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Record W7126472665

Enforcement of the United States-Mexico-Canada Agreement ("USMCA") Rapid Response Mechanism: Views from Mexican Auto Sector Workers

2024· report· W7126472665 on OpenAlexaboutno aff
Desiree LeClerq, Alex Covarrubias-V, Cirila Quintero Ramirez

Bibliographic record

VenueeCommons (Cornell University) · 2024
Typereport
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsEnforcementLaw enforcementCollective bargainingProcess (computing)Labour lawTraining (meteorology)Trade unionUnited States labor law
DOInot available

Abstract

fetched live from OpenAlex

[Excerpt] Our findings suggest that workers at facilities that have undergone RRM (Rapid Response Mechanism) enforcement activities are more aware of their labor rights and procedures than workers at facilities that have not undergone RRM enforcement activities. There are various reasons for that disparate awareness, including but not limited to the worker-level training that workers received within the framework of RRM enforcement versus the union-level training that the U.S. Department of Labor conducted throughout Mexico. Nevertheless, neither workers at RRM facilities nor facilities that had not participated in RRM enforcement tended to be as knowledgeable about the labor law reforms, the process to approve their collective bargaining agreements, and union election procedures as commonly presupposed in the current trade and labor discourse. [Also available as in a Spanish language version]

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)0.003
metaresearch head score (Gemma)0.003
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 score0.204
Threshold uncertainty score0.411

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.005
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0020.003
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 head0.057
GPT teacher head0.225
Teacher spread0.168 · 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
Published2024
Admission routes1
Has abstractyes

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