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Record W7779202 · doi:10.1055/s-2007-994409

Gender, Health and Mobility: Health Concerns of Women Migrant Farm Workers in Canada

2008· article· en· W7779202 on OpenAlexaffabout
Janet McLaughlin

Bibliographic record

VenueAmerican Journal of Perinatology · 2008
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsMigrant workersHealth workerFarm workersBusinessDemographic economicsEnvironmental healthSocioeconomicsLabour economicsEconomic growthHealth servicesGeographySociologyMedicineAgricultureEconomicsPopulation

Abstract

fetched live from OpenAlex

The economic impacts of temporary labour migration, for both migrants and host countries, often overshadow and render invisible the social consequences.\nBased on three years of ethnographic research in Mexico, Jamaica and Canada, this article addresses issues of health and health care among women migrant workers in Canada’s Seasonal Agricultural Workers Program (SAWP). This temporary labour migration program annually employs some 20,000 workers from Mexico and the Caribbean in the Canadian agricultural industry.\nApproximately three per cent of SAWP participants are women. In FOCALPoint’s 2007 Special Edition on Migration, Kerry Preibisch demonstrated the ways in which women’s migration is characterized by specific concerns, as they live and work in a “highly masculinized environment.” Women’s health is an especially important, yet neglected issue.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.500

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.056
GPT teacher head0.381
Teacher spread0.325 · 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 designObservational
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

Citations7
Published2008
Admission routes2
Has abstractyes

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