Escaping the International Governance Dilemma? Incorporated Transgovernmental Networks in the European Union
Bibliographic record
Abstract
This article investigates the role of transgovernmental networks of national regulators in addressing collective action problems endemic to international cooperation. In contrast to recent work on transgovernmental actors, which emphasizes such networks as alternatives to more traditional international institutions, we examine the synergistic interaction between the two. Building on the broader premise that patterns of “dual delegation” above and below the nation‐state enhance the coordinating role of networks of national agencies in two‐level international governance, the article examines the formal incorporation of transgovernmental networks into European Union (EU) policymaking. The focus on authoritative rule‐making adds a crucial dimension to the landscape of EU governance innovations while connecting to the broader study of transgovernmental networks in international governance. The article develops an analytical framework that maps these incorporated networks across different sectors in terms of function, emergence, and effectiveness. Two case studies of data privacy and energy market regulation are presented to apply and illustrate the insights of this mapping.
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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 | 0.019 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.003 |
| 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".