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Record W3211666132 · doi:10.18239/cor_46.2021.04

«Por los ojos vierto el alma luto traigo por mi honor»: el papel de Tamar en Los cabellos de Absalón

2021· book-chapter· es· W3211666132 on OpenAlexaff
Roberta Alviti

Bibliographic record

VenueCorral de Comedias · 2021
Typebook-chapter
Languagees
FieldArts and Humanities
TopicEarly Modern Spanish Literature
Canadian institutionsCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

"Los cabellos de Absalón", texto para el que Hilborn [1938: 70] indica el año de 1634 «as the most probable date» para su composición, se publicó por primera vez en una suelta que se incluye en un volumen facticio. Dicho volumen, que recoge trece piezas, está titulado "Comedias Nuevas. Parte IX", no presenta paginación o foliación, ni colofón y, desde luego, tampoco fecha de publicación. Sin embargo, Rodríguez Cuadros [1989: 112] supone que se debió de publicar alrededor de 1650. Sea como fuera, la propuesta de fechación avanzada por Hilborn, muy anterior a la de su publicación, está respaldada por unos datos proporcionados por "CATCOM, s.v. Los cabellos de Absalón", donde se señala que la comedia fue puesta en escena en el Corral de la Montería en Sevilla, por la compañía de Pedro de Cobaleda, Francisco Vélez de Guevara y Francisco Álvarez de Vitoria, en el mes de septiembre de 1641, aunque, según consta en el mismo banco de datos, la tragedia calderoniana se hubiera tenido que representar en el Coliseo de Sevilla, por la compañía de Francisco Álvarez de Vitoria, en el mes de diciembre del año anterior.

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)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.012
Scholarly communication0.0090.006
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0130.002

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 head0.021
GPT teacher head0.246
Teacher spread0.225 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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