Decoding the Dynamics of Social Identity Threat in the Workplace: A Within-Person Analysis of Women’s and Men’s Interactions in STEM
Bibliographic record
Abstract
The present research examined whether women’s daily experience of social identity threat in science, technology, engineering, and math (STEM) settings is triggered by a lack of acceptance during workplace conversations with male colleagues that then predicts daily experiences of burnout. To test these hypotheses, participants from two samples ( N = 389) rated their daily interactions with colleagues across 2 weeks. Results revealed that (1) women reported greater daily experiences of social identity threat on days when their work conversations with men cued a lack of acceptance, (2) these daily fluctuations of social identity threat predicted feelings of mental burnout, and (3) these effects were not found among men or for nonwork-relevant conversations. Additional analyses showed that these results were not driven by highly hostile workplace conversations between men and women, nor were they accounted for by individual differences in women’s sensitivity to perceiving gender bias, status differences, or by women being explicitly undermined by colleagues.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".