The Rise of Transnational Governance as a Field of Study
Bibliographic record
Abstract
This article surveys the literature on transnational governance (TNG) and makes the case that the field of international relations (IR) is underestimating its scholarly value. Three main charges are commonly leveled at TNG scholarship, which broadly analyzes the importance for global governance of rules and rulemaking to coordinate nonstate actors across borders: (1) That TNG scholarship is too descriptive and nontheoretical; (2) that TNG research lacks methodological rigor, and thus its claims and conclusions are unreliable; and (3) that TNG itself is peripheral to what really matters for understanding the power dynamics of world politics. These criticisms seemed largely true for much of the early TNG scholarship from the 1970s to the 1990s. Yet, as the authors argue and document, TNG scholarship since 2000 is converging around explaining three “stages” of TNG—rule emergence, selection, and adoption—and increasingly is theoretically innovative, methodologically rigorous, and speaks to concerns that are central to the larger field of IR. Given this, greater attention to TNG by IR scholars, textbooks, and courses offers many rewards.
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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 | 0.015 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".