Identity centrality moderates the relationship between acceptance of group‐based stressors and well‐being
Bibliographic record
Abstract
Abstract Two two‐wave studies were used to examine the proposition that identity centrality enhances the effectiveness of stressor acceptance in the face of group‐based stressors. Study 1 was conducted in newly commencing psychology students ( N = 154). Stressor intensity, psychology student identity centrality, and attempted stressor acceptance were measured at two‐time points over 6‐weeks. Study 2 was conducted in a group of early to late career veterinarians ( N = 92) and extended Study 1 by assessing stressor frequency as an indicator of the level of demand. Veterinarian identity centrality and stressor acceptance were measured twice over 12‐months. Both studies provided support for the predicted three‐way interaction. Only when Time 1 stressors and identity centrality were both high was stressor acceptance related to a reduction in perceived stressor intensity (Study 1) or burnout symptoms (Study 2) at Time 2. These findings suggest that identity centrality enhances the effectiveness of stressor acceptance for supporting wellbeing and resilience.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".