“We're not worth it”: Canadian parole officers' self-worth contingencies — a valuation for job fitness?
Bibliographic record
Abstract
In this article, we explore the social environment of Canadian federal parole officers (POs) through a study on seven self-worth contingencies (i.e., recognition, images, comparisons, ideology, kinship, competence, and virtue) adopted for public safety contexts. We qualitatively investigate 28 POs' perceptions, taking a semi-grounded constructivist approach to interview data, and learn how parole officers experience esteem at work. We demonstrate how participants come to recognize themselves through comparisons with other public safety roles, and we situate our findings within the broader literature on probation/parole officer mental health. Using self-determination and introjection theory as our conceptual framework, we identify a paradox. We observe that POs who seek esteem by comparing themselves to others and use techniques to project self-worth likely experience greater distress. In contrast, we surmise those whose self-worth is rooted in authenticity, reflected through abstracted self-construal and an internalized locus of controlexperience greater well-being. Limitations to our study's findings and the implications for future research are offered while theorizing how human resources may be improved in correctional work.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".