Bibliographic record
Abstract
ObjectiveIn a previous study (Iha, 2023), men voluntarily tended to choose a higher-cost option compared to women when a division of labor occurred between the opposite sexes. However, it is still unknown whether this pattern can be replicated using continuous measures when costs are not included in the choice. Therefore, the current study aimed to replicate and extend the previous study. MethodsParticipants from 4 countries (Canada, Germany, the United Kingdom and the United States of America) engaged in an online scenario experiment. ANCOVA and internal meta-analyses were used to examine whether the percentage of workload that participants voluntarily selected differed depending on the participant's own sex, and the combination of the participant's own sex and the sex of the participant's hypothetical partner.ResultsOverall, men tended to voluntarily choose more workload than women, and men paired with a hypothetical opposite sex partner voluntarily chose more workload than women paired with a hypothetical opposite sex partner. These effects were consistent across different countries.ConclusionAs a conclusion, the current study successfully replicated and expanded the previous study. In detail, it was shown that the presence of the opposite sex itself creates a division of labor, even if the participant's choice does not include the cost. Furthermore, SODOL (Spontaneous Occurrence of Division of Labor) was found to be robust regardless of the measurement method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".