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Record W3111217500 · doi:10.7202/1073797ar

La stérilisation forcée de population autochtone dans le Mexique des années 1990

2020· article· fr· W3111217500 on OpenAlexvenueno aff
Pierre Gaussens

Bibliographic record

VenueCanadian Journal of Bioethics · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article cherche à explorer la question de la stérilisation forcée de population autochtone comme problème bioéthique d’un point de vue interdisciplinaire, à partir de la sociologie historique et en dialogue avec l’anthropologie médicale, les études de genre et les droits humains. Sa méthodologie est basée sur l’étude d’un cas empirique, en lien avec un travail de terrain réalisé dans une municipalité du sud du Mexique, dans l’état de Guerrero. Elle est complémentée par une recherche documentaire qui a permis, entre autres, la construction d’un cas théorique à partir des événements survenus au Pérou, à la même époque que le cas mexicain, dans les années 1990. Le principal résultat de ce travail de recherche historique est que la stérilisation forcée, bien que largement due à une politique de contrôle démographique ainsi qu’à certaines pratiques de planification familiale, est également liée, dans le cas particulier de la population autochtone, à des processus contre-insurrectionnels déployés face à l’activité de guérillas, caractéristique de ces années-là en Amérique Latine.

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)0.003
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 score0.173
Threshold uncertainty score0.345

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.200
GPT teacher head0.385
Teacher spread0.185 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueCanadian Journal of BioethicsSame topicPublic Health and Social InequalitiesFrench-language works237,207