Same-Sex and Opposite-Sex Differences in Friendship Quality and Conflict Resolution
Bibliographic record
Abstract
Cross-sex friendships are common during young adulthood. Yet, they vary widely and are vulnerable to misunderstanding, even by the friends themselves. We examined how cross- and same-sex friends responded to different types of relationship conflict. We hypothesized that same-sex friends would respond more negatively to conflict than would cross-sex friends. Young adult participants (n= 127) were primarily women (64%) and equally divided between African American (41%) and Caucasian (39%). Participants were randomly prompted to either think of their closest same-sex or opposite sex friend and then to respond to the McGill Friendship Questionnaire. Participants then encountered three conflict scenarios (hurtful remark, social exclusion, betrayed secret) and asked how they would respond if these occurred with the imagined friend. Our hypothesis was not supported. We did not find differences in friendships based solely on the gender match or mismatch of the friendship. Instead we found that men were very sensitive about a female friend making a hurtful comment or socially excluding him. Neither gender was surprised by a male friend being socially exclusive. Despite these findings, how adults reacted to the friendship scenarios depended more on their gender than on the gender of their friend. In general, women were more upset by our conflict scenarios than were men and felt it was important to help their friend see their point of view. Age and race were not predictive of friendship perceptions. These findings add to our understanding of this common experience of young adulthood.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".