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Record W1971495256 · doi:10.1007/s10464-008-9191-y

Putting Values into Practice: Public Policy and the Future of Mental Health Consumer‐run Organizations

2008· article· en· W1971495256 on OpenAlexaff
Geoffrey Nelson, Rich Janzen, John Trainor, Joanna Ochocka

Bibliographic record

VenueAmerican Journal of Community Psychology · 2008
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsCentre for Addiction and Mental HealthCentre for Community Based ResearchWilfrid Laurier University
Fundersnot available
KeywordsMental healthValue (mathematics)Health psychologyPublic relationsAction (physics)Participatory action researchConsumer AdvocacyPublic healthCitizen journalismHealth policySociologyPsychologyPolitical scienceMedicineNursingPsychiatryLaw

Abstract

fetched live from OpenAlex

The purpose of the paper is to reflect on value dilemmas in mental health consumer-run organizations and to discuss implications for research, policy, and practice. We review the roots of consumer-run organizations in the self-help movement and the psychiatric survivor liberation movement, focusing on the distinctive values espoused by consumer-run organizations. We also discuss evidence-based and value-based approaches to mental health policy formulation and mental health reform, noting the particular importance of value-based approaches and the role that consumer-run organizations can play in mental health reform. Based on our experiences conducting a participatory action research study of four mental health consumer-run organizations, we identify and examine several value dilemmas, discuss the lessons that we learned about these value dilemmas, and note their implications for future directions in research, policy, and practice.

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)0.075
metaresearch head score (Gemma)0.072
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 score0.075
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.072
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0240.086
Scholarly communication0.0350.026
Open science0.0030.016
Research integrity0.0270.019
Insufficient payload (model declined to judge)0.0060.000

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 head0.124
GPT teacher head0.496
Teacher spread0.372 · 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

Citations29
Published2008
Admission routes1
Has abstractyes

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