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Record W2325693685 · doi:10.7870/cjcmh-2004-0006

Bridging the Gap Between Dreams and Realities Related to Employment and Mental Health: Implications for Policy and Practice

2004· article· en· W2325693685 on OpenAlexaffvenueabout
Purnima Sundar, Joanna Ochocka

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2004
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsCentre for Community Based ResearchWilfrid Laurier University
Fundersnot available
KeywordsMental healthMental illnessBridging (networking)PsychologyAction (physics)Participatory action researchCitizen journalismBridge (graph theory)Work (physics)Public relationsService providerNursingBusinessPsychiatryPolitical scienceService (business)MedicineEconomic growthEngineeringMarketingEconomics

Abstract

fetched live from OpenAlex

Access to valued resources, especially to employment and income, is a critical issue in community mental health. Appropriate public policy and services are needed to bridge the gap between dreams and realities related to employment for people with a serious mental health illness. This article reviews current literature in the area of employment and mental health, and describes the findings of a research study focusing on these issues in one community in Southern Ontario. This study used a participatory, action-oriented approach to understand the ideal employment situation for people with a serious mental health illness, and to explore the barriers preventing them from finding, getting, and keeping work. Concrete areas for action (generated by people with a serious mental health illness working with service providers in this field) are suggested in order to respond to employment barriers at various levels and to make employment a reality for people experiencing a serious mental health illness.

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)0.046
metaresearch head score (Gemma)0.071
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.071
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0200.050
Scholarly communication0.0200.020
Open science0.0050.020
Research integrity0.0130.012
Insufficient payload (model declined to judge)0.0110.001

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 head0.303
GPT teacher head0.496
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 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

Citations7
Published2004
Admission routes3
Has abstractyes

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