Rules and Unruliness: Canadian Regulatory Democracy, Governance, Capitalism, and Welfarism
Bibliographic record
Abstract
A critical examination of Canadian regulatory governance and politics over the past fifty years, Rules and Unruliness builds on the theory and practice of rule-making to show why government - the inability to form rules and implement structures for compliance - is endemic and increasing. Analyzing regulatory politics and governance in Canada from the beginning of Pierre Trudeau's era to Stephen Harper's government, the authors present a compelling argument that current regulation of the economy, business, and markets are no longer adequate to protect Canadians. They examine rules embedded in public spending programs and rules regarding political parties and parliamentary government. They also look at regulatory capitalism to elucidate how Canada and most other advanced economies can be characterized by co-governance and co-regulation between governments, corporations, and business interest groups. Bringing together literature on public policy, regulation, and democracy, Rules and Unruliness is the first major study to show how and why increasing unruliness affects not only the regulation of economic affairs, but also the social welfare state, law and order, parliamentary democracy, and the changing face of global capitalism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".