Bibliographic record
Abstract
If someone unintentionally breaks the rules, do they break the rules? In the abstract, the answer is obviously "yes." But, surprisingly, when considering specific examples of unintentional, blameless rule-breaking, approximately half of people judge that no rule was broken. This effect, known as excuse validation, has previously been observed in American adults. Outstanding questions concern what causes excuse validation, and whether it is peculiar to American moral psychology or cross-culturally robust. The present paper studies the phenomenon cross-culturally, focusing on Korean and American adults, and proposes a new explanation of why people engage in excuse validation, in terms of competing forces in human norm-psychology. The principal findings are that Americans and Koreans engaged in excuse validation at similar levels, and older adults were more likely to engage in excuse validation. OPEN RESEARCH BADGES: This article has been awarded Open Materials and Open Data badges. All materials and data are publicly accessible via the Open Science Framework at https://osf.io/8juyc/. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki .
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.
How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 teacher head, 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".