Drawing on literatures in statistics and cognitive science, this essay discusses the important difference between drawing conclusions based on statistical inference, which concerns aggregates such as mean scores, and generalization, which posits characteristics of individuals classified into kinds. To supplement findings of statistical significance, quantitative measures of substantive difference (Cohen’s d) and overlap (the Index of Similarity) are computed from the data on men, women, and risk used in 28 published articles. The results are considerably more mixed and overlapping than might be expected. Paying attention to empirical evidence that challenges subjective cultural beliefs about sex and risk has implications for labor economics, finance, and the economics of climate change.
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