International Regulatory Cooperation and the Making of “Good” Regulators A Case Study of the Canada–U.S. Regulatory Cooperation Council
Bibliographic record
Abstract
International regulatory cooperation (IRC), an assortment of governmental techniques for facilitating trade by minimizing the burden on business of variation in international regulations and standards, is an increasingly important component of bilateral and regional free trade agreements. Yet as a practice of global governance, IRC is relatively understudied by critical scholars of neoliberalism and globalization. This thesis enquires into the practices of IRC and the role of state and non-state participants in the Canada-U.S. Regulatory Cooperation Council (RCC). My research draws publicly available accounts of the RCC and earlier bilateral (Canada-U.S.) regulatory cooperation efforts into conversation with the experiences of two dozen RCC participants from government, the private sector and civil society. Applying a governmentality analysis to a case study of the RCC, I conclude that IRC can be understood as a subtle technique for governing the global economy at a distance through the production of "good" (i.e., selfmaximizing) regulators and regulated subjects.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".