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Record W4410180017 · doi:10.1016/j.ssaho.2025.101532

“We're not worth it”: Canadian parole officers' self-worth contingencies — a valuation for job fitness?

2025· article· en· W4410180017 on OpenAlexaffabout
Micheal Taylor, Rosemary Ricciardelli

Bibliographic record

VenueSocial Sciences & Humanities Open · 2025
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsValuation (finance)Self worthPsychologySocial psychologyEconomicsActuarial scienceSociologyFinanceSelf-esteem

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0140.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.226
GPT teacher head0.465
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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