From Revolutionary Nationalism to Orthodox Neoliberalism : How Nafta Contributed to Push Mexico into the Right-Wing Stranglehold
Bibliographic record
Abstract
A century ago, Mexico experienced a revolution blending liberal institutions with quasi-socialist principles. However, this country is today one of the bastions of neoliberalism and the political right in the world. How was this radical change possible?I will argue that this change resulted from a process that started in the 1940s, when a group of critics of the regime established a direct connection with the Austrian School of neo-classic economics. This connection resulted in the creation of a series of institutions that would promote neoliberalism as an alternative to the predominant revolutionary nationalist paradigm.A defining moment in this process was the adoption of the North American Free Trade Agreement (NAFTA) in the 1990s. NAFTA launched a process of massive ideological realignment; creating a new landscape in Mexico that brought the country closer to right-wing ideologies. NAFTA’s architect was Carlos Salinas, president of Mexico (1988-1994), who refashioned Mexico’s public administration to cater to the neoliberal project.This article offers evidence of this process, building both from historical record and empirical research. I will show that the roots of Mexico’s contemporary right-wing ideologies are old, a combination of bottom up and top down activism, and eventually structural; and are kept alive by persistent activism.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".