Examining Alignment Between Canadian Municipal Police Performance Evaluation Policies and Officer Perceptions
Bibliographic record
Abstract
A lack of alignment between police performance evaluation policy purposes and officer performance evaluation perceptions has implications for the organizations' resource management, officer morale, and public safety. A literature review points towards a gap existing between policy purpose statements and employee perceptions. The purpose of this study was to investigate the relationship between the policy purposes of police performance evaluations and the officers' perceptions of those evaluation experiences in 4 Ontario municipal police services. DiMaggio and Powell's (1983) Institutional theory was the foundation for this study. Data for this study were collected from 4 police services in Ontario, Canada. The data consisted of police performance evaluation policies and in-person interviews with 12 officers. Data were inductively coded, and then the coded data were subjected to content analysis. Three policy purpose themes and 13 officer perception themes emerged that indicate that: 1) there seems to be a lack of alignment between the policy purpose theme of assessing work performance and eight of the perception themes; 2) officers perceived performance evaluations as negatively impacting their morale: and, 3) healthy relationships with supervisors were more useful to officers than performance evaluations in terms of performance and career outcomes and progression. Consistent with Institutional theory, officers perceived performance evaluations to be necessary even with limited utility. The positive social change implications stemming from this study include recommendations to police executives to consider alternative processes in tandem with performance evaluations to improve morale, in turn creating better opportunities for improved public and officer safety.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".