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Record W7064654099

Científicos sociales versus crítico literarios (Todas las sangres en debate)

2013· dissertation· es· W7064654099 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2013
Typedissertation
Languagees
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)PopulationPeriod (music)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Este trabajo es una crónica del (des)encuentro entre científicos sociales y críticos literarios que se produjo el 23 de junio de 1965 en el Instituto de Estudios Peruanos (IEP) en torno a la novela de José María Arguedas publicada en 1964 titulada Todas las sangres (TLS). Participaron en el, Jorge Bravo Bresani, Alberto Escobar, Henri Favre, José Matos Mar, José Miguel Oviedo, Aníbal Quijano, Sebastián Salazar Bondy y José María Arguedas. El énfasis está puesto en cada uno de los turnos de palabra y de las lógicas argumentales para deducir los universos cognitivos y culturales de los participantes, los marcos de referencia, los presupuestos, las implicancias, las concordancias, las diferencias y las incoherencias de todos y cada uno de los enunciados que conforman el debate que, a su vez, evidencia los universos cognitivos y enciclopédicos de los campos de la crítica literaria y de las ciencias sociales. Así se harán evidentes los (des)encuentros entre críticos literarios y científicos sociales por lo menos en una etapa que forma parte de la historia de las mentalidades en el Perú.

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)0.007
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0090.027
Scholarly communication0.0160.008
Open science0.0010.007
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.026
GPT teacher head0.311
Teacher spread0.285 · 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 designTheoretical or conceptual
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

Citations0
Published2013
Admission routes1
Has abstractyes

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