Delineating policing towards a social and health profession
Bibliographic record
Abstract
This article suggests potential reforms required to address shortcomings of the policing profession in response to contemporary challenges. Police reforms that de-emphasize enforcement and promote policing as a helping profession are discussed. This stance is presented because police calls for service commonly involve complex human behaviour that includes mental health factors (including addictions) and diversity. Police officers require extensive training and education on mental health and diversity, which should include regular specialized training advancements in professionalism, interpersonal skills, and behavioural (non-verbal and verbal) response. All police officers have to deal with mental health and diversity, and, as such, an appropriate helping model (that adopts certain skills from health and social professions) should be incorporated into law enforcement practices and training. The Compass Police Response (CPR) Model is presented for consideration in police reform as well as a revised representation of the Police Use of Force Framework. The authors posit that policing should include increased collaboration with health and social professions. The support of other community disciplines and health systems is necessary to adequately address reforms required in the policing profession.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.012 | 0.021 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".