Socioeconomic status (SES) is a widely researched construct in developmental science, yet less is known concerning relations between SES and adaptive behavior. Specifically, is the relation linear, with higher SES associated with better outcomes, or does the direction of association change at different levels of SES? Our aim was to examine linear (“more is better”) and quadratic (“better near the middle”) associations between components of SES (i.e., income, years of education, occupational status/prestige) and depressive symptoms (Center for Epidemiologic Studies–Depression Scale), and to explore moderation by developmental period (adolescence, young, middle, and older adulthood), gender/sex (female, male), and race/ethnicity (Asian American, Black, Latinx, multiracial, Native American, White). We hypothesized that there would be more support for a model containing quadratic associations. We conducted a two-stage meta-analytic structural equation model of 60 data sets (27,242 correlations, 498,179 participants) within the United States, accounting for dependencies between correlations, which were identified via the Interuniversity Consortium for Political and Social Research and handled using a two-step approach. Income was quadratically associated with depressive symptoms, but the quadratic model did not explain more variance in depressive symptoms than the linear model. Developmental period and race/ethnicity moderated the associations: Income was quadratically associated with depressive symptoms among middle-aged adults, and years of education were quadratically associated with depressive symptoms among White samples. Our findings suggest that researchers and clinical practitioners should consider the elevated risk of depressive symptoms for individuals from low and high-income backgrounds in the United States.

When employers' explicit gender requests were unexpectedly removed from a Chinese job board overnight, pools of successful applicants became more integrated: women's (men's) share of callbacks to jobs that had requested men (women) rose by 61 (146) percent. The removal "worked" in this sense because it generated a large increase in gender-mismatched applications, and because those applications were treated surprisingly well by employers, suggesting that employers' gender requests often represented relatively weak preferences or outdated stereotypes. The job titles that were integrated by the ban, however, were not the most gendered ones, and were disproportionately lower-wage jobs.