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Record W1152434731 · doi:10.3233/wor-141843

How is unemployment among people with mental illness conceptualized within social policy? A case study of the Ontario Disability Support Program

2015· article· en· W1152434731 on OpenAlexafffundabout
Rebecca Gewurtz, Cheryl Cott, Brian Rush, Bonnie Kirsh

Bibliographic record

VenueWork · 2015
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsCentre for Addiction and Mental HealthUniversity of TorontoMcMaster University
FundersCanadian Occupational Therapy Foundation
KeywordsMental illnessUnemploymentSocial exclusionGovernment (linguistics)Psychological interventionSupported employmentSocial supportSocial policyPublic policyInequalityPsychologyMental healthSocial psychologyEconomic growthPsychiatryPolitical scienceEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Government policy shapes and is shaped by society's views of important social issues such as employment among people with disabilities. OBJECTIVE: This article explores how unemployment among people with mental illness has been understood and characterized within social policy. METHODS: Drawing on a qualitative case study that explored the construction and implementation of policy reform within the employment support branch of the Ontario Disability Support Program, this paper examines assumptions about unemployment among people with mental illness that underlie social policy and their impact on employment services and supports. RESULTS: The most prominent messages that emerged from the data focused on unemployment among people with mental illness as a function of personal responsibility, limitations and a lack of motivation. Although there was awareness of the role of social and systemic factors, these issues were given less weight, especially when describing employment support practices. There is a lack of sufficient attention to complex and deeply-rooted social and systemic inequalities within social policy and employment services. CONCLUSIONS: There is a need to expand conceptualizations of unemployment among people with mental illness within social policy, and develop interventions that address complex social factors and systemic constraints that can limit employment opportunities.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.901

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 studies0.0000.000
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 head0.043
GPT teacher head0.335
Teacher spread0.292 · 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 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

Citations17
Published2015
Admission routes3
Has abstractyes

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