Climate Change, Forest Fire Management & Interagency Cooperation in Canada
Bibliographic record
Abstract
Climate change has begun to affect the frequency, intensity, and duration of weather related disaster events. This trend may foster a greater probability of encountering 2 or more disaster events simultaneously, increasing the potential to deplete emergency resources. Using Canadian forest fire management as a focal point, this research has determined the extent to which forest fire resource sharing (resources being equipment, fire fighter teams, planes, etc.) has been able to mitigate the impacts of simultaneous forest fire events induced by climate change. Provincial and territorial forest fire management agencies are responsible for forest fire suppression within their jurisdictions, but when fires exceed their suppression capabilities they may request resources from other agencies using resource sharing agreements including: Compact agreements with American States, other international agreements and agreements initiated through the Canadian Interagency Forest Fire Center (CIFFC). If the potential for simultaneous forest fires is neglected, excess fire activity may overwhelm the resource sharing structure. \n \nA historical analysis, 2 case studies, and a survey were employed to uncover information regarding simultaneous forest fires. Moreover, an examination of other resource sharing disciplines was used to uncover new ways of approaching resource sharing issues. The results of this study show that simultaneous fire events have overwhelmed the resource sharing system (during at least two years 1998 and 2003) and that modifications are needed to prepare for the potential increase in forest fire frequency.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".