Transborder Spaces and International Relations: Epistemological Turns and Methodological Strategies
Bibliographic record
Abstract
From the “northern” and state-centric perspective, there are no borders without international relations and no international relations without borders. Paradoxically, the areas surrounding borders, the transborder spaces, have received little attention from the traditional paradigms of the International Relations (IR) discipline. Two factors have been critical to this phenomenon: the traditional agenda of the discipline related mainly to “northern” concerns, namely Western Europe and North America, and epistemological positions based on state logic that exclude other regions and dynamics. This article analyzes this paradox from a Latin American perspective and explains how transborder spaces are relevant for IR analysis in this region. Finally, it builds on the discussions on the epistemological turns in the IR discipline to propose two strategic and complementary methods to integrate and investigate them: the comparative method and multiscalar imbrication.
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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 | 0.033 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.008 | 0.066 |
| Scholarly communication | 0.021 | 0.032 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.006 |
| 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".