Expecting the Unexpected: Disaster Vulnerability and Emergency Planning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As climate change is projected to increase the frequency and severity of extreme weather events, communities face challenges to adapt and prepare. To address the increasing risk of natural disasters, governments have developed climate adaptation and emergency management reports and post-incident recommendations. However, implementing local measures can be daunting due to limited human and financial resources. The research question that this project investigates is: what is the compatibility of disaster risk reduction guidelines and community-identified priorities in a Southern Alberta community? As Indigenous communities in Canada continue to be disproportionately impacted by natural disaster events and account for almost 1/3 of wildfire evacuations, this report examines how community-focused risk reduction programming can help reduce disaster impacts. Through a review of historical disaster events, recent Canadian initiatives and a qualitative case study completed with Siksika Nation’s Emergency Management team, this report highlights community-specific factors that can inform community emergency management planning.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it