Scott Alexander outlines 18 preregistered investigations for the 2019 SSC survey, covering topics from psychiatric medication effects to birth order influences. Longer summary

Scott Alexander preregisters 18 investigations for the 2019 Slate Star Codex survey. These investigations cover a wide range of topics including psychiatric medication effects, social class perceptions, life history strategies, gender bias, imposter syndrome, and birth order effects. The post begins by urging readers to take the survey before reading further to avoid bias. Each investigation is briefly described, often including the reasoning behind it or the specific analysis method to be used. The investigations touch on fields such as psychology, sociology, psychiatry, and genetics, reflecting the diverse interests of the blog's audience. Shorter summary

Scott Alexander critiques a study claiming gender bias in GitHub, pointing out methodological flaws and media misrepresentation of its non-peer-reviewed findings. Longer summary

Scott Alexander critiques a study about gender bias in GitHub pull request acceptance rates. He points out several issues with the study's methodology and interpretation, including the lack of peer review, ambiguous statistical significance, and potential confounding factors. He also criticizes media outlets for misrepresenting the study's findings, exaggerating its conclusions, and failing to mention its non-peer-reviewed status. Scott emphasizes that the study actually shows women's pull requests are accepted more often overall, and that the observed bias against women in one subgroup is small and possibly not statistically significant. He expresses concern about how such studies are used to promote a narrative of widespread sexism in tech. Shorter summary

Scott Alexander analyzes two conflicting studies on gender bias in STEM hiring, exploring reasons for their contradictory results and the challenges in reaching a definitive conclusion. Longer summary

Scott Alexander discusses two contradictory studies on gender bias in STEM hiring, one showing bias against women and another showing bias in favor of women. He explores possible reasons for the discrepancy, including differences in methodology and potential experimenter bias. The post highlights the difficulty in reaching a definitive conclusion on this issue despite its importance and the resources dedicated to studying it. Scott suggests that the conflicting results might be due to subtle experimenter effects and proposes a joint study by both teams as a potential solution. Shorter summary