Early Childhood Development in the Aftermath of the 2016 Wildfires in Alberta, Canada
Bibliographic record
Abstract
The 2016 wildfires in Alberta, Canada, created numerous challenges for families with children under five years of age, due to the limited postdisaster access to early childhood development (ECD) programs, resources, and supports. In the immediate aftermath of the wildfires, families struggled to balance recovery activities with childcare responsibilities, which adversely affected their overall recovery. In this article, we discuss three main challenges experienced by families with young children after the wildfires: inadequate access to childcare services, a lack of availability and funding for ECD programs and resources, and limited long-term recovery support for families. Because of their early developmental stage, young children are especially vulnerable to the adverse effects of a disaster and dependent on their adult caregivers, thus it is essential to understand the unique challenges families face after a disaster. Children's prolonged exposure to the stress of a disaster environment is compounded when parents have limited access to crucial programs, resources, and supports during the most crucial periods of rebuilding and recovery. The findings we report in this article provide insights into the critical role disaster and emergency preparedness and planning play in ECD service delivery and infrastructure, and into the need for recovery efforts to "build back better." We advise all levels of government to consider ECD and the provision of child care to be essential services during natural disasters, crises, and pandemics. We further advise them to make the financial investment needed to ensure sustainable recovery operations, including infrastructure, provision of ECD services, and hiring of educators who can deliver high-quality, affordable early learning and child care in postdisaster environments.
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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 | 0.000 | 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".