Using a means-end approach for understanding the struggle between police reform and abolition
Bibliographic record
Abstract
A seeming dichotomy of positions towards police reform within the literature exists. On one side, there is the position of evidence based policing and efficiencies within policing budgets and, on the other, police abolition, which seeks to dismantle dominant policing agendas. In this article, we use Ben-Moshe’s framework to situate the police reform within two operating categories; reformist and non-reformist ideologies, always exploring arguments of community groups and policing scholars towards police practices. Our objective is to reveal the dialectic relationship that shapes both ontologies through non-empirical research, each position toward police reform appearing to rely on the legitimacy derived from the other. We argue the two positions work towards a similar goal in the Canadian context, specifically to change the nature of policing toward being more inclusive, responsive, and proactive in contributing to public safety.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".