Beyond Legalism? Policy Ideas, Implementation Styles and Emulation-Based Convergence in Canadian and U.S. Environmental Policy
Bibliographic record
Abstract
Past studies of the dynamics of U.S.-Canada environmental policy and policy-making have found little evidence of ‘weak’ convergence in this sector; that is, of Canadian policy moving towards the U.S. model of adversarial legalism, an implementation style based upon procedural policy instruments such as action-forcing statutes, citizen suits, and judicial activism. However, recent efforts at de-regulation and the reformation of government in the U.S., and moves towards multi-stakeholder policy-making in Canada, have altered the standard against which trends towards Canadian^ American convergence must be assessed. These reforms have moved the U.S. environmental regulatory system closer to that existing in Canada, in which regulations and other elements of the environmental regime are developed through negotiation rather than litigation. Since Canadian environmental implementation has also been altered over the same period, however, it is argued that a form of ‘strong’ convergence is emerging, in which both countries are moving not towards each other but towards a third, common, style, that associated with the development of self-regulation and voluntary initiatives under the influence of New Public Management ideas and principles.
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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 | 0.033 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.020 | 0.036 |
| Scholarly communication | 0.022 | 0.009 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| 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".