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Record W4200109321 · doi:10.7203/qf.0.22047

Los discursos de género, violencia y desigualdad social en la era de la comunicación (digital)

2021· article· es· W4200109321 on OpenAlexaff
Sergio Maruenda-Bataller, Dolors Palau Sampío, Maite Taboada

Bibliographic record

VenueQuaderns de Filologia - Estudis Lingüístics · 2021
Typearticle
Languagees
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Este volumen tiene como objetivo estudiar y analizar los discursos públicos en torno al género, la violencia y la desigualdad social en los llamados medios digitales (Couldry 2012) y, más concretamente, su evolución e impacto político, cultural, social e ideológico en la era digital y las ‘nuevas’ formas de comunicación social, institucional y política (Fuchs 2007; Bennet & Segerberg 2013; Winseck 2017). La edición pretende profundizar en los discursos generados y canalizados a través de la llamada sociedad en red (Castells 2011), cuando se celebra el primer cuarto de siglo de vida de internet.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.005
Science and technology studies0.0060.011
Scholarly communication0.0130.009
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.024
GPT teacher head0.358
Teacher spread0.333 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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