Bibliographic record
Abstract
Abstract The responsibility for hazard governance in Canada is indirectly determined by the division of subjects in the Constitution Act of 1867. This is because emergency management is not a distinct constitutional subject, and therefore it is a matter of assessing which subjects are most related to the practices of emergency management. As a result of this uncertainty both the provincial and federal governments have emergency management legislation. The various provincial legislation and the federal Emergencies Act of 1988 are primarily focused on providing for the use of extraordinary powers as part of crisis response. The federal Emergency Management Act 2008 does take a more comprehensive approach that includes hazard mitigation, but its reach only extends to federal departments. The governance tools most applicable to hazard management, such as land-use planning and zoning, are normally found within the Provinces’ planning or municipal legislation. The planning legislation empowers local authorities to manage development and its interaction with the natural environment. However, these powers are seldom directed towards hazard mitigation. If there is a reference to natural hazards in the planning legislation it is usually to specific risks, such as flooding or slope failure, that are spatially bounded risks to development. This separation of hazard governance in the legislation is reflected in local government practices. In most provinces emergency managers are not required by their respective legislation to incorporate hazard mitigation into community emergency programs. The planning legislation, however, seldom extends the community planner’s mandate for mitigation beyond the concerns for safe building sites and the separation of incompatible land uses. The responsibility to prevent human development from interacting with the extremes of the natural environment, or more succinctly “hazard governance,” is not clearly assigned in Canada.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 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".