the average workplace. This tended to be fairly low and stable over all the model runs, it did significantly impact the discriminatory practices of most discriminatory workplaces. Although interestingly, this didn't necessarily correspond with improved career equality for the agents themselves, in fact it tended to be the simplest scenarios that saw the largest improvements to LGBTQ career equality over time. With career equality here being the correlation between each individual's ability, and their career outcome.

Christine Garrington  10:58 

Okay and there were differences within the group that you were looking at also. What did you see that seemed important there?

Matt Hall  11:03  

Yeah, so, generally, we saw that the more complex, or the more detailed the theory that we implemented the more career inequality we observed between different LGBTQ strands. So, in the simplest scenarios where all agents experienced different levels of discrimination during their career transitions, based on LGBTQ ethnic and class status. In these, the different identity groups would end up with different career outcomes, but based purely on these initial levels of discrimination. The actual trajectories would be more or less the same between them. So career equality steadily increasing over time for everyone, and at a similar rate. However, over the different scenarios, as we incrementally increased complexity in the career progression process like adding in social capital as a factor mediating people's capacity to move to better workplaces, and their identity management practices and intersectional variations, we began to see different trajectories emerging through equality between each of the different LGBTQ strands and between the intersections, within each of those strands.

Christine Garrington  12:13 

And other factors such as someone's background or ethnicity, they were also important weren’t they?

Matt Hall  12:18

Yeah, so for example, in the most complex scenarios, whilst career equalities steadily increased over time for the overall agent population, when we then aggregate down - desegregate down to the non-white working class trans and queer agents we observed the complete opposite trajectory happening. So a fairly dramatic reduction in this case in career equality, over time, and this highlighted to us firstly how just fairly small intersectional differences in the career progression process cumulative - can accumulate significantly over the life course in somewhat less predictable ways than linear models would usually predict. So, a minor reduction in an individual's behavioural opportunities like moving to a better workplace or feeling confident enough to disclose their sexual or gender identity in the workplace can set the same individual on completely different trajectories in terms of career outcome over time. And secondly, it highlights the importance of aggregating down to much smaller intersections of population in our models, something that traditional quantitative methods struggle with due to losing statistical significance when aggregating down to smaller samples. And it's been an ongoing problem for research on LGBTQ populations in general, let alone when we start introducing intersections with other identities like ethnicity, and social class.

Christine Garrington  13:46  

Such a really important and major piece of work from you both. I wonder what you take away from this and how it can inform policymakers and employers who are interested in reducing inequalities for LGBTQ workers.

Matt Hall  14:00 

in terms of informing policymakers, our model hopefully demonstrates the importance of considering the impact of intersectional experiences on career inequality. So currently, both wider equality legislation across Europe and more localised workplace policies, tend to be single issue in their approach to social inequalities. For example, they'll have one policy for addressing LGBTQ issues, one for gender, and another for race, disability, etc. And because of this they very rarely address some of the more complex experiences occurring at the intersection of these identities, there seems to be this underlying assumption, that simply addressing the concerns of each of an identity category separately will automatically meliorate all of the problems emerging at the intersections of them. And as we mentioned earlier, this comes from assuming that inequality is additive or a simple sum of each experience of inequality, whereas what we've hopefully demonstrated with our model is that inequality synergized in much more complex ways than this, and that we need to encourage more intersectionally aware policymaking. For example, this may be race policies that acknowledge that many ethnic minority individuals are also gay, lesbian, bisexual, trans, and likewise LGBTQ policies that explicitly address how some LGBTQ employees will also be from ethnic minority backgrounds, different social class backgrounds, and have different abilities and neuro diversities for example, and that a one size fits all approach to LGBTQ equality, may not even begin to start addressing those individual needs at all.

Andrew King  15:38  

Yeah, we don't really see what we've done is purely a thought experiment or all about advancing theory and methodology although those things are important in the way we've described. We think that what we're doing can help to shape policy. And what we're aiming to do a little later in the project is to really engage, policymakers, and employers in these conversations.

