Border Renaissance in a Time of Border Perplexity? The Question of Renaissance/Renascence in a Post-Globalization World
Bibliographic record
Abstract
This essay explores questions of why and how there can be a border renaissance in a time of border profusion and confusion. Are we simply witnessing border renascence, a revival of the statist boundary, despite globalization? Or is the renaissance of the border new growth arising from incomprehension of the border in the 21st century? With reference to research in North America, Southeast Asia, and Europe, this article examines the entangled state of the border to discern what is unaccountable from what is complicated and to differentiate rebirth and revival of classical border thinking from that which addresses the perplexity of borders. In my view, a renaissance in border studies flirts with a return to the archaic through definition and explication of borders everywhere. A true renaissance in border studies must confront the entangled state as process, spirit, style, form, and other influences at once rooted in the classical and portrayed and performed in a post-globalization era of border rediscovery. The goal of this essay is to confront the notion of border renaissance, not to diminish the concept, but to reveal the fuller meaning and impact of border rebirth and revival.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".