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Record W4234426817 · doi:10.32920/ryerson.14653083

Protection of Nationals Abroad : The Mexican State and the Seasonal Agricultural Workers in Canada

2021· preprint· en· W4234426817 on OpenAlexaffabout
Karla Angélica Valenzuela Moreno

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEmployment, Labor, and Gender Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAgricultureGovernment (linguistics)State (computer science)BusinessForeign nationalEconomic growthPolitical scienceDevelopment economicsGeographyEconomicsLaw

Abstract

fetched live from OpenAlex

Due to the adverse economic conditions in Mexico and the need for offshore labour in Canadian agriculture, Mexico entered the Seasonal Agricultural Worker Program (SAWP) in 1974 as a source country, becoming the country that exports the highest number of agricultural works to Canada. While abroad, these workers have genuine needs that should be addressed by the Mexican government, but unfortunately the Mexican government has failed to provide adequate protection to its nationals. This paper offers an overview of the situation in rural Mexico, the operational aspects of the program and its violations; it identifies the workers' needs and the most important national and international documents that regulate the protection of nationals abroad. This research is a critique of the role of the Mexican government in the protection of the seasonal agricultural workes in Canada, identifying the limitations that the State faces for providing protection to its nationals.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.411

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0210.006
Scholarly communication0.0050.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.289
Teacher spread0.263 · 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
Published2021
Admission routes2
Has abstractyes

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