A study of factors impacting Ontario police participation in higher education
Bibliographic record
Abstract
This thesis presents the results and discusses the implications of research undertaken in the province of Ontario, Canada, to determine factors impacting police participation in higher education. The study involved 1150 respondents working in 20 different police services in Ontario. Drawing on previous studies relating to adult education theory, key personal and professional characteristic factors of the adult leaner involved in educational environments were examined. The study also examined six common clusters of factors identified as financial, convenience, social support, institutional culture, goal congruence and job relevance, that provided information on why police attain, do not attain, or are unable to attain higher education goals. Results from the personal and professional factors show 88% of respondents had already earned a college/university degree, or were in the process of completing one. Other findings suggest 82% of respondents plan to stay in policing until retirement, 94% were not seeking new careers and 86% reported no secondary employment activities. Results from the examination of the six common clusters of factors to measure the existence of potential barriers and motivations that influence police decisions to participate in higher education were: (1) Financial: lack of government assistance, lack of incentive pay, the high costs of education and the availability of personal finances were considered major barriers; (2) Convenience: shift work and personal time constraints were major barriers. The offering of a flexible distance education program was considered a motivator; (3) Social support: support from co-workers, family and meeting new people were considered major motivators; (4) Institutional culture: perceived non support by management was a barrier to civilian, constables and supervisors. Senior officers felt supported. Having opinions valued by students and faculty and attending university was considered a major motivator; (5) Goal congruence: motivators for attending universities were to improve the mind, learn new knowledge, improve/fulfill academic abilities and promote the profession; (6) Job relevance: motivators include: learning about law enforcement from an educational perspective, develop career and leadership skills and agreement that both formal education and police training is needed in policing.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".