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Record W2518188915 · doi:10.18192/rceh.v40i1.1596

Novelistas españoles y memoria histórica en el siglo XXI

2015· article· es· W2518188915 on OpenAlexaffvenue
Maryse Betrand de Muñoz

Bibliographic record

VenueRevista Canadiense de Estudios Hispánicos · 2015
Typearticle
Languagees
FieldArts and Humanities
TopicSpanish Culture and Identity
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

La memoria histórica forma parte del patrimonio de la humanidad desde finales del siglo XX. En España permanecen aún los nefastos recuerdos de la Guerra Civil de 1936-1939 y sus secuelas. Frente a este conflicto domina, al principio del siglo XXI, la oposición entre dos ideologías: la “desmemoria” y la urgencia de elucidar el pasado para lograr encontrar la verdad. Los novelistas españoles han abundado en escribir sobre la guerra fratricida y el Franquismo desde su mismo principio, pero de manera insistente desde principios del presente siglo. La Ley de la Memoria Histórica, promulgada en el 2007, permitía revisar todos aquellos años difíciles de la historia del país y ha sido un excelente incentivo para los narradores. Un centenar de autores, muchos de ellos entre los de mayor renombre en la novelística actual, adoptaron una estrategia narrativa poco usada antes: la metaficción en todas sus variantes, desde la más sencilla, como la del texto o libro encontrado, hasta la más compleja, jugando entre la realidad y la ficción, y arrastrando al lector a un laberinto a veces casi inextricable. Basándome en los críticos más conocidos sobre el género analizo las novelas de más relieve escritas en España desde el año 2000.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.026
GPT teacher head0.254
Teacher spread0.228 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

Explore more

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