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Record W7014595875

Poesia ao vivo: algumas implicações polÃticas e estéticas da cena literária nas quebradas de São Paulo

2016· article· pt· W7014595875 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scientific Electronic Library Online (Fundação de Amparo à Pesquisa do Estado de São Paulo) · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicUrban and sociocultural dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Subject (documents)Quality (philosophy)Order (exchange)Metropolitan areaQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

resumo Este artigo é resultado da observação recente da cena literária dos saraus e slams de poesia na cidade de São Paulo. Organizados e frequentados especialmente por jovens de classes economicamente menos privilegiadas de regiões pobres e periféricas da cidade, saraus literários e slams de poesia sugerem interessantes questões de natureza política, ética e estética. Defendo que esses eventos em que predomina a performance de poesia são potencialmente revolucionários não apenas pelas mensagens de contestação e ameaça que muitos textos, flagrantemente inspirados pela cultura hip-hop, veiculam, mas, sobretudo, pelo modo como eles são apresentados e pela rede de sociabilidade "marginal" que eles ajudam a estabelecer. Atrelados ao movimento maior de fortalecimento das vozes subalternas na sociedade brasileira, slams e saraus têm contribuído para a construção de discursos contra-hegemônicos que potencialmente desestabilizam representações sociais cristalizadas. Ao mesmo tempo, desafiam noções amplamente aceitas sobre o que é literatura, como ela é produzida e difundida.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0050.004
Scholarly communication0.0050.004
Open science0.0060.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.292
Teacher spread0.270 · 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
Published2016
Admission routes1
Has abstractyes

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