International Labor Policies and the North American Free Trade Agreement: Are Women Getting Their Fair Share?
Bibliographic record
Abstract
From the Introduction: The North American Free Trade Agreement (NAFTA) has always been a document of controversy. On the surface, NAFTA opened trade among its three primary parties -- Canada, Mexico, and the United States. Realistically, however, it has been a cause for tension -- mainly between the governments of the United States and Mexico. The two countries have used NAFTA and its labor side agreement, the North American Agreement on Labor Cooperation (NAALC), to dictate its economic and labor policies in each other’s countries. This article will argue that more must be done to protect the rights of female workers under the North American Agreement on Labor Cooperation. I will do this by first examining the NAALC in closer detail to give us the background to work with. Then I will look at both NAALC inquiries in more detail. The complaint against the United States involved a telecommunications company that was a subsidiary of Sprint, Inc. that closed down eight days before a scheduled union representation vote; the complaint against Mexico involved the practice of pregnancy and sex discrimination against female workers in the Maquiladora sector. Finally, I will offer discussion points for the three NAFTA parties and scholars to consider as we move into the next millennium.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.019 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".