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Record W2555894701 · doi:10.18192/rceh.v39i2.1618

Loss, Emotions, and Politics: Mass Graves, Melancholia, and Performance in Santiago Roncagliolo’s Abril rojo (2006)

2015· article· es· W2555894701 on OpenAlexaffvenue
Pablo Genaro Celis-Castillo

Bibliographic record

VenueRevista Canadiense de Estudios Hispánicos · 2015
Typearticle
Languagees
FieldSocial Sciences
TopicPolitical and Social Dynamics in Chile and Latin America
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesLIDAArtPsychology

Abstract

fetched live from OpenAlex

Una de las tantas fosas masivas clandestinas en las cuales yacen los cadáveres anónimos de muchas de las víctimas del conflicto entre el estado peruano y el grupo terrorista Sendero Luminoso es representada en la novela Abril rojo (2006) de Santiago Roncagliolo. Este horrendo agujero, además de dar testimonio sobre la violencia del choque armado, sirve como escenario para el performance político de Nélida, la acongojada madre de uno de los muchos desaparecidos del conflicto. Entre gritos, empujones y amenazas, Nélida muestra su interminable tristeza (o melancolía) y establece el infranqueable compromiso que tiene para con su hijo. Mediante estas acciones ella también protesta con singular potencia los abusos y crímenes cometidos durante el conflicto. A través de las divagaciones freudianas sobre “melancolía” y “paso al acto”, este ensayo explica cómo el comportamiento de Nélida alrededor de la fosa clandestina se convierte en un performance político que exige justicia para los culpables y que busca generar y perpetuar la memoria de las víctimas.

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)0.001
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: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0090.017
Scholarly communication0.0060.003
Open science0.0010.006
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.274
Teacher spread0.258 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueRevista Canadiense de Estudios HispánicosSame topicPolitical and Social Dynamics in Chile and Latin AmericaFrench-language works237,207