Bibliographic record
Abstract
Governments in Canada must work through the system of intergovernmental relations to address an increasing array of policy problems of concern to Canadians.This entails working together within, between, and across state boundaries and state-society relations.Although our federal system has demonstrated some adaptability and durability in its intergovernmental policy capacity (IPC) over time, intergovernmental relations have been marked by disputes and considerable lack of progress.Collaboration has occurred, but only sporadically, and policy problems in economic, social, and environmental sectors, as well as the increasing inter-relatedness of our "networked" world, highlight the need for improved IPC.Our research focuses on the need to more fully understand the interface of federalism, public policy, and public administration and to use what we learn there to analyze key political and administrative ideas, institutions, actors, and relations which facilitate or impede IPC.Our purpose has been to collect and assess recommendations for improving IPC, and to disseminate the results of the research through public seminars and through the publication of articles and, now, this book on IPC.Our methodology, rooted in a neo-institutionalist and interpretive analysis, involves a combination of a survey and interviews of intergovernmental officials working in intergovernmental relations and finance central agencies, and in environment, trade, and health ministries, as well as a review of primary and secondary documents.The survey and interviews collected baseline data on the demographic profiles of intergovernmental officials and their perceptions on factors enhancing and inhibiting IPC, as well as on recent and future developments in intergovernmental relations; and recommendations xvi Preface for future intergovernmental challenges.This was supplemented with existing government data and scholarship in the fields.Overall, this work has resulted in a better understanding of IPC in Canada.It identifies the many different factors which enhance and inhibit IPC across policy sectors and jurisdictions, and contains recommendations from a cross-section of intergovernmental officials.The authors supplement this set of important recommendations with others which have been made in the federalism, public policy, and public administration literature, resulting in an innovative study which provides a needed synthesis of the literatures of the field, and hopefully a valuable source for academics, government officials, students, and stakeholders alike.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.461 | 0.212 |
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".