Policing with a public health lens – Moving towards an understanding of crime as a public health issue
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
Policing organizations are currently experiencing more pressure than ever to address systemic racism and police brutality. Advocates and academics have suggested a range of changes, such as defunding the police, moving towards more body-worn cameras, ensuring higher educational levels of new recruits, implicit bias training, and so on. Our article draws attention and advocates for a different avenue: moving our understanding of crime towards a public health issue. By drawing on some data from the University of Alberta Prison Project, we argue that looking at justice clients with a public health lens would significantly change the way police are trained and respond to incidents. We believe this would have monumental consequences for both justice clients and policing organizations: justice clients will benefit from a police service that is trauma informed, compassionate, and understands their client base, while policing organizations will arguably increase their trust relationship with the public, therefore building legitimacy in the community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.000 | 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