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Record W4391018336 · doi:10.4000/artelogie.12829

Confluências literárias na obra de Gerd Bornheim

2023· article· pt· W4391018336 on OpenAlexaff
Gaspar Paz

Bibliographic record

VenueArtelogie · 2023
Typearticle
Languagept
FieldArts and Humanities
TopicPhilosophy and Historical Thought
Canadian institutionsCanadian Heritage
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Estudo sobre as contribuições do filósofo brasileiro Gerd Bornheim (1929-2002) para a abertura, ampliação e consolidação de temas estético-filosóficos no Brasil a partir das convergências literárias presentes em sua obra. A literatura foi importante para Bornheim nas incursões pelo sentido da língua e da pulsação rítmica dos arranjos simbólicos. Além da leitura de mundo e do aprendizado das coisas pela palavra – ora ficcionalizando-as, ora expondo a carnadura real –, a literatura marcou a trajetória do autor como modo de disseminar um insopitável espírito crítico, cuja verve moldou sua ensaística. Nesse sentido, localizamos ao menos seis pontos de confluências literárias em seus trabalhos: 1. A aproximação entre poetas-pensadores e filósofos-poetas; 2. O convívio, a interlocução e a influência direta de escritores brasileiros em suas pesquisas; 3. A forma como a literatura se faz presente em seus escritos; 4. Escritos performativos entre a cena e o texto: literatura e teatro; 5. As tensões políticas vivenciadas por Bornheim nos anos 60 e 70 (na ditadura civil-militar no Brasil) e o modo como as perspectivas estético-político-literárias ganham corpo na correspondência do autor, em textos esparsos e em entrevistas concedidas à mídia e a revistas acadêmicas; 6. A tradução como forma de pensamento e tomada de posição: a linguagem dinâmica e participativa e o fluxo da língua viva.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.770

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0070.006
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.142
GPT teacher head0.296
Teacher spread0.153 · 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 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
Published2023
Admission routes1
Has abstractyes

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