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Record W1556932960 · doi:10.7202/039269ar

Analyse d’un écho. La trace de l’explicador dans la sonorisation comique des films muets en Espagne (1933-1950) 1

2010· article· fr· W1556932960 on OpenAlexvenueno aff
Daniel Sánchez Salas

Bibliographic record

VenueCinémas Revue d études cinématographiques · 2010
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

L’avènement du parlant en Espagne durant les années 1930-1940 a donné lieu à une expérience singulière : l’adjonction de commentaires comiques à d’anciennes bandes de l’ère du muet. Cette expérience permet d’étudier l’hypothétique présence de l’explicador au sein d’un contexte historique bien différent de celui de ses origines, le cinéma des premiers temps. S’agit-il d’une simple « réapparition » de l’explicador, ou plutôt d’une hybridation qui aurait bénéficié de l’ère nouvelle du parlant ? L’auteur de cet article tente une réponse en explorant deux voies complémentaires d’analyse : d’abord, en menant l’étude des circonstances de l’apparition de ce type de sonorisation, puis en comparant le discours comique produit par cette expérience avec le discours de l’explicador du cinéma des premiers temps. Cette étude s’appuie sur deux cas emblématiques : les Celuloides rancios (1933) de la compagnie Hispano Foxfilm et les courts métrages de la compagnie Exclusivas Arajol, diffusés dans les années 1940.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.006
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.014
GPT teacher head0.230
Teacher spread0.216 · 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
Published2010
Admission routes1
Has abstractyes

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