Moral paragons, but crummy friends: The case of snitching.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Loyalty to friends is an important moral value, but does that mean snitching on friends is considered immoral? Across six preregistered studies, we examine how loyalty obligations impact people's moral evaluations of snitching (i.e., turning in others who commit transgressions). In vignette and incentivized partner choice paradigms, we find that witnesses who snitch (vs. do not snitch) are seen as more moral and as better leaders (Studies 1-6), regardless of whether they snitch on a friend or an acquaintance (Studies 1-3). We find that a willingness to turn in one's friends increases perceived morality, while an unwillingness to do so diminishes it, with the latter effect exhibiting a stronger impact than the former (Study 2). Our experiments also demonstrate that snitches receive less moral credit when snitching on nonmoral (vs. moral) transgressions (Study 3) and when snitching aligns with self-interest (Study 4). We demonstrate that although snitching is often seen as morally right, turning in transgressors entails important reputational trade-offs: Snitching makes one appear disloyal and a bad friend but boosts perceptions of morality and leadership. This reveals a context in which what is loyal is no longer considered moral. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 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 it