A Study of Psychological Well-Being among Police Personnel
Bibliographic record
Abstract
This study explores psychosocial well-being among male and female police personnel. Empathy and forgiveness are explored as correlates of psychological well-being. Gender and rank differences on all three variables are also assessed. Personnel in age range of 30 to 45 years, having experience of minimum three years in dealing directly with citizens were selected from Jalandhar range of Punjab police, belonging to Assistant Sub Inspector {ASI} and Sub Inspector {SI} ranks. Respondents were administered Ryff’s psychological well-being scale (Ryff& Keyes, 1995), Heartland Forgiveness Scale (Thompson, Snyder & Hoffman, 2005) and Toronto Empathy Questionnaire (Spreng, McKinnon, Mar & Levine, 2009). Descriptive statistics (mean and S.D.), correlation analysis, t-test and 2x2 ANOVA was applied. Results revealed that empathy positively correlate with psychological well-being among police personnel and significant gender differences exist on forgiveness while significant rank differences exist on empathy and psychological well-being.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".