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Record W2984487846

Mental Illness Stigma Expressed by Police to Police.

2017· article· en· W2984487846 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsQueen's University
Fundersnot available
KeywordsStigma (botany)Mental illnessOfficerCronbach's alphaPsychologyScale (ratio)Psychological interventionMental healthPsychiatryExploratory factor analysisClinical psychologyMedicinePsychometrics
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: This paper describes mental health related stigma expressed by police to police using a newly developed 11-item Police Officer Stigma Scale and reports on the preliminary psychometric properties (factor structure and internal reliability) of this scale. METHOD: The scale used an indirect measurement approach adapted from the Perceived Devaluation and Discrimination Scale. Five themes appropriate to police culture were adapted and six additional items were added. Responses were rated on a 5-point agreement scale with an additional don't know option. Data were collected from officers attending a mandatory workshop (90.5% response). RESULTS: Exploratory factor analysis showed the scale to be unidimensional and internally reliable (Cronbach's alpha was 0.82). The most endorsed items pertained to avoiding disclosure to a supervisor/manager or to a colleague (85% agreement), that most officers would expect discrimination at work (62%), and that most officers would not want a supervisor or manager who had a mental illness (62%). CONCLUSIONS: Findings highlight that (a) Police-to-police mental illness stigma may be a particularly strong feature of police cultures; (b) police should be a focus for targeted anti-stigma interventions; and

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.

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 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: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.999

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 studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.067
GPT teacher head0.364
Teacher spread0.297 · 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