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Record W2967913758 · doi:10.9771/cgd.v5i1.31930

Ser Pardo: o limbo identitário-racial brasileiro e a reivindicação da identidade

2019· article· pt· W2967913758 on OpenAlexaff
Lauro Gomes

Bibliographic record

VenueCadernos de Gênero e Diversidade · 2019
Typearticle
Languagept
FieldSocial Sciences
TopicRace, Identity, and Education in Brazil
Canadian institutionsWSP (Canada)
Fundersnot available
KeywordsHumanitiesSociologyPhilosophy

Abstract

fetched live from OpenAlex

Este artigo busca apontar a necessidade de pensar-se o racismo por meio da perspectiva dos produtos da miscigenação brasileira: os pardos, já que o embranquecimento foi, no Brasil, uma estratégia de genocídio da população negra e indígena. Por isso, o texto é uma confluência entre teorias sobre a miscigenação e a narrativa do autor, visando construir um corpo de denúncia ao limbo identitário-racial por intermédio do entendimento sobre o surgimento do sujeito pardo e de sua situação. Nesse sentido, o artigo é divido em quatro partes. A primeira trata da criação do limbo onde a historicidade da miscigenação brasileira é evocada. A próxima seção, “O limbo e suas características” demonstra as características da situação do pardo no Brasile como ela é descrita socialmente; a terceira, “A saída do limbo”, pretende refletir sobre a necessidade (ou não) da autodefinição (e reinvindicação) racial do pardo, como negro, e as maneiras possíveis para fazê-lo. A quarta e última seção apresenta as considerações finais e perspectivas para novas produções sobre o tema.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.088
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0140.025
Scholarly communication0.0090.005
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.036
GPT teacher head0.331
Teacher spread0.295 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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