What One Might Expect: A Scoping Review of the Canadian Policing Research Literature
Bibliographic record
Abstract
Using the medium of a scoping review, the author provides an analysis of the Canadian policing research literature published over the past ten years (2006-2015). What this analysis reveals is both expected and unexpected. In line with public views expressed by a number of sources (academics, policy-makers and police), the overall volume of literature produced during this period was low (some 188 (n=188) papers were identified). However, in contrast to the belief expressed by some that the Canadian policing literature is overly theoretical and largely qualitative, the bulk of studies examined (n=123) were quantitative, and eighteen (n=18) were experimental or quasi- experimental in design. Of more critical import, however, is the issue of overall production and lack of coverage of key policing topics. Gaps in topic coverage are explored here, with some key recommendations offered for improving Canadian output.
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.
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 | 0.045 | 0.138 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.036 | 0.057 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".