Het coronavirus zou niet discrimineren volgens Bert Wagendorp. Deze aanname klopt hoogstwaarschijnlijk niet. Een sluitend antwoord op de vraag of het coronavirus discrimineert op basis van bijvoorbeeld gender laat op zich wachten: volgens onderzoekers in The Lancet ontbreekt tot nu onderzoek naar pandemieën en genderverschillen. Desalniettemin lijkt het coronavirus wel degelijk te discrimineren: sociaaleconomische verschillen en genderverschillen op basis van blootstelling liggen op de loer.

Onderliggende sociaaleconomische verschillen kunnen leiden tot sociaaleconomisch onderscheid in blootstellingskansen. Jezelf beschermen tegen blootstelling gaat een stuk makkelijker als je een vaste baan hebt, of een goed gevulde bankrekening (denk aan het thuis laten bezorgen van pakketten of boodschappen). Voor de mensen die al moeilijk de eindjes aan elkaar konden knopen, is thuiswerken vaak geen optie en meerdere dagen werk missen ook niet. Hierdoor lopen zij een veel groter risico om blootgesteld te worden. Niet voor niets zien we overal ter wereld – van New York tot Stockholm tot Johannesburg – dat arme wijken het centrum van coronabesmettingen vormen.

Blootstellingskansen kunnen ook hoger liggen voor vrouwen, bijvoorbeeld doordat vrouwen oververtegenwoordigd zijn in de sector die nu het hardst werkt om ons in leven te houden, de gezondheidszorg. Zij stellen zich dagelijks bloot aan mensen die besmet zijn. Voor bepaalde beroepsgroepen in de gezondheidszorg waar vrouwen ook sterk oververtegenwoordigd zijn, zoals de thuiszorg, is de situatie zelfs schrijnend te noemen. Er is nu al onvoldoende beschermingsmateriaal voor al het personeel. Dit zijn vaak dezelfde thuiszorgorganisaties die de laatste jaren steeds meer moesten doen met beperkte middelen door stevige overheidsbezuinigingen.

En dat is misschien wel het pijnlijkst aan het coronavirus: de discriminatie van het virus hebben we als maatschappij over onszelf afgeroepen. Hoewel de regering nu ongekende en zeer noodzakelijke maatregelen neemt om zowel de medische als de economische gevolgen van de coronapandemie te dempen, is zij ook medeverantwoordelijk voor de jarenlange uitholling van de publieke sector, de afwenteling van arbeidsrisico’s op werknemers, de onzekerheid op de arbeidsmarkt, de groei van het aantal onvrijwillige zzp’ers, en het afschuiven van zorgtaken op mantelzorg (wederom voor het overgrote deel door vrouwen gegeven). Allemaal factoren die de blootstellingskansen voor lagere sociaaleconomische klassen en vrouwen vergroten.

Wie net als Bert Wagendorp beweert dat het virus niet discrimineert, sluit de ogen voor de maatschappelijke scheidslijnen die het virus blootlegt. We hebben onze samenleving zelf zo ingericht dat sociaaleconomische klasse en gender bepalen wie de grootste kans heeft om aan het virus blootgesteld te worden.

Mara A. Yerkes is Universitair Hoofddocent in Interdisciplinaire Sociale Wetenschap (Universiteit Utrecht) met expertise op het terrein van sociaal beleid en sociale ongelijkheid.

Rense Nieuwenhuis is Associate Professor in de sociologie bij het Zweeds instituut voor sociaal-wetenschappelijk onderzoek (SOFI) aan de Universiteit van Stockholm. Hij doet onderzoek op het gebied van sociaal-economische ongelijkheid, gezinnen, en sociaal beleid.

Read more in our new open access publication!

Alm, S., Nelson, K., & Nieuwenhuis, R. (2019). The Diminishing Power of One? Welfare State Retrenchment and Rising Poverty of Single-Adult Households in Sweden 1988–2011. European Sociological Review, 0(0), 20.