Christine Garrington  16:07 

Queer(y)ing Agent-Based Modelling: An example from LGBTQ workplace studies is a DIAL Working Paper by Matt Hall and colleagues. It's part of DIAL’s CILIA-LGBTQI+ project, which is providing cross cultural evidence for the first time ever on life course inequalities experienced by LGBTQI+ people. Thanks for listening to this episode of our podcast which is presented and produced by Chris Garrington and edited by Elina Kilpi-Jakonen.

 

In Episode 8 of Series 3 of the DIAL Podcast, Katri Räikkönen from Helsinki University and a member of DIAL’s PremLife project, talks about her research investigating whether the babies of mothers who whilst pregnant are prescribed steroid drugs, because of concerns around premature births, are more likely to develop behavioural and mental disorders later on.

Associations Between Maternal Antenatal Corticosteroid Treatment and Mental and Behavioural Disorders in Children is research published in the Journal of the American Medical Association. 

In Episode 7 of Series 3 of the DIAL Podcast, Rita Pereira from the Erasmus University in Rotterdam and a member of DIAL’s Gene Environment Interplay in the Generation of Health and Education Inequalities(GEIGHEI) project, talks about her research looking at the links between mothers' smoking and their baby's birthweight.

The Interplay between Maternal Smoking and Genes in Offspring Birth Weight is a DIAL Working Paper by Rita Dias Pereira, Cornelius Rietveld and Hans van Kippersluis.

Transcript

In Episode 7 of Series 3 of the DIAL Podcast, Rita Pereira from the Erasmus University in Rotterdam and a member of DIAL’s Gene Environment Interplay in the Generation of Health and Education Inequalities(GEIGHEI) project, talks about her research looking at the links between mothers’ smoking and their baby’s birthweight.

The Interplay between Maternal Smoking and Genes in Offspring Birth Weight is a DIAL Working Paper by Rita Dias Pereira, Cornelius Rietveld and Hans van Kippersluis.

Christine Garrington  0:00  

Welcome to DIAL a podcast where we tune in to evidence on inequality over the life course. In this series, we discuss emerging findings from DIAL research. Our guest today is Rita Pereira from Erasmus University in Rotterdam, she has been looking at the relationships between genes, smoking and birth weight. I started by asking her about the background to the research.

Rita Pereira  0:22  

So this research has been funded by NORFACE grant. And this grant had the idea of studying gene and environment, and particularly how they interact to generate health and education inequalities. So in other words, what this means is, we already know that both genes and environment matter for generating inequalities. But our question was whether there are particularly harmful or beneficial combinations of genes and environments, in determining inequalities. In this setting, we know that maternal smoking during pregnancy is harmful for the baby. And it is reflected in a low birth weight. And we also know that your genetic constituency will determine partially how heavy or light you're going to be born. So the question here is whether there are combinations that are particularly harmful for you.

Christine Garrington  1:26  

Okay, so what was it about mothers who smoke that you specifically wanted to look at and why?

Rita Pereira  1:32  

So we wanted to know whether smoking was particularly harmful for babies, depending on their children. So other possibility was also that some genetic variants protect you against smoking? Right? So in the end, the was not so much about the mothers who smoke, we know that smoking has detrimental effects for the baby. But we wanted to know if the risk of smoking would differ depending on the genes of the offspring.

Christine Garrington  2:01

Right. Okay, so your information came from two great data sources, I wonder if you can tell us something about them? You know, the detail how many people were involved? How those datasets work? and What people are asked that was relevant to your research?

Rita Pereira  2:14  

Our main data set was a data set called ALSPAC, ALSPAC, which is from the UK, and it's a incredible data set is very detailed. And it followed pregnant women and their children that were born in the 90s, in area of risk though. And it's great for us because it has genetic information, both on the mother, on the baby. And it also has biomarkers so there are urine samples, blood samples that were collected from the mother, when they were pregnant. And it has 5000 to mother baby pairs, that are, that have genetic information on both the mother and the baby. And then we wanted to replicate our findings. And for that we use the UK Biobank. So as the name indicates, is also a dataset from the UK, and is a huge data set. So it has 500,000 individuals that are genotyped. But for our study, it has less variables that are relevant. So for example, we don't have maternal genetic information, and we don't have biomarkers during pregnancy.

Christine Garrington  3:28  

So in order to get a clearer picture you needed to get around this issue of simply comparing mothers who smoke with mothers who don't, so what did you do there?

