Enjoying Each Other’s Company: Gaining Other-Gender Friendships Promotes Positive Gender Attitudes Among Ethnically Diverse Children
Bibliographic record
Abstract
Gender segregation is ubiquitous and may lead to increased bias against other-gender peers. In this study, we examined whether individual differences in friendships with other-gender children reduce gender bias, and whether these patterns vary by gender or ethnicity. Using a 1-year longitudinal design ( N = 408 second graders [ M age = 7.56 years] and fourth graders [ M age = 9.48 years]), we found that, across groups, gaining more other-gender friendships over the year led to (a) increased positive cognitive-based attitudes toward the other gender and (b) increased positive and decreased negative affect when with the other gender. We also tested the reverse pattern and found support for a bidirectional link. Girls and Latinx children often showed more gender bias than did boys and European American children. Implications for promoting positive relationships between girls and boys are discussed.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".