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Record W4416183040 · doi:10.55905/revconv.18n.11-134

Mulheres negras 60+: histórias de vida na velhice

2025· article· W4416183040 on OpenAlexaboutno aff
Denise Ferreira da Costa, Leides Barroso Azevedo Moura

Bibliographic record

VenueContribuciones a las Ciencias Sociales · 2025
Typearticle
Language
FieldSocial Sciences
TopicRace, Identity, and Education in Brazil
Canadian institutionsnot available
Fundersnot available
KeywordsBlack womenRacismPaid workQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

Este artigo discute a velhice de mulheres negras brasileiras, entendendo-a como um fenômeno biopsicossocial e destacando dimensões históricas, culturais e políticas do racismo estrutural que historicamente vitima essas mulheres. A fundamentação teórica apoia-se, entre outras(os), em bell hooks, Lélia Gonzalez e Sueli Carneiro. O objetivo é analisar as histórias de vida narradas por mulheres negras 60+, a partir de uma abordagem interseccional entre experiências de racismo, machismo, questões de gênero e idadismo, conferindo visibilidade a processos históricos, culturais e ideológicos assentados no racismo brasileiro e seus desdobramentos para a velhice. A metodologia é qualitativa, com análise narrativa de histórias de vida, em diálogo com a Escrevivência de Conceição Evaristo e com os estudos de Ecléa Bosi sobre memória e velhice. Conclui-se que o racismo no Brasil incide de modo particularmente perverso na vida das mulheres negras, agravando danos à saúde mental na velhice. Ainda assim, mesmo diante das iniquidades, mulheres negras brasileiras 60+ exercem protagonismo, lideram suas famílias e constroem processos de resistência antirracista, afirmando a defesa da emancipação e da liberdade.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0120.006
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.038
GPT teacher head0.345
Teacher spread0.307 · 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 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
Published2025
Admission routes1
Has abstractyes

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