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Hellenistic Poetry in Translation by Brazilian Women: A Yet Untrodden Path

2025· article· W4416796337 on OpenAlexaff
Flavia Vasconcellos Amaral

Bibliographic record

VenueCadernos de Literatura em Tradução · 2025
Typearticle
Language
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsPath (computing)PoetryTranslation (biology)

Abstract

fetched live from OpenAlex

Embora os estudos de poesia helenística tenham crescido no país desde o começo do século, seguindo tendências globais de crescimento e interesse em determinados temas de pesquisa, ainda são poucas as traduções publicadas em livro e a grande maioria delas é feita por pesquisadores homens. Pesquisa bibliográfica usando bases de dados de dissertações e teses mostra que há mais traduções de pesquisadoras mulheres no âmbito da produção acadêmica e elas tendem a integrar seus trabalhos de mestrado e doutorado. Entretanto, esses trabalhos raramente se tornam livros publicados, permanecendo inertes nos repositórios de acesso livre de universidades. Dessa maneira, os objetivos deste artigo são descrever e analisar a disparidade de gênero encontrada nas traduções de poesia helenística publicadas em formato de livro e propor ações para diminuir a assimetria de gênero na tradução de textos clássicos.

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)0.008
metaresearch head score (Gemma)0.019
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: none
Teacher disagreement score0.024
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0110.028
Scholarly communication0.0080.006
Open science0.0010.005
Research integrity0.0020.002
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 head0.013
GPT teacher head0.290
Teacher spread0.277 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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