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Record W376723855 · doi:10.3989/alqantara.2013.006

Musulmanes retóricos: el Islam como testigo en la polémica cristiana anti-judía en occidente

2013· article· es· W376723855 on OpenAlexfundno aff
Ryan Szpiech

Bibliographic record

VenueAl-Qanṭara · 2013
Typearticle
Languagees
FieldSocial Sciences
TopicHistorical and Linguistic Studies
Canadian institutionsnot available
FundersInstitut d'Estudis CatalansYork UniversityPrinceton University
KeywordsIslamWitnessJudaismRhetorical questionReligious studiesPhilosophyTheologyLinguistics

Abstract

fetched live from OpenAlex

Aunque los escritores del s. XII como Pedro Alfonso y Pedro el Venerable de Cluny atacaron las ideas musulmanas sobre Jesús y María, los autores polémicos de los ss. XIII y XIV a veces presentaron las mismas ideas de manera positiva y describieron al musulmán como un 《testigo》 de las ideas cristianas ante los judíos. En los textos del dominico Ramon Martí, el Corán mismo sirve como una 《prueba》 de las doctrinas cristianas sobre Jesús y María y en textos como el Mostrador de justicia de Abner de Burgos/Alfonso de Valladolid, a los musulmanes se los describe como 《nazarenos》. El estudio de estas imágenes permite distinguir entre la representación de los musulmanes en los textos anti-judíos y su representación en los textos anti-islámicos. Este artículo sugiere que, en los textos anti-judíos de los ss. XIII y XIV, son más determinantes las normas de la polémica anti-judía que el juicio sobre el islam que se observa en la polémica anti-musulmana.

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)0.002
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.011
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.299
Teacher spread0.289 · 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

Citations15
Published2013
Admission routes1
Has abstractyes

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