Louis-André VALLET, organisateur de la session « Sibling Analysis in Educational and Social Stratification Research », au XX ISA World Congress of Sociology (June 25-July 1, 2023)

Sibling analysis was introduced in social stratification research during the 1970s to overcome the limitations encountered by traditional analyses of the effect of family background on educational and occupational attainment. These analyses only capture the effect of the family characteristics that are explicitly observed and included in the analytical model. They therefore provide a biased and under-estimated measure of the whole effect of the family background. However, total family impact is much larger and also includes other aspects of family socialization, parental resources, genetic inheritance, and reciprocal sibling influences. By relying on data on more than one child in a family, sibling analysis captures the total impact of the family as the resemblance between brothers and sisters, then decomposes it in observed and unobserved components. Most of the pioneering sibling analyses were based on the Wisconsin Longitudinal Study and published in the US and, over years, sibling analysis has also developed in many other countries. This regular session will host two different types of papers. On the one hand, new analyses of educational and social stratification based on a sibling design in a given country or a comparative perspective, across cohorts or between countries. On the other hand and in a perspective of cumulative science, contributions that try to systematically assess what we have learned with sibling analysis in education and social stratification research and how these results compare with those derived from traditional analyses, especially with regard to temporal trends, change across cohorts, and comparison between countries.

Session Organizer:

Louis-Andre VALLET, French National Centre for Scientific Research – CNRS, France, louis-andre.vallet@cnrs.fr

Accédez à l’appel à communications publié le 1er juillet 2022

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