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Record W2559895640 · doi:10.18192/rceh.v39i3.1627

Thinking Postmemory through Translation in Roberto Brodsky’s Bosque quemado

2015· article· es· W2559895640 on OpenAlexaffvenue
Hilary Levinson

Bibliographic record

VenueRevista Canadiense de Estudios Hispánicos · 2015
Typearticle
Languagees
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesArtCartographyGeography

Abstract

fetched live from OpenAlex

El presente artículo se concentra en Bosque quemado (2007), novela escrita por Roberto Brodsky y texto ejemplar para explorar el concepto de “posmemoria” – formulado por Marianne Hirsch para describir la experiencia de los hijos de sobrevivientes de un trauma. Considera la novela de Brodsky como una respuesta literaria tanto a la represión que imponía la dictadura chilena como a la herencia de aquel trauma en el presente. Se refiere a la figura de la traducción como metáfora general que reconoce y negocia las distancias que aparecen siguiendo los pasos de la dictadura en Chile y demuestra que la posmemoria, como respuesta o reacción negociada, es una forma de traducción en sí misma. Este artículo detalla las referencias recurrentes a fotografías y películas en Bosque quemado, proponiendo que estos objetos visuales son emblemáticos del pasado y, además, de la materialidad del pasado y sus representaciones. La posmemoria, entendida a través de la traducción, demanda una negociación con esta densa materialidad. Las distintas formas de trabajar con los objetos visuales (por ejemplo, revelar negativos fotográficos) son actos de traducción que se hacen eco de las negociaciones implicadas en la construcción y reconstrucción de narrativas personales y colectivas.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.282
Teacher spread0.226 · 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

Citations3
Published2015
Admission routes2
Has abstractyes

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