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Record W2050953811 · doi:10.1080/09581596.2015.1007923

Policing ‘Vancouver’s mental health crisis’: a critical discourse analysis

2015· article· en· W2050953811 on OpenAlexaffabout
Jade Boyd, Thomas Kerr

Bibliographic record

VenueCritical Public Health · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersNational Institute on Drug AbuseNational Institutes of Health
KeywordsMental healthMental illnessFraming (construction)Criminal justiceCriminologyCritical discourse analysisStigma (botany)Public healthPolitical scienceSociologyPsychologyPsychiatryMedicineGeographyLawNursingPolitics

Abstract

fetched live from OpenAlex

In Canada and other western nations there has been an unprecedented expansion of criminal justice systems and a well documented increase of contact between people with mental illness and the police. Canadian police, especially in Vancouver, British Columbia, have been increasingly at the forefront of discourse and regulation specific to mental health. Drawing on critical discourse analysis, this paper to explores this claim through a case study of four Vancouver Police Department (VPD) policy reports on "Vancouver's mental health crisis" from 2008-2013, which include recommendations for action. Analyzed is the VPD's role in framing issues of mental health in one urban space. This study is the first analysis to critically examine the VPD reports on mental health in Vancouver, B.C. The reports reproduce negative discourses about deinstitutionalization, mental illness and dangerousness that may contribute to further stigma and discrimination of persons with mental illness. Policing reports are widely drawn upon, thus critical analyses are particularly significant for policy makers and public health professionals in and outside of Canada.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.781

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.009
Science and technology studies0.0430.036
Scholarly communication0.0200.005
Open science0.0030.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.138
GPT teacher head0.481
Teacher spread0.343 · 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 source (direct Gemma or distilled Codex), 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

Citations51
Published2015
Admission routes2
Has abstractyes

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