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Record W1566633670 · doi:10.1080/02650533.2015.1050654

Police Encounters in Child and Youth Mental Health: Could Stigma Informed Crisis Intervention Training (CIT) for Parents Help?

2015· article· en· W1566633670 on OpenAlexaboutno aff
Maria Liegghio, Prableen Jaswal

Bibliographic record

VenueJournal of Social Work Practice · 2015
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsnot available
FundersMental Health Commission
KeywordsMental healthStigma (botany)PsychologySiblingIntervention (counseling)Focus groupMental illnessQualitative researchPsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

Recently in Canada the issue of police encounters among persons living with a mental health issue has received considerable public attention; however, the focus has been primarily on the experiences of adults and not of children and youth. In this paper, we explore police encounters in child and youth mental health by presenting the outcomes of 14 qualitative interviews conducted with seven caregivers and seven siblings and two focus groups conducted with eight caregivers about their experiences of having a child/sibling, 13–21 years old, living with a mental health issue. There were two main themes identified: (1) the need for police support to deescalate a high conflict situation involving a distressed child/sibling, and (2) the stigmatisation and criminalisation of the distressed child, parents and families. Based on these outcomes, a model of support is proposed whereby parents would be provided with crisis intervention training informed by an understanding of the stigma of mental illness as a structural condition of their personal experiences. Such training could provide caregivers with support for identifying and responding to crisis and for developing safety plans that may or may not involve police, but could minimise and/or divert the need for their involvement.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.095
GPT teacher head0.410
Teacher spread0.315 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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