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Record W4300068257 · doi:10.17665/1676-4285.200535

Education and professional strengthening of the community health agent - an ethnography study

2005· article· en· W4300068257 on OpenAlexaff
Margareth Santos Zanchetta, Lígia Costa Leite, Michel Perreault, Hélène Lefebvre

Bibliographic record

VenueOnline Brazilian Journal of Nursing · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsUniversité de MontréalToronto Metropolitan University
Fundersnot available
KeywordsFacilitatorEthnographySociologyCollective identityPublic relationsIdentity (music)PoliticsPopulationParticipant observationHealth carePedagogyNursingSocial psychologyPsychologyMedicinePolitical scienceSocial scienceLawAesthetics

Abstract

fetched live from OpenAlex

This inquiry explored the educative actions of Community health agents (CHAs) with socially disaffiliated populations in a Rio de Janeiro metropolitan area. Individual and group interviews, participant observation during visits to the shantytowns, and picture gathering apprehended the philosophical and empirical dimensions of such actions. The software ATLAS ti. 4.2 supported the coding procedures of the raw material. Abduction in communication framed findings’ analysis and interpretation. Analysis revealed their social professional identity, political awareness regarding their own organization as a professional group, plus criticisms regarding the negligence of occupational safety and the lack of governmental help. CHAs “voice” is a tool of social leadership and a main facilitator to empower the population, and to promote optimization of the health care system. Since their professional practice revealed conflicts, contradictions and paradoxes, it seems necessary a collective reflection on the needed support to sustain CHAs wishes for change and freedom to act.

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, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.100
GPT teacher head0.505
Teacher spread0.404 · 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

Citations3
Published2005
Admission routes1
Has abstractyes

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