This discussion paper provides an updated analysis of gendered economic inequality in high- and middle-income countries. A review of the literature demonstrates that such an analysis needs to explicitly recognize that gender, poverty, and (economic) inequality are intrinsically linked. Specifically, the paper addresses two sets of questions:

• First, how do intra-family resource allocation and distribution patterns both reflect and shape gender inequalities in power and well-being, and what factors—including policy-related ones—can mitigate these inequalities?
• Second, how do families as gendered institutions contribute to broader socio-economic inequalities, and what can be done to reduce/reverse these inequalities?

Using data from the LIS Database, this paper shows considerable differences among 42 countries with respect to how likely women were to have their own income. The period from 2000 to 2010/2014 saw increasing rates of own incomes as well as women’s incomes constituting larger shares in total household income. A key finding is that, in countries where many women have an income of their own, relative poverty rates are lower.

The comparative analyses, combined with a review of the literature, suggest that welfare state arrangements that support working women not only improve the overall employment rates of women but also help to prevent particularly women in low-income households from living in dependence and instead to have an income of their own—thus reinforcing the potential for poverty reduction. Moreover, institutional contexts that are generally conducive to women’s employment tend to be effective across family forms.

I was a great pleasure to work with the excellent LIS team on this project, and an honour to prepare this report commissioned by UN Women (the United Nations organization dedicated to gender equality and the empowerment of women). This paper was produced for UN Women’s flagship report, “Progress of the World’s Women 2019”.

This project examines how the rise of women’s employment and earnings affected trends in economic inequality among all households, across OECD and European countries since the 1980s. So far, prominent explanations of economic inequality have neglected the potential impact of women’s rising earnings on inequality among households, even though it is one of the most profound developments in economic activity in recent decades.

This project theorizes and analyzes how trends in women’s employment and earnings affected vertical inequality: the extent to which household incomes differ. For economic inequality it matters a great deal whether the rise of women’s employment and earnings was predominantly among singles and single mothers, among women living in couples, or among households with additional earners that already were close to the top (or bottom) of the earnings distribution. In this project, I also study how institutional contexts shape employment and earnings of women across diverse households.

This proposed theory will be rigorously tested using state-of-the-art quantile regression techniques and longitudinal data from EU-SILC and LIS, combined with high quality indicators of institutional context. Empirical studies address four areas of particular interest: (A1.) family diversity including single parents, (A2.) causal inferences, and the impact of the institutional context that is characterized both by (B1.) family policy and (B2.) social security.

The triple bind of single-parent families is available for free/open access download.

What kind of barriers and risks do single parents face? In their new book, The Triple Bind of Single-Parent Families: Resources, Employment and Policies to Improve Well-Being (Policy Press, 2018), editors Rense Nieuwenhuis and Laurie C. Maldonado argue that understanding inadequate resources, employment, and policies matter for understanding single-parent families. They refer to these as the “Triple Bind.” Part One explores resources, including exploring education, wealth gaps, and school settings. Other chapters in this section also explore how single-parenthood is often a transitory phase and the importance of co-parenting. Part Two explored inadequate employment and starts with an important chapter about taking a life course perspective when researching single-parents. The chapters in this section also tackle income transfers, paid parental leave, and other workplace characteristics. Part Three focuses on redistributive policies, including cash benefits, universal vs. targeted polices, daycare, and minimum income. Part Four concludes the book with important discussions around framing single-parents in a “deficit model” way, the importance of gender in the discussion of single-parents, and ideas for future research.

This book is free to download in its entirety online and therefore is made accessible to anyone who may be interested in one or all of the topics contained within! Overall, this book tackles important topics around single-parents around the world and would be useful for an upper level undergraduate course in the Sociology of Family or Family Studies. It would also be the perfect addition to a graduate level course that focus on families.

