Etnografia institucional: conceito, usos e potencialidades em pesquisas no campo da Saúde (Institutional Ethnography: concept, uses and potentialities in health researches field)
Bibliographic record
Abstract
A Etnografia Institucional (EI), desenvolvida pela Canadense Dorothy Smith, vem sendo utilizada para pesquisas no campo da saude, enfatizando a analise das relacoes de poder que conformam as praticas cotidianas em instituicoes de saude. Esse artigo teve como objetivo apresentar essa metodologia, relativamente nova no Brasil, atraves de dois desdobramentos: a conceitualizacao da EI, suas formas de aplicacao e utilizacao nas pesquisas em instituicoes de saude; e a apresentacao dos aspectos metodologicos de uma pesquisa baseada na EI realizada no Programa Canguru da Cidade de Natal, RN. ABSTRACT – The Institutional Ethnography (IE), developed by the Canadian Dorothy Smith, has been used in researchers of health fields, emphasizing the analysis of power relations that regulate the everyday practices in health institutions. This article aimed to present this methodology, relatively new in Brazil, through two steps: the IE conceptualization, its application in the institutional health researches, and the presentation of methodology aspects of a research based on IE developed in Kangaroo Program in the Natal City, RN. Keywords: Anthropology, Cultural; Power Relations; Health Facilities
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".