Political Invisibility as Resistance: Unpacking Enloe’s Zapatismo and the Normative Blindspots of International Relations | A invisibilidade política como resistência
Bibliographic record
Abstract
Building upon Cynthia Enloe’s critique (2004) of the normative assumptions underlying orthodox International Relations (IR) theories, this article examines the epistemological and ontological foundations of these theories in the context of the Zapatista Army of National Liberation (EZLN) uprising following the implementation of the North American Free Trade Agreement (NAFTA). By integrating critical theory perspectives, it investigates how the valuation of epistemologies within orthodox IR and the perceived immutability of central-peripheral dynamics contribute to political invisibility imposed on peripheral actors. The article contextualizes the relationship between NAFTA and Zapatismo, demonstrating how the neoliberal policies embodied in NAFTA exacerbated Indigenous marginalization, thereby catalyzing the EZLN uprising. Employing Enloe’s evaluation of the EZLN case study, alongside the works of adjacent critical theorists, it demonstrates how critical theory can challenge problem-solving theories’ ontological and epistemological assumptions. It concludes that these assumptions synthesize to impose political invisibility onto peripheral actors, which, if exploited properly, can paradoxically emancipate these actors.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.091 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".