“We Need to Do Something About This”: Children and Youth’s Post‐Disaster Views on Climate Change and Environmental Crisis
Bibliographic record
Abstract
Research is increasingly uncovering the many ways that individuals affected by disasters change their environmental views in response to their direct experience of such catastrophic events. There is a growing body of research that focuses on adults’ environmental views, revealing that they often remain complacent toward environmental problems even after experiencing a disaster. However, very little research examines whether and to what extent children and youth’s environmental views shift and change after experiencing a disaster. This article fills this gap by specifically focusing on the environmental views and practices of 83 children and youth between the ages of 5 and 17 years who experienced the 2013 Southern Alberta Flood, the costliest flood disaster in Canadian history. Findings suggest that disaster catalyzes a process of reflexivity in children and youth. Experiencing the flood prompted children and youth to think more about the environment than prior to the flood; contemplate larger environmental issues, such as climate change, as the root cause of the locally experienced flood; and take action, as well as call others to action, to ameliorate climate and environmental problems in their own lives and communities. We discuss the implications these findings have for environmental and disaster education, policies, and practices.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".