Effort-Reward Imbalance, Overcommitment, and Psychological Distress in Canadian Police Officers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of the present study was to examine the relationship among Effort, Reward, and Overcommitment dimensions of Siegrist's Effort-Reward Imbalance Model and Psychological Distress in a sample of 78 Canadian police officers. Ages of respondents ranged between 24 and 56 years (M=36.1, SD=8.0). 30% of respondents had been in policing for 16 years or more, 24% between 6 and 15 years, and 44% for 5 years or less. Ordinary least-squares regression was used to evaluate the relationship between the independent and dependent variables. After adjusting for age, sex, education, and marital status, higher levels of Effort-Reward Imbalance and Overcommitment were associated with greater Psychological Distress. Present findings support the utility of the model in this particular occupational group and add to the increasing literature suggesting association of Effort-Reward Imbalance, Overcommitment, and reduced mental health.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it