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Record W2027197655 · doi:10.1080/14636204.2013.888255

Discursos patriótico-aristocráticos sobre la “nación gallega” a comienzos del siglo XVII: a propósito de<i>Tragedias de amor</i>(1607) de Juan de Arce Solorzeno

2013· article· es· W2027197655 on OpenAlexaboutno aff
Javier Irigoyen-García

Bibliographic record

VenueJournal of Spanish Cultural Studies · 2013
Typearticle
Languagees
FieldArts and Humanities
TopicHistorical Studies on Spain
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Este artículo plantea la existencia de un proyecto de promoción identitaria de Galicia llevada a cabo por la nobleza gallega a principios del siglo XVII, en el marco de la defensa de diversos intereses locales. Para ello se analizan los discursos historiográficos, cartográficos y literarios que crean una imagen idealizada del espacio gallego y que, a pesar de su carácter aristocratizante, comienzan a formular un sentimiento de identificación colectiva que busca que los límites territoriales del grupo cultural y lingüístico coincidan con los del ejercicio del poder político dentro del marco institucional de la monarquía española. Es dentro de este contexto intelectual y político en el que resultan inteligibles textos literarios como Tragedias de amor (1607) de Juan de Arce Solorzeno, ya que el análisis de sus referentes historiográficos y de representación espacial indica que se inserta dentro de los discursos identitarios gallegos. La importancia del contexto de producción y consumo para la interpretación de la obra se hace evidente al comparar la circulación de la primera edición con la reedición de Tragedias de amor en Zaragoza en 1647, que neutraliza el contenido identitario de la obra al descontextualizar la alabanza del territorio y enfatizar en cambio la alabanza de la casa de Castro, en un intento de la élite aragonesa por relacionarse con los círculos de poder.

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: none
Teacher disagreement score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.020
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0020.003
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 head0.033
GPT teacher head0.281
Teacher spread0.249 · 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".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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