Tolerance for Law Violations and Social Projection among Offenders and Nonoffenders
Bibliographic record
Abstract
Using a social projection paradigm, the present study investigated offenders’ beliefs that “everyone breaks the law.” A modified Tolerance for Law Violations Scale (TLV) was completed by 103 male provincial prison inmates and 135 male nonoffenders. Participants subsequently estimated either the percentage of offenders or nonoffenders who would agree with their responses to each of the 10 items that compose the TLV. As predicted, offenders scored significantly higher on the TLV than nonoffenders, indicating that offenders are more likely to see law violations as acceptable behavior. In addition, offenders significantly overestimated the actual percentage of offenders and nonoffenders who would endorse criminal sentiments and behaviors; that is, offenders believed that criminal conduct was normative behavior for not only offenders but for nonoffenders as well. Implications of the findings are discussed in terms of social norms theory and social norms intervention within a prison setting.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".