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Record W3165404766 · doi:10.32748/revec.v6i17.15728

ESTRATÉGIA DE FAMÍLIA

2021· article· pt· W3165404766 on OpenAlexaff
Gabriel Chagas

Bibliographic record

VenueRevista de Estudos de Cultura · 2021
Typearticle
Languagept
FieldSocial Sciences
TopicGender, Sexuality, and Education
Canadian institutionsCascades (Canada)
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Abordar a relação das pesquisas médico-científicas com o comportamento da sociedade nunca foi tema mais atual. O presente artigo debruça sobre a influência que o discurso médico-científico exerceu sobre as decisões matrimoniais de um grupo familiar, os Ferreira da Fonseca/ Armond, em Minas Gerais, a partir de fins do século XIX, o que permite debater, na larga escala, o abandono da estratégia de casamentos consanguíneos em prol de casamentos extrafamiliares. Sob o impacto dos primeiros estudos de genética, a estratégia tinha a intenção de prevenir, ao longo das gerações, que seus membros herdassem doenças geneticamente potencializadas pelo casamento consanguíneo dosprogenitores. A relação entre sociedade e ciência em momento tão contemporâneo (2020) é um dos resultados da construção dessa relação ao longo de um século e meio e a mudança nas práticas sociais de casamento, resultantes dos enunciados emanados pelas pesquisas médico-científicas no campo da Genético, é campo preferencial para se analisar o lugar do discurso médico no engendramento dos comportamentos sociais, uma vez que as relações conjugais se situam na intimidade do lar e é necessário a introjeção individual desse discurso para que a sociedade modele coletivamente seu comportamento segundo as prescrições médico-científicos.Palavras-chave: Casamentos Consanguíneos. Genética. História da Medicina

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)0.004
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0070.010
Scholarly communication0.0060.003
Open science0.0010.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.002

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 head0.077
GPT teacher head0.373
Teacher spread0.296 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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