Analyses and Implications of Hazard Management Collaborations in U.S. and Canada
Bibliographic record
Abstract
The purpose of this study is to draw implications from case studies of collaborations between independent administrative sectors for effective hazard management. In order to investigate mutual collaboration cases among state governments in regional scales, we selected cases in U.S. and Canada. Our research results are follow. First, hazard management needs to be designated and conducted as a primary regional function. Second, an organization of separate regional institution can be a political and administrative authority. Third, agreement led by local government for mutual assistance can be seen as a coexistence model for effective hazard management. Based on these results, we draw the following implications for policy improvement. Based on the findings, it is necessary to establish a regional insititution for systematic hazard management and to build a field-centered legal system for regional hazard management. Futhermore, in order to apply the implications from the studies of international cases to our national legal systems it is important to have a consensus among the key stakeholders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".