A Qualitative Examination of the Impact of the 2021 Floods and Fires: Experiences, Emotions, and Future Uncertainties among Youth in Merritt, British Columbia
Bibliographic record
Abstract
Global warming is expected to increase the frequency and severity of extreme events, disproportionately affecting vulnerable populations, with youth at heightened risk of climate-related psychological stress. However, research on young people in climate emotions literature is underrepresented. Understanding youth climate emotions is crucial for helping them develop effective coping strategies and fostering a sense of hope, which can lead them towards pro-environmental behaviors. With young people constituting approximately one-fifth of the world’s population, their involvement in climate action is critical. The main objective of this qualitative study is to explore the impact of the floods and fires of 2021 among youth in Merritt, British Columbia. In-person and remote interviews were conducted with five youth aged 17 to 29, two secondary school instructors, and four parents. Through thematic analysis within a social constructivist framework, data from the interviews were coded according to three overarching themes: Extreme Event Experiences, Climate Emotions, and Future Uncertainties. The analysis revealed several key insights. First, municipalities may be inadequately prepared for extreme events, resulting in significant disruptions to daily life for community members. Second, extreme events and climate change can intensify future uncertainties and evoke strong climate emotions, including eco-anxiety, grief, and loss. Third, community connectedness emerged as a crucial emotional coping mechanism for youth. The findings also highlight that youth participants advocate for enhanced climate change adaptation efforts in Merritt and across Canada, specifically calling for expanded climate change education and a more inclusive approach to climate governance that incorporates the voices of youth, rural, and Indigenous populations.
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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 | 0.000 |
| 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) | 0.001 | 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".