Religion and the Acceptability of White‐Collar Crime: A Cross‐National Analysis
Bibliographic record
Abstract
This article examines whether shared religious beliefs and religious social relationships (Durkheim) and belief in a personal, moral God (Stark) negatively affect attitudes toward the acceptability of white‐collar crime. In addition, using a large cross‐national sample and estimating multilevel models, we test whether effects are conditional on modernization and religious contexts characterized by belief in an impersonal or amoral God. Shared religious beliefs and the importance of God in one's life are negatively related to the acceptability of white‐collar crime. These effects, however, weaken in religious contexts characterized by belief in an impersonal or amoral God as do the effects of religious social relationships and belonging to a religious organization; modernization, on the other hand, does not have a moderating effect. In short, religious belief is associated with lower acceptance of white‐collar crime and certain types of religious contexts condition this relationship.
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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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".