Rita Pereira  3:37 

So endogeneity is a problem that arises if you just compare mothers who smoke with mothers who don't smoke. And the problem is that smoking is likely to be a result of other variables such as stress, social class, education, maybe personality traits. So if you just compare mothers who smoke with mothers who don't smoke, you might attribute a low birth rate to smoke while in reality, there are other factors driving the low birth weight. So our first step was to solve this issue. And to be able to solve this issue, we instrumented the decision to smoke. So an instrument is a variable that causes smoking, but doesn't cause anything else.

Christine Garrington  4:23  

And how did you do that in your research?

Rita Pereira  4:25

Our instrument was a single snip. So a single snip is a single genetic variant that causes an increase in cigarette smoke a day. In this snip is a is located in a nicotine receptor snip, so people think that it might have to do with how people get addicted and how their body simulates nicotine. We use this snip and we also show that it only correlates with birth weight on mothers who smoke so indicating that there is no effect from this snip on birth rates in mothers who don’t smoke, which is what we want. And we also find that it doesn't really correlate with other variables that are correlated with smoking. Such as age at delivery, whether they're married or single, the social class, education. So it seems that they've having snip is somehow random. And then this snip increases the frequency of smoking. So we use that to do with endogeneity.

Christine Garrington  5:18  

So that was the first issue you dealt with, that you need to overcome. You also needed to deal with this whole question of under reporting, didn't you? This question of people not necessarily giving the full picture or telling the full story because they feel they might be judged in some way, especially about something like smoking.

Rita Pereira  5:35

So usually mothers are not very comfortable reporting that they smoked during pregnancy, because it's somehow taboo, or they don't feel comfortable or they feel may be judged. So we were worried that the reporting they're reporting to smoke was incorrect. So this is where ALSPAC is a really great data set, because they collected urine of the mothers when they were pregnant, and they tested for cotinine. And cotinine is a byproduct of nicotine that stays in your system for far longer than nicotine that so it stays in your system for a few days. And that's what usually people test when you want to check if you're a smoker or not. So we had this variable. And then what we found is that while 22 mothers reported that they smoked, actually 31% had enough cotinine in their system to be considered active smokers. So that was the second problem that we needed to solve. And after we solve this issue, we will find that one extra cigarette per day decreases the baby's birth weight by by 20 to 40 grams.

Christine Garrington  6:43  

Right, so there was a there was a sort of a clear link there. And you were able to predict a baby's tendency to be born larger and heavier. How did you get that information? And what did that tell you?

Rita Pereira  6:53 

So we constructed a score, which is based on the the baby's genetic data, I mean, they're not babies now. But they were because then. So based on their genetic data, we can construct a score that gives us the child's predisposition to be born with a low or high birth weight. So just to give you an idea of how predictive this correlates, one standard deviation below or above the mean, means that you're going to be born around 100 to 110 grams lighter.

Christine Garrington  7:25  

Pulling all of this together, what would you say that we learn overall, beyond what most of us know about smoking being bad for our health and the health of our children?

Rita Pereira  7:34  

First and foremost this research highlights how harmful the nicotine effect is on your baby. But besides that, we also want to check whether the risks differ between the babies when we don't find any evidence for meaningful interactions. So this leads us to conclude that the effects seem to be the same for all babies, regardless of their genome. Okay, so it affects every baby apparently, the same more or less the same.

Christine Garrington  8:03  

Do you have any plans then to take this work further?

Rita Pereira  8:06

Yeah, we do, actually. Because now we found this great data set that allows us to have a really cool instrument, and correct for under reporting. So it's definitely in our plans to check whether smoking has other harmful effects, maybe in other outcomes. And besides that, we also wanted to look at gene environmental interactions, maybe in other contexts, such as mental health, education, and so on.

Christine Garrington  8:33  

The Interplay between Maternal Smoking and Genes in Offspring Birth Weight is a DIAL Working Paper by Rita Pereira and colleagues involved in the GEIGEI project. You can find out more about the project at gene-environment.com, and about the wider DIAL programme at dynamicsofinequality.org. Thanks for listening to this episode of our podcast which is presented and produced by Chris Garrington and edited by Elina Kilpi-Jakonen.