Perception of Immigrant Communities on Adaptability to Climate-induced Risks and Disasters: A Study on Turkish-Canadian Immigrants in Calgary
Bibliographic record
Abstract
Background: Climate change brings uneven implications not only to countries around the world but even to the people living in the same country based on their socio-economic status, access to resources, participation in the decision-making process, and so forth. Climate change affects not only developing countries, but it also affects the developed countries. As a developed country, Canada, especially the Western region of Canada, is observing climate-induced risks and hazards. This Western region is also home to many people with immigrant status, making them more vulnerable. Therefore, this study aims to understand how the immigrant communities (Turkish-Canadian) define the climate change impacts, how they translate their perception to develop adaptation strategies, and whether they take part in the climate decision-making process developed by the City of Calgary. Methods: In this research, we will employ the relational theoretical approach to explore how the Turkish-Canadian communities experience climate risks and disasters and how their socio-cultural knowledge helped them develop adaptation strategies to cope with climate risks and disasters. Through this relational approach, we will conduct 15 in-depth interviews using a non-structured interview guide. The interview will be transcribed into themes and sub-themes, leading to interpretative thematic analysis. Potential Outcomes: The study results show that the vulnerability of Turkish-Canadian communities intensified due to their intersectional positionality, i.e., immigrant status in Calgary and systematic inequality, which limited their access to government-led adaptation policies and resources. The results explore that the members of this community use various adaptive mechanisms to cope with climate-induced risks and disasters. Conclusion: Although there are some studies on immigrant communities and their adaptation challenges, there is a gap in how Turkish-Canadian immigrants perceive climate-induced disasters and the barriers that limit their adaptability to the risks and disasters. Therefore, this study's results will be helpful for researchers and policymakers to develop a holistic approach to fully delineate the climate risks and disasters and minimize structural inequality, increase awareness, build resilience, and engage all the racialized communities in the state-led adaptation strategies.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".