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PELE NEGRA/VERMELHA, MÁSCARAS BRANCAS: CONTRIBUIÇÕES À DESCOLONIZAÇÃO DAS TEORIAS DO RECONHECIMENTO

2020· article· pt· W3111160501 on OpenAlexfundno aff
Marcos de Jesus Oliveira

Bibliographic record

VenueRevista Direitos Humanos e Democracia · 2020
Typearticle
Languagept
FieldSocial Sciences
TopicUrban Development and Societal Issues
Canadian institutionsnot available
FundersUniversity of CambridgeUniversity of TorontoUniversity of OxfordUniversity of MinnesotaPrinceton University
KeywordsHumanitiesPhilosophySociology

Abstract

fetched live from OpenAlex

O objetivo do presente trabalho é apresentar alguns dos limites das teorias do reconhecimento quando pensadas desde a perspectiva pós-colonial e em contextos não-europeus. No percalço deste objetivo, dividiu-se o texto em quatro partes, iniciando-o com uma breve exposição da problemática para, em seguida, discutir a proposta de Frantz Fanon como uma das mais paradigmáticas e influentes nos estudos pós-coloniais. Feito isso, passo à contribuição de Glean Sean Coulthard com o intuito de aprofundar alguns dos problemas das correntes hegemônicas sobre o reconhecimento. Ao final, discutem-se os desafios colocados pelas teorias pós-coloniais às teorias do reconhecimento na superação do “déficit colonial” das tendências hegemônicas.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.015
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.062
GPT teacher head0.336
Teacher spread0.273 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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