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Record W2594984994 · doi:10.18192/rceh.v40i3.1953

Museo de la Memoria y los Derechos Humanos de Santiago de Chile: crisis de memoriales y lógicas urbanísticas de mercado

2016· article· es· W2594984994 on OpenAlexaffvenue
Miguel Caballero Vázquez

Bibliographic record

VenueRevista Canadiense de Estudios Hispánicos · 2016
Typearticle
Languagees
FieldSocial Sciences
TopicPolitical and Social Dynamics in Chile and Latin America
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

El presente artículo discute el impacto producido por la inauguración en 2010 del Museo de la Memoria y los Derechos Humanos en Santiago de Chile, en el marco de la celebración del Bicentenario de la Independencia. La lectura que se propone entiende el Museo como respuesta al deseo del gobierno de la Concentración por controlar el significado del resto de memoriales de Chile, que se habían vuelto demasiado ambiguos e independientes. El Museo se concibe, por tanto, como archi-memorial para controlar el sentido de los demás memoriales de Chile. Reestructura el mapa de la memoria de Santiago y, en última instancia, de todo el país, a la vez que reincide en el centralismo político. También se propone un análisis de la exposición permanente del Museo con respecto a lo excluido, tanto de la historia de otras memorias, desde el allendismo hasta el conflicto mapuche, como de la relación jerárquica entre la exposición permanente y las muestras temporales. Finalmente, se aboga por la necesidad de interpretar el Museo dentro de las lógicas del mercado urbanístico, la gentrificación y la espectacularización de la arquitectura, a partir de las políticas oficiales de reconstrucción nacional, marca-ciudad y terciarización económica de la modernidad neoliberal.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.010
Scholarly communication0.0070.004
Open science0.0010.011
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.015
GPT teacher head0.310
Teacher spread0.295 · 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

Citations2
Published2016
Admission routes2
Has abstractyes

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