Cross-Boarder Trade with Mexico and the Prospect for Worker Solidarity: the Case of Mexico
Bibliographic record
Abstract
While auto labor in North America remains fragmented and local, the auto companies have been reorganizing on a continental basis, building a modern, export-oriented production base in Mexico. This paper addresses the question of whether and how the diverse labor movements of Mexico, the U.S. and Canada can overcome the competitive dynamic of free trade and establish a regional union movement based on cross-border solidarity. A review of the salient events of the last 30 years indicates that, despite the widespread assumption that Mexican autoworkers must be benefiting from globalization to the same degree that U.S. and Canadian workers are losing, the actual outcomes are mixed on both sides of the border. Jobs are up in most years, but real wages are stagnant or falling, bargaining leverage is weakened, and de-unionization is growing across the continent. At the same time, the North American integration of production has established a common “occupational idiom” (and accompanying grievances) centered on lean production, outsourcing, and competitive “whipsawing” of plants making the same product. On this basis alone, proponents of cross-border solidarity can find potential allies from Puebla to Oshawa. Mobilizing that potential is difficult, however, when there are so few links between the labor movements of North America. Historical divisions rooted in the Mexican revolution and the Cold War are now diminished, but barriers of language and culture remain. A further barrier is the heightened job insecurity felt in many corners of the auto industry. Shifting market shares, global mergers, and periodic downsizing all contribute to this anxious state, which continental whipsawing makes all the more intense, continuous, and potentially divisive for any cross-border union movement. The paper ends with an assessment of current initiatives that point towards a possible North American movement of autoworkers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".