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Record W1851486901 · doi:10.14198/aleua.2012.24.05

Los espacios urbanos de la miseria en algunas novelas del siglo XIX: una estética de la verdad

2012· article· es· W1851486901 on OpenAlexaff
Yvan Lissorgues

Bibliographic record

VenueAnales de Literatura Española · 2012
Typearticle
Languagees
FieldArts and Humanities
TopicHistorical Art and Architecture Studies
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

En la estela de L’Assommoir (1877) y a partir de La desheredada (1881), por primera vez en España, acceden a la representación literaria los espacios urbanos del bajo pueblo: los barrios de la miseria del Sur de Madrid (en La desheredada, Fortunata y Jacinta, Nazarín, Misericordia, La Busca, Mala Hierba,…), los espacios del «proletariado» urbano de Marineda (La Tribuna) o de Vetusta (La Regenta). Además del precioso valor documental de estas representaciones de unas realidades hasta entonces ocultadas o idealizadas, se impone, según una ética totalizadora, una estética de la verdad que es una superación de la teoría de los niveles estilísticos que ignoraba lo bajo, por feo y por indigno del arte o lo relegaba al campo de lo cómico (comedia) o lo toleraba como contrapunto burlesco de lo grande (épica, tragedia). En España, como en toda Europa, las obras naturalistas de la segunda mitad del siglo XIX, gracias al total ensanchamiento temático y al rigor puesto en la fidelidad de la pintura, rompen definitivamente esa jerarquía de los estilos y muestran que cualquier realidad, como la de los barrios urbanos de la miseria, puede ser objeto de representación artística.

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)0.001
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.251
Teacher spread0.246 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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