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Record W4390950878 · doi:10.7203/celestinesca.47.26729

La influencia en los espectadores de la fama de las actrices que encarnaron a Celestina

2023· article· es· W4390950878 on OpenAlexaff
Enrique Fernández

Bibliographic record

VenueCelestinesca · 2023
Typearticle
Languagees
FieldArts and Humanities
TopicMedia, Journalism, and Communication History
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHumanitiesArtPersona

Abstract

fetched live from OpenAlex

Las actrices famosas que interpretaron el papel de Celestina predispusieron a las audiencias a una recepción de la obra mediatizada por su "persona", que es resultado de su larga y conocida carrera profesional y su imagen pública. Las actrices se convierten así en un intertexto más de la obra. Su influencia en las expectativas de las audiencias y por ende su recepción de la obra se puede reconstruir a través de cómo la promoción publicitaria de los espectáculos selecciona aspectos de su imagen integrándolos con el personaje de Celestina. Se percibe igualmente en cómo cada actriz, en colaboración con el director y el equipo de producción, crea un personaje de Celestina único que recicla elementos de su persona. Especialmente interesante es cómo los ideales de femineidad de cada época se negocian en estas encarnaciones de Celestina de actrices mayores que se hicieron famosas en su juventud. Para este análisis se aplican métodos y conceptos de los star studies y los études actorales a una selección de actrices señeras de teatro, cine y televisión que hicieron el papel de Celestina, desde su primera puesta en escena en 1909 hasta hoy.

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)0.005
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.006
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.016
GPT teacher head0.275
Teacher spread0.260 · 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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