Are many sex/gender differences really power differences?
Bibliographic record
Abstract
Abstract This research addresses the long-standing debate about the determinants of sex/gender differences. Evolutionary theorists trace many sex/gender differences back to natural selection and sex-specific adaptations. Sociocultural and biosocial theorists, in contrast, emphasize how societal roles and social power contribute to sex/gender differences beyond any biological distinctions. By connecting two empirical advances over the past two decades—6-fold increases in sex/gender difference meta-analyses and in experiments conducted on the psychological effects of power—the current research offers a novel empirical examination of whether power differences play an explanatory role in sex/gender differences. Our analyses assessed whether experimental manipulations of power and sex/gender differences produce similar psychological and behavioral effects. We first identified 59 findings from published experiments on power. We then conducted a P-curve of the experimental power literature and established that it contained evidential value. We next subsumed these effects of power into 11 broad categories and compared them to 102 similar meta-analytic sex/gender differences. We found that high-power individuals and men generally display higher agency, lower communion, more positive self-evaluations, and similar cognitive processes. Overall, 71% (72/102) of the sex/gender differences were consistent with the effects of experimental power differences, whereas only 8% (8/102) were opposite, representing a 9:1 ratio of consistent-to-inconsistent effects. We also tested for discriminant validity by analyzing whether power corresponds more strongly to sex/gender differences than extraversion: although extraversion correlates with power, it has different relationships with sex/gender differences. These results offer novel evidence that many sex/gender differences may be explained, in part, by power differences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".