Community Adaptation to Climate Change in Ulukhaktok, Canada
Bibliographic record
Abstract
This paper presents research that examined the sensitivity and adaptive capacity of people and their livelihoods to climate change in Ulukhaktok, NWT, Canada. The case study identifies climate conditions and hazards that community members are currently dealing with, the adaptive strategies employed to deal with these hazards, the effectiveness of these adaptive strategies and the capacity of the community to deal with future climate change. As a result of climate-driven changes and changing livelihoods, community members in Ulukhaktok are sensitive to climate hazards associated with harvesting activities including, travel routes on the sea-ice, land and ocean, and changes in the health and distribution of wildlife species important for subsistence. These changes have implications for food security, household income, health and culture. Community members are currently demonstrating significant adaptability to changing conditions by harvesting alternative species of wildlife, being flexible in harvesting activities (e.g. timing, travel routes), using technologies (e.g. GPS, VHF radio, weather forecasts) to ensure safe travel, and supplementing country foods with store-bought foods. However, the capacity to adapt differs amongst community members as does the desirability of adaptation options. Institutional support (e.g. financial aid and harvesting resources) and social networks (e.g. food sharing, knowledge sharing, equipment sharing) are identified as key components of adaptive capacity. These sources provide strategic opportunities to integrate adaptation planning to climate change within existing institutions and community networks.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".