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Record W4406981158 · doi:10.1525/collabra.127729

Harm Is Key to Judgments That Stealing Is Immoral

2025· article· en· W4406981158 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCollabra Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsConcordia University
Fundersnot available
KeywordsHarmKey (lock)PsychologyCriminologySocial psychologyComputer securityComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.108
GPT teacher head0.468
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it