Abstract

It is demonstrated that family policies are an important aspect of the institutional context of earnings inequality among coupled households. Although seldom integrated into prominent analyses of economic inequality, women’s earnings are consistently found to reduce relative inequality among households. This means that family policies, as well-known determinants of women’s employment and earnings, are important contextual determinants of economic inequality. Using Luxembourg Income Study data from 18 OECD countries in the period 1981–2008, this study demonstrates that women have higher earnings, and that their earnings reduce inequality among coupled households more in institutional contexts with generous paid leave and public childcare. We found no sizeable association between financial support policies, such as family allowances and tax benefits to families with children, and the degree to which women’s earnings contribute to inequality among coupled households. Family policy arrangements that facilitate women’s employment and earnings are associated with less economic inequality among coupled households.

Nieuwenhuis, R., Need, A. & Van der Kolk, H. (2018). Family policy as an institutional context of economic inequality. Acta Sociologica. Forthcoming, online first: http://journals.sagepub.com/doi/full/10.1177/0001699318760125

Single parents face a triple bind of inadequate resources, employment, and policies, which in combination further complicate their lives.

This book – multi-disciplinary and comparative in design – shows evidence from over 40 countries, along with detailed case studies of Sweden, Iceland, Scotland, and the UK. It covers aspects of well-being that include poverty, good quality jobs, the middle class, wealth, health, children’s development and performance in school, and reflects on social justice.

Leading international scholars challenge our current understanding of what works and draw policy lessons on how to improve the well-being of single parents and their children.

Don’t buy our book!

Well, you can. There is a beautiful hardback version available. But you don’t have to. The open access .PDF of the book is free to download, thanks to generous support of Knowledge Unlatched.

Free download: http://oapen.org/search?identifier=643492
Policy Press website: http://policypress.co.uk/the-triple-bind-of-single-parent-families

Family policies are those public policies that directly affect families with children. Given the fact that definitions of what constitutes a family are constantly changing, and with changing goals of governments, the nature of family policies has been changing since their early inception (in their modern form) at the time of industrialization. Family policies are understood as having a variety of goals, including 1) poverty reduction and income maintenance, 2) direct compensation for the financial cost of raising children, 3) fostering employment, 4) improving gender equity, 5) support for early childhood development, and 6) raising birth rates (see Thévenon 2011 in Origin and Variety of Family Policies).

The available research on family policies is vast, and naturally difficult decisions had to be made to end up with the selection of studies presented here. Important works and topics had to be left out, although many of the topics that are not explicitly discussed emerge in one form or another in our selection of research. Although our selection seeks to cover a broad range of perspectives, we have focused on 1) empirical research, often (but not exclusively) quantitative in nature, 2) research on outcomes of family policies, 3) research on family policy outcomes that include employment, wages, poverty, and fertility, and 4) in addition to some classics, some recent works that point to current frontiers in family policy research.

The references are organized in six major categories, which necessarily show some overlap. We begin with several General subsections that cover the Origin and Variety of Family Policies, selected Classics, concepts, Research Overviews, discussions on Gender in Welfare State Regimes, and recent perspectives on family policies such as social investment. Next, we detail studies that examined various forms of family Policies as their object of study, covering parental leave, childcare, and cash support for families, including child support and alimonies. Third, we selected studies on Outcomes pertaining to employment, unpaid work, occupations and earnings, poverty, and fertility. Fourth, we highlight several Debates that are ongoing in the literature, including on the Matthew Effect and on using aggregated data to study the link between fertility and (women’s) employment. Fifth, we highlight several research Frontiers: areas of more recently developed topics that include the role of fathers, family policies outside the EU or OECD, company-level (rather than public) family policies, and the use of experimental approaches. We conclude by listing a range of Data Sources that are relevant for the continued study of family policies and their outcomes.

The chapter is available online

Of course, all credit for winning matches goes to the players and their coaches. Popularity of (women’s) football in a country surely is important for being able to draft good teams. Training facilities, strategies, and all kinds of football-related factors will be of great importance, but those should be analysed by someone who actually knows something about football.

