Trust in the police and underreporting of crimes in Brazil
Bibliographic record
Abstract
This study investigates how individuals’ trust in police forces relates to the probability of filing a police report after experiencing a residential theft in Brazil, focusing on the State Military Police and the State Investigative Police. The analysis uses microdata from the fourth quarter of the 2021 Continuous National Household Sample Survey and estimates this association using a Probit model. The results indicate that declaring trust or high trust in the State Investigative Police or the State Military Police is associated with a higher likelihood of reporting the offense. Individuals who express trust in these institutions are more willing to inform the authorities about the theft, suggesting that positive perceptions of police performance influence reporting behavior. The study may contribute to the understanding of underreporting by using recent victimization data that include direct measures of institutional trust, expanding knowledge about the factors that shape the decision to report property crimes in Brazil and highlighting the relevance of perceptions regarding police credibility.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".