Conceptualizing Borders in Cross-Border Regions: Case Studies of the Barents and Ireland–Wales Supranational Regions
Bibliographic record
Abstract
This paper scrutinizes the significance of borders in cross-border cooperation. Since borders are seen here as multilayered constructs that may be either hard or soft, it is asked to what extent they determine the contents of cooperation, and whether they also define the key actors participating in various border crossing processes and projects. By analyzing comparative case studies of the Barents and Ireland–Wales cross-border regions through the layer model of borders and some key ideas of actor-network theory, this paper points out how borders, as lines of demarcation, are of relevance for the forms of cooperation adopted. Cross-border collaboration also transforms borders, making the significance of various layers dynamic in time. Moreover, the paper suggests that cross-border collaboration should be conceptualized as a hybrid of sub-national (local), national, and supranational policies and objectives.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".