Harm Is Key to Judgments That Stealing Is Immoral
Bibliographic record
Abstract
Stealing is considered to be a typical moral violation, but is taking without permission immoral when it does not involve harm? To assess the role of harm in reasoning about taking resources, two studies were conducted. In Study 1, 201 American undergraduates with a range of political orientations (M = 3.81 on a 7-point scale, SD = 1.49) judged instances of taking resources without permission to benefit a third party. Study 2 built on Study 1, testing 288 undergraduate students from the U.S. and Canada with a range of political orientations (M = 4.52 on a 10-point scale, SD = 2.02). Across both studies, participants judged vignettes that varied who took the resources (an authority or an individual), the need of the recipient, and the harm to the owner (left with not enough or more than enough). Labeling acts as stealing was only moderately associated with evaluations of acts in both studies. Harm was key to judgments of taking without permission across political orientations: participants judged taking resources without permission as unacceptable when it harmed the owner but as acceptable when it helped others in need. In the absence of harm, stealing was not consistently seen as a moral issue.
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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 | 0.007 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".