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Record W2181945492 · doi:10.26443/mjm.v4i1.675

Public Attitudes Regarding the Community Canadian Mental Health Association Crisis Stabilization Unit in Swan River, Manitoba

2020· article· en· W2181945492 on OpenAlexafffundvenueabout
Ivan L. Rapchuk

Bibliographic record

VenueMcGill Journal of Medicine · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Manitoba
FundersCanadian Mental Health AssociationUniversity of Manitoba
KeywordsResidenceMental healthUnit (ring theory)Mentally illMedicineMental illnessPopulationAssociation (psychology)PsychiatryGerontologyEnvironmental healthPsychologyDemographySociology

Abstract

fetched live from OpenAlex

A door-to-door survey was conducted on households within a one square block of a Canadian Mental Health Association Crisis Stabilization Unit (Swan River, Manitoba, Canada). This was undertaken to examine the opinions and attitudes of the members of the surveyed households regarding the neighboring community mental health residence, as well as their general attitudes toward mentally ill individuals. The survey utilized preliminary questions to obtain personal characteristics of the respondents, which were followed by 11 short questions regarding attitudes towards mental illness and the neighborhood facility. The findings of this study agree with previous research suggesting a general receptiveness on the part of community residents to deinstitutionalization and to having community mental health residents as neighbors. The personal characteristic with the greatest positive influence on attitudes was previous personal contact with mentally ill individuals. However, it was found that a segment of the population holds negative attitudes towards the CSU. The author suggests that education of the community regarding the mental health facility and mentally ill persons may improve acceptance to a greater extent.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.226
GPT teacher head0.419
Teacher spread0.193 · 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 designObservational
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

Citations1
Published2020
Admission routes4
Has abstractyes

Explore more

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