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Record W4230377987 · doi:10.4000/alhim.5466

Le programme canadien des travailleurs agricoles saisonniers et le système régional de migration au Yucatán : où sont les femmes?

2016· article· fr· W4230377987 on OpenAlexaffabout
Marie France Labrecque

Bibliographic record

VenueAmérique latine histoire et mémoire · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article s’intéresse à la migration qui s’effectue dans le cadre d’un programme bilatéral entre le Canada et le Mexique, le Programme des travailleurs agricoles saisonniers (PTAS). Ouvert aux femmes et aux hommes mexicains, le programme ne recrute pourtant qu’une proportion infime de femmes les assignant à des tâches spécifiques tout en surveillant étroitement leur comportement. S’appuyant sur la notion de système régional de migration de même que sur des données ethnographiques recueillies pendant l’année 2012 au Yucatán, l’auteure décrit l’insertion des femmes dans les différents types de migration dans cet État mexicain qui se caractérise par un fort pourcentage de population autochtone maya, et montre que les rapports sociaux inégaux, tels que le genre, sont consolidés dans le contexte de ce programme. On constate que la structure globale du programme, le type d’insertion des individus dans cette migration et les représentations sociales à la fois de la société d’origine et de la société de destination sont à l’œuvre pour maintenir les femmes dans un état de subordination, qu’il s’agisse des travailleuses recrutées dans le PTAS ou des conjointes des travailleurs du programme.

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: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.867

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.260
Teacher spread0.237 · 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
Published2016
Admission routes2
Has abstractyes

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