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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".