Relational dynamics under close supervision: Examining transnational cooperation in regulatory oversight
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The increasing institutionalization of regulatory oversight worldwide has not resulted in the creation of numerous formal channels of transnational regulatory oversight cooperation. Despite its puzzling nature, this circumstance has barely attracted scholarly attention. Additionally, the study of cooperation across transgovernmental regulatory networks with actors having low autonomy from central governments remains under‐researched. We fill these literature gaps by applying insights from the policy networks literature to identify drivers of transnational regulatory oversight cooperation. Combining Exponential Random Graph Models with semi‐structured interviews, we show that commonalities in administrative traditions drive cooperation. Innovative bodies become sources of best practices. Conversely, exchanges between countries with similar regulatory oversight settings or preferences are rare, perhaps due to their low independence from their political principals. These results suggest that regulatory oversight actors use relational opportunities and general country features as cues for transnational cooperation, instead of adopting strategic partnerships with better matches.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it