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 dissects a hoax chocolate study to critique common misconceptions about nutrition science, study design, and statistical methods. Longer summary

Scott Alexander analyzes a viral study claiming chocolate aids weight loss, which was revealed as a hoax designed to expose poor science journalism. He critiques four common but incorrect conclusions drawn from this incident: that people were gullible for believing it, that nutrition isn't a real science, that studies always need high sample sizes, and that p-values should be eliminated. Scott argues that there is previous research supporting chocolate's health benefits, that nutrition science uses multiple study types to build evidence, that sample size importance depends on the effect being studied, and that p-values have their place in research. He agrees with the fifth conclusion that science journalism should be trusted less, but notes that some sources like Wikipedia and specialized blogs are more reliable. Shorter summary

Scott Alexander critiques a study on gender gaps in academia, arguing it ignores actual measures of ability which better explain the disparities. Longer summary

Scott Alexander critiques a study claiming that women are underrepresented in fields perceived to require innate talent. He argues that the study ignores actual measures of ability like GRE scores, which correlate more strongly with gender representation. Scott shows that when controlling for GRE quantitative scores, there is little left to explain in terms of gender gaps in fields like mathematics. He suggests the study's findings are an artifact of using perceptions as a proxy for actual ability, and criticizes how the media has misinterpreted the results. Shorter summary