A Program of Their Own: The Design and Evolution of an Undergraduate Degree Program for Police Officers in Ontario
Bibliographic record
Abstract
In the late 1990s and early 2000s, the Toronto Police Service was exploring how to increase access to higher education to its officers. The service saw higher education as salient to its organizational imperatives of professionalization, increased public legitimacy and credibility, and enhanced academic recognition of police professional learning. To realize this mission, the Toronto Police Service entered into a higher education partnership with the University of Guelph and Humber Institute of Technology and Advanced Learning under its then-new joint venture, the University of Guelph-Humber. The University of Guelph-Humber designed an accredited higher education pathway for Toronto Police personnel that also gave academic credit for past professional learning and increased educational access by offering blended course delivery. Based on semi-structured interviews with key educational administrators at the University of Guelph-Humber, Humber Institute of Technology and Advanced Learning, and the Toronto Police Service, this article narrates the origins of this higher education pathway—a Bachelor of Applied Arts in Justice Studies. In addition, it describes how this pathway evolved to include non-uniform Toronto police personnel, other police services, and expanded further to include learners from the larger justice and public safety fields. The exploration is situated in a larger discussion about the relationship between higher education, professionalization and legitimacy, and the potential of partnerships between higher educational institutions and professions in Canada.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".