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Record W2732331469 · doi:10.15446/hys.n33.61824

Intertextualidad en los textos del antiguo Egipto: un análisis de los “bancos de arena”

2017· article· es· W2732331469 on OpenAlexaff
Leila Salem

Bibliographic record

VenueHistoria y Sociedad · 2017
Typearticle
Languagees
FieldArts and Humanities
TopicAncient Egypt and Archaeology
Canadian institutionsNutrasource
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Los textos literarios surgieron en el antiguo Egipto a comienzos de la dinastía XII. Sin embargo algunas metáforas, tópicos y expresiones que son recurrentes en los textos de ficción pertenecen a otros ámbitos narrativos, como los textos de las tumbas o monumentales. El concepto de intertextualidad nos permite analizar cómo los textos literarios dialogan permanentemente con otro tipo de discursos expresivos, cuestionando la autoría individual de los mismos, ya que el texto literario participa y es parte de una textualidad más amplia, interconectada, y sin un único mentor. A través de la expresión Tsw “bancos de arena” analizaremos la relación intertextual de los textos literarios del Reino Medio con las autobiografías del Reino Antiguo y del Primer Periodo Intermedio, y algunos textos religiosos del Reino Nuevo como los Libros del Amduat. De este modo, pondremos en discusión los diferentes significados que la expresión Tsw fue adquiriendo según el contexto textual e histórico en el cual fue expresada. Lo que nos permite concluir que el texto literario se alimenta de la diversidad y narra tópicos que no le pertenecen del todo, es decir, ficcionaliza metáforas, expresiones, ideas y textos que encontramos en narraciones no ficcionales pero que se nutren de sus significados.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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 score0.677
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.024
GPT teacher head0.286
Teacher spread0.262 · 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
Published2017
Admission routes1
Has abstractyes

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