Coping with identity threat: The role of religious orientation and implications for emotions and action intentions.
Bibliographic record
Abstract
Religiosity is typically related to positive outcomes following distress, yet it remains unclear how religiosity may alter responses when one’s religious identity itself is challenged. The present investigation examined the role of appraisal-coping processes in the relations between religious orientations, emotions, and action intentions following identity threat. Study 1 (N 63) assessed associations with religious orientations (intrinsic and extrinsic) following a threat targeting one’s religion. Although both orientations evoked a broad array of responses, those related to an intrinsic orientation were stronger and included more negative reactions (e.g., sadness, confrontation). Study 2 (N 59) evaluated the impact of a nonreligious identity threat, which elicited only adaptive responses (i.e., problemfocused coping, support seeking) that were associated with an intrinsic orientation. Appraisal-coping processes mediated relations between religiosity and responses to an identity threat in both studies but were most evident following religious threat. Taken together, these findings suggest that whereas an extrinsic religious orientation may function as a social identity in response to religious threats, the positive effects of an intrinsic religious orientation appear to be undermined by threats targeting the social group and belief system therein.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".