A Governance Theory for Cross-Border Regions: Identifying Principles and Processes with Grounded Theory
Bibliographic record
Abstract
The rise of governance in border studies has become an opportunity to increase efficiency, generate better institutional arrangements and reduce the gap between theory and practice. However, the multiplicity of theories where cross-border governance can be placed, the lack of consensus on concepts and the multiple disciplines that can be used for studying it have increased the need of more comprehensive theoretical frameworks. From an evolutionary-constructivist approach, this paper explores the principles and processes behind cross-border governance evolution through a Grounded Theory methodology based on 49 interviews. The proposed theory identifies four principles – shared experience, Nation State construction, scale difference and notions of power–, defining governance as a mean and result of the territorialization of cross-border actors’ knowledge construction and power concentration at different levels, sectors and scales, based on five on-going processes – knowledge creation, articulation of relationships, decision-making, implementation & management and appraisal of results –.
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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 | 0.013 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".