“You have to be really careful, in this environment, of what you say and what you do”: A qualitative examination of how organizational culture shapes parole officers' work and well-being
Bibliographic record
Abstract
Drawing on existing literature on organizational culture in correctional work, in the current article we augment scholarship on community correctional services, specifically parole work, by considering how organizational culture, as narrated by frontline parole officers, impacts parole officers” feelings toward their work and their own health and well-being. Using the insights gained from 150 qualitative interviews with parole officers across Canada, we empirically show how participants described organizational culture as (1) imbued with social networks and hierarchies and (2) inherently reactive. We then provide insight into their perceived relationships with management. Participants explained they largely felt uncomfortable voicing concerns or making suggestions for improvements, in addition to feeling their work did not receive the respect and appreciation it deserved. We draw attention to the implications of perceptions on parole officers' feelings toward their job and sense of self, as well as the potential impact of organizational culture on parole officers' feelings of safety and emotional well-being on the job.
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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 | 0.006 | 0.012 |
| 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 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".