Underestimating Our Influence Over Others’ Unethical Behavior and Decisions
Bibliographic record
Abstract
We examined the psychology of "instigators," people who surround an unethical act and influence the wrongdoer (the "actor") without directly committing the act themselves. In four studies, we found that instigators of unethical acts underestimated their influence over actors. In Studies 1 and 2, university students enlisted other students to commit a "white lie" (Study 1) or commit a small act of vandalism (Study 2) after making predictions about how easy it would be to get their fellow students to do so. In Studies 3 and 4, online samples of participants responded to hypothetical vignettes, for example, about buying children alcohol and taking office supplies home for personal use. In all four studies, instigators failed to recognize the social pressure they levied on actors through simple unethical suggestions, that is, the discomfort actors would experience by making a decision that was inconsistent with the instigator's suggestion.
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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 | 0.009 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".