Monitoring climate change impacts, Indigenous livelihoods and adaptation: Perspectives from Inuit community of Hopedale, Nunatsiavut, Canada
Bibliographic record
Abstract
The Arctic is at the forefront of climate change, undergoing some of the most rapid environmental transformations globally. Here, we examine the impacts of climate change on the livelihoods in the coastal Inuit community of Hopedale, Nunatsiavut, Canada. The study examines recently evolved adaptation strategies employed by Inuit and the challenges to these adaptations. We document changing sea ice patterns, changing weather patterns and the impact of invasive species on food resources and the environment. Utilising knowledge co-production and drawing upon Indigenous knowledge, we monitor the changes and multiple stresses through direct observations, engagement with rights holders and community experiences to characterise climate risks and associated changes affecting livelihoods. We use both decolonising research and participatory methodologies to develop collaboration and partnership, ensuring that monitoring reflects local priorities and realities while also fostering trust and collaboration. We showcase that monitoring environmental trends involves more than data collection; it includes observing and analysing how environmental changes affect community well-being, particularly in terms of food security, cultural practices, economic activities, mental health, sea ice changes and weather patterns. The paper contributes to a nuanced understanding of Inuit resilience and experiences in confronting climate risks and the broader implications for Indigenous communities confronting climate challenges.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".