Social, Economic and Health Effects of the 2016 Alberta Wildfires: Pediatric Resilience
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
The 2016 Alberta wildfires resulted in devastating human, socio-economic, and environmental impacts. Very little research has examined pediatric resilience (5–18 years) in disaster-affected communities in Canada. This article discusses the effects of the wildfire on child and youth mental health, community perspectives on how to foster resilience post-disaster, and lessons learned about long-term disaster recovery by drawing on data collected from 75 community influencers following the 2016 Alberta wildfires. Community influencers engaged in the delivery of services and programs for children, youth, and families shared their perspectives and experiences in interviews ( n = 30) and in focus group sessions ( n = 35). Using a purposive and snowball sampling approach, participants were recruited from schools, community organizations, not-for-profit agencies, early childhood development centers, and government agencies. The results show that long-term disaster recovery efforts require sustained funding, particularly in meeting mental health and well-being. Implications and recommendations are provided.
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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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