Sex Differences in Sport Remain When Accounting for Countries’ Gender Inequality
Bibliographic record
Abstract
The spectator lek hypothesis argues that sex differences in preferences for sport largely stem from evolved predispositions and thus should be universal or near universal, whereas socioconstructivist hypotheses argue that such sex differences are entirely socially constructed and thus should vary as a function of a society’s gender inequality. To test these competing hypotheses, cross-national nested data were acquired from the International Social Survey Program (s s = 49,729, n countries = 34). Hierarchical linear modeling was used to examine whether sex differences in sport are universal or near universal when controlling for countries’ gender inequality. Findings indicate that even when controlling for gender inequality, sex differences remain in reporting sport as one’s most common activity, in watching sport, and in attending sport events and for agreeing with the statement that one plays sport to compete against others. Although this study was limited by the homogeneity of the sampled countries and the use of self-report measures, these findings nonetheless support the spectator lek hypothesis. Future research should examine case studies (e.g., matrilineal societies) that can specifically test the assumptions of the spectator lek hypothesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".