Community into Intelligence: Resolving Information uptake in the RCMP
Bibliographic record
Abstract
Police now and then undergo radical mission adaptation. Yet, how events shape organizational police history, including the adoption of radically different missions, has largely evaded scholarship. Through a review of executive-level interviews and strategic leadership documents, we trace how the Royal Canadian Mounted Police turned from a community-policing mission to one which now highlights intelligence. We argue that while various programs and strategies to garner rank-and-file and public buy-in to the community-policing mission largely failed, problem-oriented policing nevertheless readied the ground for the next mission iteration: intelligence-led policing. The core problem underpinning the transition was not community service, but information uptake.
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 | 0.040 | 0.171 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.036 | 0.034 |
| Scholarly communication | 0.025 | 0.027 |
| Open science | 0.005 | 0.022 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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".