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Record W2209570670 · doi:10.18192/rceh.v39i2.1624

Reading for Stimmung in Muñoz Molina’s Sefarad

2015· article· es· W2209570670 on OpenAlexaffvenue
Alvin F. Sherman

Bibliographic record

VenueRevista Canadiense de Estudios Hispánicos · 2015
Typearticle
Languagees
FieldArts and Humanities
TopicComparative Literary Analysis and Criticism
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

En su novela Sefarad, Antonio Muñoz Molina logra sumergir el lector en un mundo repleto de olores y sabores, objetos, lugares y circunstancias, y sensaciones físicas y emocionales que desencadenan una reacción física en el lector que sobrepasa la lectura pasiva del texto. A base de las ideas de Heidegger, Gumbrecht, y otros, se desarrolla aquí una manera sobretextual de aproximarse el lector al texto. Aplicando las ideas de Stimmung, veremos cómo el autor ha logrado injertar en los recuerdos de su narrador sensaciones que individualizan la experiencia vivida. Lo significativo de esa técnica es la capacidad de esas descripciones de afectar al lector, ligando sus experiencias y recuerdos con los del narrador. Esa técnica complementa y aumenta la importancia de la identidad individual frente a su neutralización en el contexto de una identidad nacionalista, sutilmente representado en el contexto franquista. Como sugiere el título, Sefarad recalca el papel que juegan los elementos culturales (comida, aromas, lugares, celebraciones, etc.) que estimulan al individuo y causan una reacción física (e.g., escalofríos, hambre, salivar, lágrimas). Como resultado, la novela sirve como propaganda antinacionalista y reafirma la peculiaridad de la identidad individual y cultural que define a un pueblo.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.285
Teacher spread0.240 · 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 teacher head, not a consensus.

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
Published2015
Admission routes2
Has abstractyes

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