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Record W4391138257 · doi:10.3389/fpsyg.2024.1258944

“We must be mentally strong”: exploring barriers to mental health in correctional services

2024· article· en· W4391138257 on OpenAlexaff
Ryan Coulling, Matthew S. Johnston, Rosemary Ricciardelli

Bibliographic record

VenueFrontiers in Psychology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsMemorial University of NewfoundlandProvidence University College and Theological Seminary
Fundersnot available
KeywordsMental healthPsychologyStigma (botany)Work (physics)Public relationsMedical educationPsychiatryMedicinePolitical science

Abstract

fetched live from OpenAlex

Introduction: The inherent nature of work in correctional services can have negative effects on correctional worker mental health and well-being. Methods: = 192). Specifically, participants were asked at the end of an extensive mental health and well-being survey an open-ended question requesting any additional feedback or information. Results: Four predominant themes were identified in the data: (1) stigma pertaining to a need to recognize mental health concerns within correctional services; (2) the idea that correctional services wear on the mind and body; (3) a need for better relationships with and support from correctional supervisors, upper management, and ministerial leadership; and (4) suggestions to improve correctional services to help the sector realize its full potential and maximize workplace health. Discussion: We discuss the implications of these findings, with an emphasis on finding ways to promote positive organizational and cultural change in correctional services.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.041
GPT teacher head0.376
Teacher spread0.334 · 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 designQualitative
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

Citations21
Published2024
Admission routes1
Has abstractyes

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