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Record W1554684794

Primary Health Care, Comprehensive Social Management and Participation

2014· article· en· W1554684794 on OpenAlexvenueno aff
Nelson Ardón Centeno, Andrés Felipe Cubillos Novella

Bibliographic record

VenueCross-cultural communication · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthOfficerMultidisciplinary approachPsychosocialPublic relationsCitizenshipHealth carePopulationNursingPolitical scienceMedicineSociologyPsychiatryEnvironmental healthLaw
DOInot available

Abstract

fetched live from OpenAlex

For many, the implementation of strategies of Primary Health Care (PHC) based on interdisciplinary approaches, constitutes a condition of possibility for undertaking mental health reform proposals for the Americas region. This view of the emphasis that makes the APS in social and state responsibility to uphold the rights of social citizenship, necessary to ensure the complex processes of reform. There are numerous experiences of implementing actions primary mental health care in Latin America, many linked with focused on community mental health programs. This paper makes an analysis of these successful experiences of implementing actions primary mental health care through community experiences that have determined that they are characterized: they had the presence of at least one mental health officer; was no explicit support from national and provincial authorities; was recognized as the focus of psychosocial problems geographic area and a population group; it had specific allocation of human and material resources; had managed to organize a multidisciplinary team; subsisted program where assisted community was well defined; there was a sense of identity and recognition had its problems and claim areas.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0040.002
Open science0.0010.011
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0520.005

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 head0.091
GPT teacher head0.520
Teacher spread0.429 · 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 designNot applicable
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

Citations0
Published2014
Admission routes1
Has abstractyes

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