Bibliographic record
Abstract
Abstract: Joint cabinet meetings are increasingly used for inter-governmental dialogue, at both international and sub-state levels. Provincial governments in western Canada, in particular, have employed the joint cabinet meeting format, and, between 2003 and 2009, nine such joint cabinet meetings were held. The resulting inter-provincial collaboration at these meetings produced over thirty inter-provincial agreements. Using the details of these particular joint cabinet meetings as a case study, this article considers three questions: First, why do governments hold joint cabinet meetings? Second, are joint cabinet meetings effective mechanisms for inter-governmental policy-making? And, third, particular to the Canadian context, what are the implications of joint cabinet meetings for federalism and democracy? The author argues that joint cabinet meetings are designed to build relationships and trust between governments and to allow a “whole-of-government” approach for inter-governmental policy-making. The joint cabinet meeting model appears to facilitate expedient inter-governmental policy-making, but the effectiveness of the resulting policies depends on the political will of the participating governments. Furthermore, in the Canadian context, joint cabinet meetings have the potential of reinforcing regionalism and the undemocratic tendencies associated with executive federalism.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".