“Do Unto Others”: Effects of Priming the Golden Rule on Buddhists’ and Christians’ Attitudes Toward Gay People
Bibliographic record
Abstract
The Golden Rule, a core precept of many religions, emphasizes the importance of treating others with compassion. We examined whether priming Golden Rule messages would influence Buddhists’ and Christians’ attitudes toward gay people and perceptions that homosexuality is a choice. In a priming task, participants filled in missing words for popular quotations including two Golden Rule messages that were attributed to either Buddha or Jesus. Christians ( N = 585) in the Buddha-attributed Golden Rule condition showed stronger explicit anti-gay attitudes and were more likely to agree that homosexuality is a choice than Christians in the Jesus-attributed or control conditions, = .012, = .035, even after controlling for political orientation and religiosity. Buddhists ( = 394) showed no variation in attitudes across priming conditions, = .001, = .78. Our results suggest that although the Golden Rule has an important influence on believers, its message of compassion may produce more prejudice if it comes from an outgroup source compared to an ingroup source.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| 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".