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Record W3107147636 · doi:10.34096/cas.i52.8899

Se viene el malón. Las geografías afectivas del racismo argentino

2020· article· es· W3107147636 on OpenAlexaff
Gastón Gordillo

Bibliographic record

VenueCuadernos de antropología social · 2020
Typearticle
Languagees
FieldSocial Sciences
TopicArgentine historical studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Este trabajo analiza las dimensiones espaciales y afectivas de la blanquitud y del racismo en la Argentina por medio de un contrapunto entre “la Argentina Blanca”, entendida como el proyecto de crear una geografía nacional de tipo europeo, y “el malón” como alegoría de las multitudes populares que amenazan dicho proyecto. A partir de una lectura espacial y afectiva de momentos clave de la historia argentina desde fines del siglo XIX hasta el gobierno de Macri, muestro que lo que más suele generar expresiones de racismo en la Argentina es la irrupción en el espacio público de multitudes de gente pobre y de tez oscura que evocan “el malón”: las caballerías indígenas que en el pasado le pusieron límites al proyecto de una nación europeizada. Este artículo analiza cómo el miedo al malón ha sido usado en diversos contextos históricos para legitimar el terror estatal –que analizo por medio de la figura del “malón blanco”– y cómo en las últimas décadas ha surgido, como contrapunto y crítica al racismo del proyecto de la Argentina Blanca, una “Argentina mestiza” que se siente cómoda con la multiplicidad de la nación.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.049
GPT teacher head0.338
Teacher spread0.290 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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