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Preface

2023· book-chapter· en· W4387792468 on OpenAlexaboutno aff
Philip Martin

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicLatin American rural development
Canadian institutionsnot available
Fundersnot available
KeywordsFarm workersImmigrationWorkforcePovertyGeographyMigrant workersPolitical scienceSocioeconomicsAgricultureEconomic growthSociologyEconomicsArchaeology

Abstract

fetched live from OpenAlex

Extract Five million Mexican-born farm workers are employed on North American farms sometime during a typical year, including 50,000 in Canada, 3 million in Mexico, and 2 million in the United States. Almost all of these workers were raised in poverty in rural Mexico. Mexican farm workers employed on American and Canadian farms earn at least ten times more than they would earn in Mexico, whether they are employed as guest workers, legal immigrants or naturalized citizens, or unauthorized workers. Mexican farm workers are also employed in Mexico on farms in the northern and central states that export fruits and vegetables to the United States; this group of workers includes internal migrants from Mexico’s poorer southern states. This book explores the impacts of Mexican migrant workers in Canada, Mexico, and the United States, the alternatives to farm workers in particular commodities, and policies to improve protections for farm workers. Mexican braceros, or guest workers, were a significant share of the US farm workforce in the 1950s, an experience often viewed as a time of failure to protect Mexican and US farm workers. Bracero 2.0 explores the similarities and differences between the braceros of the past and the migrant farm workers in Canada, Mexico, and the United States today.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.812
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.008

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 head0.031
GPT teacher head0.196
Teacher spread0.165 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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