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Record W2905067186 · doi:10.1108/mhsi-10-2018-0036

The ghettoization of persons with severe mental illnesses

2018· article· en· W2905067186 on OpenAlexaffabout
Janet Laura Stewart

Bibliographic record

VenueMental Health and Social Inclusion · 2018
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMental healthOriginalityMental illnessCommunity integrationPsychologyStigma (botany)Peer supportValue (mathematics)Social exclusionPsychiatryMedicineSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to outline the reflections of a person with lived experience of a severe mental illness (SMI) and former peer support worker in Montreal, Quebec, Canada, who has also worked for seven years in mental health research. It describes a tendency of resources and services to create ghettos of people with SMIs by failing to support the integration of people with SMIs into the community at large or in exploring options for meaningful, fulfilling occupation, reinforcing social exclusion and ghettoization. Design/methodology/approach This paper shows a reflective and narrative account of personal experiences and observations of the ghettoizing tendency in mental health services. Findings Mental healthcare professionals tend to support people with SMIs in engaging activities within resources for the mentally ill, and not in carrying out activities in the community at large. The range of activities offered is limited, an obstacle to finding meaningful, fulfilling occupation. Harmful psychological effects include self-stigma, low self-esteem and a sense of marginalization, generating a ghettoized mentality. The difficulties encountered in an effort to leave the mental health ghetto are touched on with examples of how to overcome them. Practical implications The need for professional support for social integration of people with SMIs is identified, which could ultimately favor social inclusion of people with SMIs. Originality/value It is written from the perspective of a user and provider of mental health services, who also has seven years’ experience in mental health research.

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 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 score0.673
Threshold uncertainty score0.986

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 studies0.0150.000
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 head0.058
GPT teacher head0.473
Teacher spread0.415 · 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.

Study designNot applicable
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

Citations12
Published2018
Admission routes2
Has abstractyes

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