The lives of others: Third parties’ responses to others’ injustice.
Bibliographic record
Abstract
This research takes a moral perspective to studying third parties' reactions to injustice as a function of their moral identity. Drawing from theories of deontic justice, moral intuition, moral heuristics, and moral identity, we develop and test a model of the moral underpinnings of third parties' reactions to injustice. First, we compare third parties' responses with interpersonal, distributive, and procedural justice violations. We hypothesize that third parties are more likely to intuit that interpersonal justice violations are morally wrong, compared with distributive and procedural justice violations. As a result, third parties are more likely to experience stronger moral anger and punish violators in response to interpersonal transgressions compared with distributive and procedural justice transgressions. Second, we test the proposition that third parties with a strong moral identity will react more strongly to justice violations than third parties with a comparatively weak moral identity. Results from 3 studies support these predictions.
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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 | 0.002 | 0.012 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".