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Record W3040556670 · doi:10.46744/bapl.201402.001

Dos voces que parecen una: Idearios políticos e identidades étnicas en las memorias de Juan Bautista Túpac Amaru

2014· article· es· W3040556670 on OpenAlexaff
María Teresa Grillo

Bibliographic record

VenueBoletín de la Academia Peruana de la Lengua · 2014
Typearticle
Languagees
FieldSocial Sciences
TopicIndigenous Cultures and History
Canadian institutionsMount Royal University
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Las Memorias de Juan Bautista Túpac Amaru (1825) es un texto singular, de corte autobiográfico, escrito por el hermano de José Gabriel Condorcanqui, Túpac Amaru II, quien fue hecho prisionero después de la derrota del líder andino y liberado décadas después, en tiempos de la emancipación americana. En él confluyen los recuerdos de la sublevación andina y los ideales de la independencia hispanoamericana liderada por criollos. Este artículo sugiere que las Memorias constituyen una “autobiografía en colaboración” (Lejeune1989) cuyas marcas textuales permiten identificar una voz andina y otra criolla. La dualidad de la voz narrativa revela la importancia del momento de la enunciación en la textualización de los recuerdos de Juan Bautista, particularmente en las construcciones textuales referidas a las ideas de la Ilustración y los conceptos sobre raza. A través de las fisuras producidas por la doble enunciación se hace posible una aproximación a las ideas políticas predominantes en el texto así como a las percepciones de las identidades étnicas manifestadas por los sujetos de la enunciación.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

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 studies0.0100.013
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.003
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 head0.005
GPT teacher head0.320
Teacher spread0.315 · 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 designQualitative
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
Published2014
Admission routes1
Has abstractyes

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