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Record W4408082394 · doi:10.1016/j.ijlcj.2025.100731

Correctional officer recruits’ navigation of overwhelm: Internal and external strategies

2025· article· en· W4408082394 on OpenAlexafffundabout
Katy Konyk, Katherine Maurer, Rosemary Ricciardelli, Cheryl Regehr, Marjorie Rabiau

Bibliographic record

VenueInternational journal of law, crime and justice · 2025
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsCanada Research ChairsMemorial University of NewfoundlandMcGill University
FundersCanadian Institutes of Health ResearchFonds de Recherche du Québec-Société et Culture
KeywordsOfficerPsychologyAeronauticsPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Internationally, little is known of how correctional officer recruits (CORs), those beginning their careers as federal COs, navigate states of overwhelm (i.e., moments of acute stress) and whether their responses to overwhelm could be adaptive to the carceral environment. In this study, we analyze qualitative interviews with 27 Canadian CORs (18 male, 8 female) on navigating overwhelm to understand their preemployment strategies for responding to acute stress. Our grounded theory analysis reveals that CORs engage in both externally focused (i.e., stressor resolution) and internally focused (i.e., emotion regulation) coping strategies to navigate overwhelm. Additionally, CORs seek out relational support and identify how overwhelm can be an opportunity to grow and learn new strategies. We discuss how CORs’ reports of employing both problem-focused and emotion-focused coping strategies can shape how the organization supports CORs and COs in maintaining and developing new coping skills for overwhelm, specifically by creating conditions for regulatory flexibility and fostering strong relationships.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

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

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 head0.049
GPT teacher head0.439
Teacher spread0.390 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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 routes3
Has abstractyes

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