Why do people cooperate with the police and criminal courts? A test of procedural justice theory in 30 countries
Bibliographic record
Abstract
Abstract This article presents a cross‐national test of the portability of procedural justice theory (PJT). Drawing on nationally representative survey data from 30 diverse social, political, and legal contexts across Europe and beyond, we find that the theory travels well across national borders and that its psychological purchase is particularly pronounced in societies where fair policing is considered the norm. First, in most countries, a normative account of public cooperation with the police—grounded in procedural justice and legitimacy—has greater empirical traction than an instrumental account based on effectiveness and fear of crime. Second, although procedural justice consistently emerges as the strongest predictor of police legitimacy, it is especially important in contexts where the police are widely viewed as fair and inclusive authorities—a proxy for their status as a positive group authority. These findings help lay the groundwork for cross‐national extensions of PJT, pointing to the need for further research into the social and institutional conditions that shape its psychological impact.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".