Instead, I decided to have a look at three factors that are not (directly) related to football. Gender (in)equality, first, represents women’s opportunities in a country. If inequality is high, fewer women may have the opportunity to play football, let alone to do so professionally. The size of a countries’ population, secondly, will facilitate drafting better players simply because in these countries there are more women who may discover to have talent for football. Finally, I look at how ‘rich’ a country is: richer countries may be able to provide better support to their teams, support (more) professional teams, and perhaps have more youth teams. The story came out a bit technical, but bear with me.

To test these ideas, I used data on the results of all matches played in Women’s Euro 2017 (including the qualification matches, but given the time of writing without the final). I used data on each match twice, once to assess the likelihood that team A would win, and once for team B. More sophisticated analyses would simultaneously account for characteristics of both teams in each match, as well as the structure of the tournament, but for now this should do. I then estimated a multilevel (logistic) regression model of the likelihood that each team would win their matches with random intercepts for each country (one might interpret these random effects as the latent capability of each team). Data from the United Nations were obtained on their Gender Inequality Index (from the Human Development Reports), population size, and GDP per capita. The latter two were logged and standardised. Some additional datapoints, for instance on Wales and Scotland, were obtained from wikipedia. Andorra and the Faroe Islands were removed due to missing data. It should be stressed that this is a very simple analysis, done for fun, and results should be interested with a grain of salt and certainly without causality.

The results are presented in the Table below. Model 1 is just a baseline model to estimate how much countries differ in their likelihood to win matches (represented by the random intercept variance, to which I’ll return later). Model 2 shows that countries with higher gender INequality have a lower likelihood of winning matches. Model 3 shows that countries win more matches when they have a larger population and a higher GDP per capita. The effect of gender inequality now vanishes (this is due solely to adding GDP to the model, not shown). This is easily explained: in more gender equal societies more people contribute to the formal economy, thus boosting GDP per capita. Thus, gender equal countries have performed better on Women’s EURO 2017 in part because their level equality made this countries more prosperous.

Finally, Model 4 shows that the effect of a higher GDP per capita are weaker in more gender unequal societies. In other words, the benefits that rich countries have only benefit women’s teams in Euro 2017 if these countries have an adequate level of gender equality. This interaction is shown in the Figure below. Countries that score higher than 0.2 on the gender inequality index (about the level of Latvia and Kazakhstan) have no benefit of an increase in their GDP per capita.

The Table also showed the random intercept variance to represent how much countries differed in their capability to win matches. In the baseline model this was estimated to be .99. The absolute number doesn’t mean that much, but when gender inequality is accounted for in model 2, the number is almost halved to .55. This means that levels of gender inequality explain almost half of the differences in countries’ performance in Women’s Euro 2017. Also accounting for population size and GDP per capita (model 3) further reduces the random intercept variance to .13, and the interaction between GDP and gender inequality leaves the variance at .06. This means that with these 3 variables, 94% of differences between countries’ performance can be explained.

One important take-away from these models is that the likelihood that a national team did well in Women’s Euro 2017 was determined by (/associated with) to a very large extent with structural factors that are not directly related to football. Another is that gender equality plays a major role.

Will the models tell us who will win tonight? No, for that purpose more detailed models would be required. The figure below shows the random intercepts (i.e. the latent capability of each country to win matches) as estimated for each country. The circles show the baseline estimates, indicating how well each team did during the tournament (for those interested, the triangles show how countries would have performed had it not been for their level of gender inequality. Generally, countries that did well would have done less well had it not been for their high level of gender equality. Romania and Russia, for instance, would actually have performed better if these countries had better gender equality.). So far, the Netherlands have done slightly better than Denmark (in part, of course, by the Netherlands beating Denmark earlier in the tournament). Yet, England is estimated to have done better than the Netherlands, and Germany better than Denmark (remember that these data also include the qualifying phase of the tournament). Evidently, both England and Germany are out already (eliminated by the Netherlands and Denmark, respectively) which indicates that there are plenty of things these models do not account for. Teams ‘growing’ into the tournament being one, and both the Netherlands and Denmark seem to have done so.

What these analyses do suggest, is that Denmark and the Netherlands would not have been final had these not been rich countries with high levels of gender equality. For the rest, who will win tonight is up to the players.