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Enseñar como lectoras: literaturas polifónicas para narrativas heterográficas

2023· article· en· W4390240561 on OpenAlexaff

Bibliographic record

VenueClepsydra Revista de Estudios de Género y Teoría Feminista · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLiteracy and Educational Practices
Canadian institutionsArthritis Research Centre of Canada
Fundersnot available
KeywordsPolyphonyPoliticsDimension (graph theory)ChorusSociologyMeaning (existential)AestheticsEpistemologyLiteraturePolitical sciencePedagogyArtPhilosophyLaw

Abstract

fetched live from OpenAlex

Gender studies are an indisputable contribution to pedagogy and epistemology-oriented innovation. In this regard, the meaning conferred to the concept of innovation is gradually defined. To innovate is to retake, with a transforming will, the best of the legacy and to dismiss the outdated, it is to give and legitimize the voices of those silenced by history and give them the possibility to rewrite the forgotten; also to innovate demands to make visible and viralize reality, to validate pedagogical proposals that have as a driving force the struggle for dignities, that do not turn their backs on the climate and ecological crisis. In this regard, it is essential to analyze the link between Pedagogy and Literature, disciplines that converge in their political dimension from an ecocritical and gynocritical approach to the written legacy and new textualizations, capable of generating a polyphonic chorus that can transgress the limits imposed by a predominantly male canon.

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)0.008
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 score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.006
Science and technology studies0.0050.014
Scholarly communication0.0120.009
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.002

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 head0.058
GPT teacher head0.391
Teacher spread0.334 · 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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