MétaCan
Menu
Back to cohort
Record W2312946907 · doi:10.7870/cjcmh-2004-0015

What can Community Support Programs Do to Promote Productivity?: Perspectives of Service Users

2004· article· en· W2312946907 on OpenAlexaffvenue
Rosa A. Raponi, Bonnie Kirsh

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2004
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProductivityEmpowermentService (business)Sample (material)Perspective (graphical)Qualitative researchKnowledge managementFocus groupPublic relationsBusinessMarketingPsychologySociologyPolitical scienceComputer scienceEconomic growth

Abstract

fetched live from OpenAlex

A major goal of community support programs is to help users of services lead meaningful, productive lives in the community. However, there is currently little evidence to support an understanding of how community support programs influence the productivity of service users, particularly from the perspective of consumers themselves. This qualitative study explored consumer perspectives on how community support programs promote productive activity. Data were obtained from in-depth interviews with a sample of 14 participants who received community support services, and analyzed using the constant comparative method involving unitizing, categorizing, and forming themes. The 4 themes that emerged from the data were: (a) the need for a specific focus on productivity within services, (b) the importance of consumer empowerment, (c) the need for learning opportunities, and (d) the value of supportive networks.

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)0.006
metaresearch head score (Gemma)0.015
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0100.006
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.212
GPT teacher head0.424
Teacher spread0.213 · 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

Citations5
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Community Mental HealthSame topicMental Health and Patient InvolvementFrench-language works237,207