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Record W2171985032

# Mexico-U.S. Migration and Labor Unions: Obstacles to Building Cross-Border Solidarity

2003· article· en· W2171985032 on OpenAlexaboutno aff
Julie R. Watts

Bibliographic record

VenueeScholarship (California Digital Library) · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsSolidarityImmigrationCenter (category theory)SociologyPolitical scienceGeographyLaw
DOInot available

Abstract

fetched live from OpenAlex

Despite persistent Mexican migration, deepening North American economic integration, and the recent predominance of migration on the U.S.-Mexico bi-national agenda, cross-border labor union efforts to collaborate on immigration policy and migrant worker rights have been sporadic, reactive, and lacking in concerted action.Based on recent interviews conducted with U.S. and Mexican labor union representatives, migration scholars, immigrant advocacy groups, and government officials, Watts examines the historical, political, and institutional obstacles to cross-border labor union solidarity on migration issues.Over the last decade, the North American Free Trade Agreement (NAFTA) has deepened economic integration between the U.S. and Mexico by lowering barriers to trade and investment.Since 1993, the value of trade between the U.S. and Mexico has almost tripled from $81 billion to $232 billion and Mexico is now the second largest trading partner for the U.S. after Canada. 1 Although not facilitated by NAFTA, 2 Mexico-U.S. migration also has increased and is equally vital to the region.Between 1994 and 2001, annual legal and illegal Mexico-U.S. migration increased from 300,000 to 500,000. 3 Over a 10-year period, the Mexican-born population in the U.S. increased by 53% to reach 20.6 million in 2000.Of these Mexican-born, those who are immigrants totaled just over 9 million. 4 Finally, an estimated 4.8 million undocumented Mexicans are in the U.S., a 58% increase from 1990. 5 1 Griswold, D.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0030.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.309
Teacher spread0.295 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations19
Published2003
Admission routes1
Has abstractyes

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