Trumping Capacity Gap with Negotiation Strategies: the Mexican USMCA Negotiation Experience
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT In the past few months, we have witnessed the ‘worst deal’ in the history of the USA become the ‘best deal’ in the history of the USA. The negotiation leading to the United States–Mexico–Canada Agreement (USMCA) appeared as an ‘asymmetrical exchange’ scenario that could have led to an unbalanced outcome for Mexico. However, Mexico stood firm on its positions and negotiated a modernized version of North American Free Trade Agreement. Mexico faced various challenges during this renegotiation, not only because it was required to negotiate with two developed countries but also due to the high level of ambition and demands raised by the new US administration. This paper provides an account of these impediments. More importantly, it analyzes the strategies that Mexico used to overcome the resource constraints it faced amidst the unpredictable political dilemma in the US and at home. In this manner, this paper seeks to provide a blueprint of strategies that other developing countries could employ to overcome their negotiation capacity constraints, especially when they are dealing with developed countries and in uncertain political environments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it