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Record W6996598477

So, what can we do?: We are coming here to work, human security and the agricultural worker program

2004· dissertation· en· W6996598477 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2004
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureFarm workersHuman securityMigrant workersTechnology transferSocial security
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores how the Seasonal Agricultural Worker Program impacts the various dimensions of "human security" of the life of Mexicans in Canada and in the community of Las Nubes in Mexico. Special attention is given to describe the perceptions of the Mexicans regarding the possibilities of whether they are able to transfer the technology that they learned in Canada to their communities of origin and to assess if the participation of Mexicans in the SAWP either promote, hinder, or is irrelevant to, development in Las Nubes. Multiple methods were used to collect data. This research shows that the SAWP, rather than being a vehicle of technology transfer that benefits the communities of the Mexican migrant workers, is merely an opportunity for those Mexican farm workers to make remittances. The circular migration constitutes a survival practice that allows migrant farm workers the risk management of the conditions of human insecurity that they live with in Mexico. The survival strategy is compounded by a series of trade-offs of different levels of risks on the different dimensions of human security between Mexico and Canada.

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)0.002
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.909
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.009
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.002

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 head0.209
Teacher spread0.197 · 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
Published2004
Admission routes1
Has abstractyes

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