Gender, mood state, and justice preference: Do mood states moderate gender‐based norms of justice?
Bibliographic record
Abstract
The present study extends research on distributive justice by investigating whether a person's mood state moderates the robust effects of gender norms on allocation decisions. One hundred and eighty undergraduates (90 men: 90 women) were asked to undergo a mood induction procedure in which they were randomly assigned to a positive, negative, or neutral mood condition, and to work on a task with either a male or female co-worker (confederate). This resulted in a 2 (gender of participant) x 2 (gender of confederate) x 3 (positive vs. neutral vs. negative mood) between-subjects factorial design. Following completion of the task, participants were informed that they did 60% of the work and their co-worker did 40%. They were then asked to divide money between themselves and their co-worker in a way that they considered fair. The analysis revealed a three-way interaction in participants self-payment whereby men in a negative mood, working with other men took more pay for themselves than did participants in all other conditions. Specifically, 60% of the participants in this condition, allocated the payment either equitably or in a manner suggesting even greater self-interest. These results support the view that gender effects are strongly influenced by the presence of other relevant contextual cues.
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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) | 0.001 | 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 | 0.000 |
| 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".