Introduction: Border Temporalities in and Beyond Europe
Bibliographic record
Abstract
How are borders and time related? Are borders shifting state lines enshrined in history, the landscape, and cultural heritage? Are borders places where new understandings of time and space can be formed? Are temporalities of borders the material appearance, transformation, and disappearance of borders or the social practices which leave us with traces of times, tidelines, phantom, or ghost borders? Have we paid enough attention to the experiences of people from different ages passing borders? This special section of Borders in Globalization Review presents twelve articles developed from papers presented on the conference on “Borders in Flux and Border Temporalities in and beyond Europe”, which was organised by the Luxembourg Centre for Contemporary and Digital History (C2DH), the Transfrontier Euro-Institut Network (TEIN), and the Franco-German Jean Monnet Center of Excellence in cooperation with the UniGR-Center for Border Studies and Borders in Globalization (BIG) on 15 and 16 December 2022 in Belval, Luxembourg. The conference examined the temporal dimension of borders, borderlands, and border regions. The articles shed light on temporalities of borders by exploring the relationship between temporalities—in their broadest sense, understood as the way time is experienced and lived—on the one hand, and border practices, border discourses, and border regimes on the other. They focus on four approaches: the past, the present, the future and borders, diachronic studies of borders and border regions, age and borders, and new understandings of time and space at the border. Keywords: borders; temporalities; border temporalities; Europe.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.002 |
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".