Validating the Police Legitimacy Scale with a Canadian Sample
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
For years, scholars and law enforcement agencies have been interested in examining the public’s perceptions of police legitimacy. However, previous studies have operationalized “police legitimacy” in a wide variety of ways. In an attempt to standardize this construct, Tankebe, Reisig, and Wang (2016) recently developed and validated the Police Legitimacy Scale using samples from the United States and Ghana. To determine the validity of this scale in a Canadian context, we had 2,962 Canadian community members complete a demographics survey as well as Tankebe et al.’s (2016) Police Legitimacy Scale. Descriptive statistics suggest the majority of responses to the scale do not differ across demographic factors, such as gender or race. Results from a confirmatory factor analysis indicate the previously proposed four-factor model of police legitimacy (lawfulness, procedural fairness, distributive fairness, and effectiveness) strongly fits participants’ responses.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 it