Understanding Public Attitudes towards the Police: Co-variates of Satisfaction, Trust, and Confidence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Prior research on public attitudes towards the police has tended to refer to three concepts—satisfaction with the police, confidence in the police, and trust in the police—entirely interchangeably. Recently, there has been a call to differentiate these three concepts. The current study seeks to address this research gap by analysing a unique Canadian dataset that includes all three concepts. The main research question that the study tries to answer is whether significant co-variates will differ in predicting the three concepts. The findings indicate that different models have slightly different demographic co-variates, but they share three of the same co-variates: dissatisfaction with prior citizen–police contacts, victimization, and neighbourhood conditions. The study suggests that while differentiating these three concepts may be promising, it is important, efficient, and practical to handle the three shared co-variates to improve overall public attitudes towards the police.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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 it