Marketization, Knowledge Work and Visibility in 'Users Pay' Policing in Canada
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
This article explores central themes in policing and security scholarship by examining a ‘users pay’ form of police moonlighting in Ontario called ‘pay duty’. Drawing on interviews with police personnel and service users, as well as analysis of ‘pay duty’ data and policies from four municipal police services, we raise questions about this form of policing in relation to police marketization, knowledge work and visibility. Our analysis of pay duty casts doubt on assumptions about the pervasiveness of police marketization and knowledge work. We also explore dimensions of police visibility overlooked in existing literature and make connections to issues of legitimacy. We demonstrate how police marketization, work type and visibility represent a key conceptual trifecta useful in examining this pervasive form of police moonlighting, and in policing and security studies more broadly.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it