The transition from school to work is a crucial turning point in young people’s lives. While employment is central to social inclusion and economic independence, access to the labor market is unequally distributed. Research documents hiring disadvantages based on disability and migration background, and context-dependent disadvantages based on gender (e.g. Berthoud, 2008; Birkelund et al., 2022; Heath et al., 2008). A growing body of work further highlights that such disadvantages may intersect, leading to particularly adverse outcomes for individuals who combine multiple marginalized identities. However, it remains unclear whether these inequalities reflect additive effects of single attributes or intersectional effects that go beyond additivity. This study examines how recruiters’ evaluations of young candidates’ chances of being hired vary across intersectional strata defined by disability status, migration background and gender. Drawing on intersectionality theory (Collins, 2019), disability critical race theory (Annamma et al., 2013), theories of social distance and stigma (Goffman, 2018), we expect systematic differences in hiring evaluations across these strata. These expectations are further reinforced by an economic rational perspective, which assumes recruiters rely on perceived productivity signals (Esser, 1999). Such perceptions may be shaped by stereotypes and stigma. Taken together, these theoretical perspectives lead us to hypothesize that hiring evaluations vary across intersectional strata, with some strata deviating from expectations based on additive main effects. Empirically we draw on a factorial survey experiment administered to recruiters in Switzerland and Luxembourg. Recruiters from five occupational sectors evaluated the hiring chances of fictive young applicants described in short vignettes. The vignettes were experimentally varied along the dimensions disability, nation of origin, and gender. Age, education, language proficiency, work experience and work permit status were held constant. In total, 464 employers evaluated multiple vignettes, resulting in 2.784 vignette ratings on an 11-point scale. To analyze intersectional inequalities, we employ multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA), using a cross-classified specification to account for vignette clustering within recruiters (Evans et al., 2019; Van Dusen et al., 2024). Preliminary results indicate that most between-stratum variation is explained by additive effects of disability status and migration background, with gender playing a comparatively smaller role. Residual variance between intersectional strata is minimal once these main effects are accounted for, suggesting limited evidence of intersectional deviation beyond additivity. Nevertheless, consistent with theories of stigma, recruiters’ assessments remain strongly structured by additive disadvantages related to disability and migration background.

Annamma, S. A., Connor, D. & Ferri, B. (2013). Dis/ability critical race studies (DisCrit): theorizing at the intersections of race and dis/ability. Race Ethnicity and Education, 16(1), 1-31. Berthoud, R. (2008). Disability employment penalties in Britain. Work, Employment and Society, 22(1), 129-148. Birkelund, G. E., Lancee, B., Larsen, E. N., Polavieja, J. G., Radl, J. & Yemane, R. (2022). Gender Discrimination in Hiring: Evidence from a Cross-National Harmonized Field Experiment. European Sociological Review, 38(3), 337-354. Collins, P. H. (2019). Intersectionality as Critical Social Theory. Duke University Press. Esser, H. (1999). Soziologie: Allgemeine Grundlagen (3rd ed.). Campus Verlag. Evans, C. R. (2019). Reintegrating contexts into quantitative intersectional analyses of health inequalities. Health & place, 60, 102214. Goffman, E. (2018). Stigma. Über Techniken der Bewältigung beschädigter Identität (24. Aufl.). Suhrkamp. Heath, A. F., Rothon, C. & Kilpi, E. (2008). The Second Generation in Western Europe: Education, Unemployment, and Occupational Attainment. Annual Review of Sociology, 34(1), 211-235. Van Dusen, B., Cian, H., Nissen, J., Arellano, L., & Woods, A. D. (2024). Comparing the Efficacy of Fixed-Effects and MAIHDA Models in Predicting Outcomes for Intersectional Social Strata. Sociology of Education, 97(4), 342–362.