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O Comitê Cidadão como estratégia cogestiva em uma pesquisa participativa no campo da saúde mental

2013· article· pt· W2115093312 on OpenAlexaffabout
Eduardo Passos, Thais Mikie de Carvalho Otanari, Bruno Ferrari Emerich, Lorena Rodrigues Guerini

Bibliographic record

VenueCiência & Saúde Coletiva · 2013
Typearticle
Languagept
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesSociologyMedicinePhilosophy

Abstract

fetched live from OpenAlex

The theme of users' rights has become a central issue in contemporary debate on mental health. Drawing from the experiences of "Comitê Cidadão" (Citizen Committee), consisting of users and family members in an international research alliance between Brazil and Canada, an attempt is made to discuss the effects of the experience of co-management of the so-called Autonomous Medication Administration (GAM - Gestão Autônoma da Medicação) participatory research project on these individuals. By means of a detailed description of the background of the Committee and interviews and analysis of the voice transcriptions of its members, the problems raised by the relation of dialogue between scientific knowledge and users' knowledge are examined in a methodological approach of participatory research. As a result of the research, it was established that the experience of the Citizens Committee in co-management of health research can be propitious to the increase in the degree of autonomy, greater empowerment and the exercise of leadership and citizenship, with the consequent emergence of subjects with rights.

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)0.053
metaresearch head score (Gemma)0.043
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 score0.053
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.043
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0200.038
Scholarly communication0.0180.011
Open science0.0020.019
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.069
GPT teacher head0.375
Teacher spread0.306 · 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

Citations26
Published2013
Admission routes2
Has abstractyes

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