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Record W1551548255

Etnografia institucional: conceito, usos e potencialidades em pesquisas no campo da Saúde (Institutional Ethnography: concept, uses and potentialities in health researches field)

2011· article· pt· W1551548255 on OpenAlexaboutno aff
Renata Meira Véras

Bibliographic record

VenueSaúde & Transformação Social / Health & Social Change · 2011
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsnot available
Fundersnot available
KeywordsConceptualizationEthnographySociologyField researchField (mathematics)HumanitiesPresentation (obstetrics)Power (physics)AnthropologyArtMedicinePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

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

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0130.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0010.000

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 head0.313
GPT teacher head0.447
Teacher spread0.134 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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