RCMP Surrey Ride Along Study: General Findings
Bibliographic record
Abstract
Over the past thirty years, the public has increased their demands for police services which has contributed to RCMP detachments taking on additional responsibilities. At the same time, changes in policing technologies and Canadian case law have increased the number of steps and the amount of time it takes police to perform many of their routine activities. For many RCMP detachments, an increase in the number of members and other resources has not kept pace to the changes to the job of policing or the demands for police services. ... The purpose of this study was to quantify the typical shift of a general duty police officer in Surrey, British Columbia, how often general duty members perform specific activities, the amount of time it takes, on average, for members to perform their daily activities, and the proportion of time out of a typical full shift these routine activities consume. This current report is the first in a series of reports that will examine general duty officers. While this report will focus on the methodology of the study, an analysis of the main actions and activities that general duty officers engaged in, and the amount of time it takes, on average, to perform these activities, subsequent reports will focus, for example, on officer maintenance and health, general patrolling and police driving, and investigative activities.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".