The Redesign of Advanced Patrol Training for Police Constables in Ontario: Making Use of Evaluation to Maximize Organizational Effectiveness and Efficiency
Bibliographic record
Abstract
Abstract: The use of evaluation to maximize the effectiveness and efficiency of the Ontario Police College in the delivery of a refresher training program for police officers is described. Confronted by a growing backlog of patrol officers requiring refresher training and ongoing financial constraints, in 1997 the College, in co-operation with Ontario police services, initiated a comprehensive refresher training needs analysis. A multi-stage, multi-method strategy was employed in the research. The results of the needs analysis were used to redesign the curriculum, format, and delivery of the Advanced Patrol Training (APT) refresher course for patrol constables. As a result of the APT redesign, the number of police officers receiving refresher training increased by an average of 657% annually (effectiveness), while costs associated with the APT course decreased by 50% (efficiency). The evaluation, design, and delivery of the APT course has become a model for other police training programs in Ontario.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".