An Agenda for Comparing Local Governance and Institutional Collective Action in Canada and the United States
Bibliographic record
Abstract
As neighboring federal systems, Canada and the United States provide an opportunity to compare institutional collective action (ICA) by proximate local governments. After explaining the importance of understanding local governance in Canada and the United States in comparative context, the ICA framework is used to highlight propositions along two paths of inquiry. First, the ICA framework can be used to compare responses to ICA dilemmas in two distinct systems of local governance, focusing on the comparative instance of use and performance of ICA mechanisms. Second, the ICA framework can be used to analyze collaboration and paradiplomacy across the international border. Deploying the ICA framework for comparative research can improve our understanding of local governance and local government reform in both countries.
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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 | 0.025 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.016 | 0.022 |
| Science and technology studies | 0.018 | 0.022 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| 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".