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Record W4244420955 · doi:10.4324/9781315233154-9

The Endriago subject and the dislocation of state attribution in human rights discourse: the case of Mexican asylum claims in Canada

2018· book-chapter· en· W4244420955 on OpenAlexaboutno aff
Ariadna Estévez

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)AttributionDislocationHuman rightsState (computer science)Political scienceSociologyGender studiesLawPsychologySocial psychologyLibrary scienceComputer sciencePhysicsCondensed matter physics

Abstract

fetched live from OpenAlex

Mexico is arguably immersed in an unprecedented wave of violence in which drug cartels and law enforcement officials at times work together in cases of forced disappearance, kidnapping, execution, torture, persecution and other atrocities considered violations of the most basic human rights, including the right to life and to physical integrity. However, these atrocities are only classified as human rights violations if they can be unequivocally attributed to the state; this is not always possible. Using Foucault’s idea of governmentality and Valencia’s concept of the Endriago as a subjectivity emerging from the specific governmentalisation of the Mexican state, this article examines how hybrid agents in Mexico – law enforcement officials working for criminal gangs or criminals working for the state – serve to subvert common understandings of attribution and responsibility in the state-centric discourse of human rights in general, and of the right of asylum in the specific case of Canada, a country to which thousands of Mexicans have fled.

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)0.002
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 score0.081
Threshold uncertainty score0.585

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0290.030
Scholarly communication0.0100.003
Open science0.0010.003
Research integrity0.0020.004
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 head0.012
GPT teacher head0.279
Teacher spread0.268 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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