Love thine enemy? Evidence that (ir)religious identification can promote outgroup tolerance under threat
Bibliographic record
Abstract
The divide between religious traditionalists and secular humanists has been widening for decades; yet, little is known about factors that attenuate hostility between these groups. Two studies examined whether (ir)religious identification could mitigate negative feelings toward (ir)religious outgroups. Following priming to make salient religious groups in daily life or group-based threat, Atheists and Christians in Britain (Study 1, n = 113), and Atheists, Catholics, Jews, Muslims, and Protestants in Canada (Study 2, n = 181) reported intergroup feelings, ingroup evaluations, and perceptions of their group as viewed by others. Atheists reported the lowest ingroup identification and felt equally negative toward all religious groups. Likewise, religious group members generally felt most negative toward Atheists. However, identification with the (ir)religious ingroup was associated with less hostility toward the outgroup(s). This was particularly marked for Atheists who perceived that religious followers felt positively toward them. These results challenge suggestions that (ir)religious identification and threat necessarily promote intergroup hostility.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".