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Record W4318293200 · doi:10.1016/s2214-109x(23)00015-3

Equitable and sustainable funding for community-based organisations in global mental health

2023· article· en· W4318293200 on OpenAlexaff
June Larrieta, Milena Wuerth, May Aoun, Dörte Bemme, Nicole D’souza, Nyaradzayi Gumbonzvanda, Georgina Miguel Esponda, Tessa Roberts, Angi Yoder-Maina, Emilia Zamora, Onaiza Qureshi, Rita Giacaman

Bibliographic record

VenueThe Lancet Global Health · 2023
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsMcGill University
FundersEconomic and Social Research CouncilMedical Research CouncilKing's College London
KeywordsMental healthPublic relationsBusinessSustainable communityPolitical scienceEconomic growthSustainable developmentPsychologyEconomicsPsychiatry

Abstract

fetched live from OpenAlex

Community-based organisations working in mental health are essential for supporting wellbeing globally, particularly in areas where other services are scarce. Such organisations are uniquely attuned to local needs, challenges, and priorities, often established and led by members of a particular community themselves. Thus, community-based organisations provide culturally relevant services and programmes within familiar environments by trusted providers, whereby community participation is central to their implementation.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
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 head0.120
GPT teacher head0.473
Teacher spread0.353 · 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 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

Citations13
Published2023
Admission routes1
Has abstractyes

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