This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

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The persistence of horizontal sex segregation in higher education continues to puzzle social scientists. To help resolve this puzzle, we analyze a sample of college entrants in Germany with a discrete choice design that allows for social learning from the experiences of others. We make at least two contributions to the state of research. First, we test whether essentialist gender stereotypes affect major selection mostly through internalization or rather as external constraints that high school graduates adapt their behavior to. Empirically, we find that internalized vocational interests better explain gendered major choices than conformance with friends' and parents' expectations does. Second, we scrutinize whether segregation results from women's anticipation of gendered family roles or from their anticipation of sex-based discrimination, but we find no evidence for either of these hypotheses. As in most previous studies, differences in mathematics achievement fail to explain gendered patterns of selection into college majors.

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As men are overrepresented in lucrative fields and women disproportionately graduate from disciplines that yield low wages in the labor market, horizontal sex segregation in higher education contributes significantly to economic gender inequality. But what underlies the association between sex composition and wages in fields of study? We draw on data from the German HIS Graduate Panel Study 1997 (N=4092) and use hierarchical linear models to adjudicate between devaluation theory and explanations based on differential sorting processes: human capital and gender role theory. The resulting evidence for both human capital and devaluation theory is scant. Consistent with gender role theory, differences in the attractiveness of fields to students with a careerist approach to higher education and the labor market in turn explain most of the association between field of studies’ sex composition and wage levels. We therefore conclude that gendered patterns of self-selection which derive from men’s socialization into the breadwinner role rather than valuative discrimination or rational anticipation of career interruptions underlie the association between fields’ sex composition and wage levels.