Multilevel Governance and Emergency Management in Canadian Municipalities
Bibliographic record
Abstract
Whether it is wildfires in Alberta, widespread flooding in Newfoundland, or massive snowstorms in Nova Scotia, Canadian governments must be prepared to manage a range of emergencies. Many organizations and resources have to be coordinated in emergency management, and the quality of emergency planning has a direct impact on the effectiveness of disaster response. Municipalities have primary responsibility, but emergency management requires authority and resources from all levels of government as well as collaboration with stakeholders from the private and voluntary sectors. Drawing on extensive documentary evidence and many interviews with government officials and stakeholders, Multilevel Governance and Emergency Management in Canadian Municipalities provides a comprehensive assessment of the structure and dynamics of emergency management in Canada. Contributors analyze the role of the federal government, compare policies and governance in three different provinces, and examine approaches to emergency planning in thirteen municipalities of varying sizes. In addition to describing political and legal frameworks, essays investigate how emergency management policies are shaped by the relationships between municipal, provincial, and federal officials, as well as with social interests that are concerned about planning for emergencies. Contributors also assess the quality of emergency management. Despite the growing importance of emergency management, there has been little comparative research on Canadian policy making in this field. Multilevel Governance and Emergency Management in Canadian Municipalities provides insights into how governments have readied themselves for emergencies and how they can better prepare. Contributors include Norm Catto (Memorial University), Malcolm Grieve (retired, Acadia University), Geoffrey Hale (University of Lethbridge), Daniel Henstra (University of Waterloo), Luc Juillet (University of Ottawa), Junichiro Koji (PhD, University of Ottawa), Stephen Tomblin (Memorial University), Lori Turnbell (Dalhousie University), and Robert Young (University of Western Ontario).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".