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Record W4285407326 · doi:10.4000/conflits.23565

Du déplacement forcé à l’auto-défense.

2022· article· fr· W4285407326 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCultures & conflits/Cultures et conflits · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicPolitical and Social Dynamics in Chile and Latin America
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Les programmes de villagisation forcée mis en place durant la guerre froide globale permettent d’explorer le processus de « miliciarisation forcée » de la population civile regroupée dans ces villages. Si l’enrôlement de personnes déplacées dans des milices semble avoir été une constante dans le cadre de ces programmes, comment la villagisation forcée est-elle devenue tout à la fois un outil pour combattre la « menace communiste », un programme de « développement forcé » et un dispositif destiné à forcer la miliciarisation de la population déplacée ? À partir de l’analyse de plusieurs cas en Amérique latine, et notamment celui de l’Argentine, nous voulons comprendre pourquoi le dispositif milicien n’a pas toujours eu le même degré de systématicité ni le même degré de confiance des armées locales vis-à-vis de la population à miliciariser. Cet article se veut avant tout une contribution critique à l’étude de l’appropriation locale d’une technique de contre-insurrection et de développement forcé ainsi qu’une réflexion sur les effets à long terme sur la population ayant subi un processus de miliciarisation forcée.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.859
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0050.002
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.031
GPT teacher head0.343
Teacher spread0.312 · 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