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Masculinidad y autoviolencia: representación del pasado, crisis del relato marco y desviaciones de la focalización en Aftersun (Charlotte Wells, 2022)

2024· article· es· W4400892829 on OpenAlexaff
José A. Planes Pedreño, Javier Juárez Rodríguez

Bibliographic record

VenueFotocinema Revista científica de cine y fotografía · 2024
Typearticle
Languagees
FieldArts and Humanities
TopicCinema History and Criticism
Canadian institutionsWSP (Canada)
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Con este artículo, proponemos un análisis interdisciplinar de una obra cinematográfica de especial relevancia estética y temática como es Aftersun (Charlotte Welles, 2022), toda vez que expone los nocivos efectos que, aún hoy, arrastran los modelos de masculinidades y paternidades hegemónicos en los propios hombres: por un lado, desvela cómo tales efectos emergen a la luz de unas autoexigencias marcadas por los códigos, roles, estereotipos y creencias arraigados en imaginarios sociales y culturales; por otro, advierte de la autoviolencia como respuesta inconsciente ante la presión de las obligaciones y mandatos que, inherentes al paradigma tradicional, las varonías esperadas imponen y que, a la postre, resultan imposibles de asumir. El filme de la directora británica explora asuntos apenas visibilizados en el medio cinematográfico, y lo hace a través de una singular disposición narrativa donde las anacronías temporales y el ejercicio de la memoria desempeñan una función esencial a fin de transmitir hasta qué extremo estos modelos pueden heredarse sin vislumbrar las causas que abocan al género masculino a un destino trágico. De este modo, la teoría narratológica nos permite esclarecer los fenómenos narrativos que caracterizan al largometraje, para, a continuación, discernir su discurso con arreglo a una perspectiva de género.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.009
GPT teacher head0.265
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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