Algorithmic Bias and Access to Opportunities

The chapter discusses the problem of algorithmic bias in decision-making processes that determine access to opportunities, such as recidivism scores, college admission decisions, or loan scores. After describing the technical bases of algorithmic bias, it asks how to evaluate them, drawing on Iris Marion Young’s perspective of structural (in)justice. The focus is in particular on the risk of so-called ‘Matthew effects’, in which privileged individuals gain more advantages, while those who are already disadvantaged suffer further. Some proposed solutions are discussed, with an emphasis on the need to take a broad, interdisciplinary perspective rather than a purely technical perspective. The chapter also replies to the objection that private firms cannot be held responsible for addressing structural injustices and concludes by emphasizing the need for political and social action.

Do Disadvantaged Young Adults Benefit Less from Social Investment? Studying Matthew Effects in Activation Measures

In Germany, social investment can be crucial for disadvantaged young adults, as intergenerational mobility is low and credentials are decisive for employment. However, the literature on policy implementation calls attention to ‘Matthew effects’, by which the most disadvantaged often have the least access to social investment. We contribute to ongoing research on Matthew effects by examining whether the worst-off among young German welfare recipients are assigned to active labour market policy measures that are more advantageous or less advantageous. Findings for a register sample of 20–22 year olds in 2014 support hypotheses that those with the lowest education and employment experience participate less often in the most advantageous measures; particularly in firm-based upskilling and employment assistance, and more often in measures that proved to be not as beneficial, such as workfare programmes. On a positive note, welfare experience during adolescence as an indicator of low socio-economic status in the family of origin does not additionally affect access to social investment policy measures.

Matthew Effects in Science and the Serial Diffusion of Ideas Testing Old Ideas with New Methods

The Matthew effect has become a standard concept in science studies and beyond to describe processes of cumulative advantage. Despite its wide success, a rigorous quantitative analysis for Merton’s original case for Matthew effects – the Nobel Prize – is still missing. This paper aims to fill this gap by exploring the causal effect of the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (hereafter the Nobel Prize in Economics). Furthermore, we test another of Merton’s ideas: successful papers can draw attention to cited references leading to a serial diffusion of ideas. Based on the complete Web of Science 1900–2011, we estimate the causal effects of Nobel Prizes compared to a synthetic control group which we constructed by combining different matching techniques. We find clear evidence for a Matthew effect upon citation impacts, especially for papers published within five years before the award. Further, scholars from the focal field of the award are particularly receptive to the award signal. In contrast to that, we find no evidence that the Nobel Prize causes a serial diffusion of ideas. Papers cited by future Nobel laureates do not gain in citation impact after the award. Peer Review https://publons.com/publon/10.1162/qss_a_00129

Development of socio-economic gaps in children’s language skills in Germany

Gaps in language skills by socio-economic status (SES) are already evident before school entry, and these gaps may change over time. After discussing mechanisms of cumulative advantages (‘Matthew effects’) and compensatory effects as well as the relevance of cultural capital and child-related activities in families, this paper tests mechanisms behind changing SES gaps in language skills from age five to nine in Germany. Analysing data from the German National Educational Panel Study with growth curve models, we find widening SES gaps in children’s vocabulary. Children of mothers with low educational attainment show a far below-average increase in skills. The findings are in line with cumulative advantage by status, although initial skills predict their growth over time as well. There are no signs of any type of compensatory effects. Reading aloud to children appears to substantially impact and mediate SES differences in vocabulary progress.<br /><br />Key messages<br /><ul><li>Based on longitudinal data, vocabulary development from age five to nine in Germany is researched.</li><br /><li>At age five, vocabulary skills of children with low- and high-educated mothers differ by one year.</li><br /><li>This gap doubles in the following four years, hinting at cumulative advantages.</li></ul>

Competence Development of High Achievers Within the Highest Track in German Secondary School: Evidence for Matthew Effects or Compensation?

The Matthew effect hypothesis of academic development predictsthat students with higher initial achievement will develop further skillsat a faster rate resulting in cumulative advantages. Prior research hasfocused on the development of reading competence in primary school. Toextend this research, we used a sample of N = 1,010 German students inGrades 5 to 9 to compare the development of reading and mathematicsskills between high-achieving high-track secondary school students andtheir peers to clarify whether rates of academic development differbetween these groups. Using latent growth curve modeling, we found apattern of compensation in both domains—that is, the achievement gapbecame smaller and this was the case particularly in the early grades ofsecondary school. Thus, our results provide no evidence for the existenceof Matthew effects in reading and mathematics in lower secondary school.

Family Policy: Neglected Determinant of Vertical Income Inequality

This chapter develops a research agenda for examining family policy outcomes with respect to vertical economic inequality between households, arguing that family policies have wrongly been neglected as a determinant of vertical economic inequality. Three questions are central to this research agenda: who uses family policy, to what income effect, and with whom do people live? Family policies have been linked to women’s employment and earnings, and to lower vertical income inequality. Yet, the literature also makes abundantly clear that family policies come with trade-offs along the lines of gender and class, as well as Matthew effects. These mechanisms need to be better understood to integrate family policy in analyses of—and recommendation against—high and rising inequality. The challenge ahead is to understand what (combination of) family policies may be inclusive to a wide range of families across the full width of the income distribution.