Being on Land and Sea in Troubled Times: Climate Change and Food Sovereignty in Nunavut
Bibliographic record
Abstract
Climate change driven food insecurity has emerged as a topic of special concern in the Canadian Arctic. Inuit communities in this region rely heavily on subsistence; however, access to traditional food sources may have been compromised due to climate change. Drawing from a total of 25 interviews among Inuit elders and experienced hunters from Cambridge Bay and Kugluktuk in Nunavut, Canada, this research examines how climate change is impacting food sovereignty and health. Our results show that reports of food insecurity were more pronounced in Kugluktuk than Cambridge Bay. Participants in Kugluktuk consistently noted declining availability of preferred fish and game species (e.g., caribou, Arctic char), a decline in participation of sharing networks, and overall increased difficulty accessing traditional foods. Respondents in both communities presented a consistent picture of climate change compounding existing socio-economic (e.g., poverty, disconnect between elders and youth) and health stressors affecting multiple aspects of food sovereignty. This article presents a situated understanding of how climate change as well as other sociocultural factors are eroding food sovereignty at the community-scale in the Arctic. We argue that a communal focus is required to address resilience and adaptation at the local level through programs that protect the local cultural knowledge, traditional ways of life, and indigenous sovereignty to reduce the severities of food insecurity in the Arctic stemming from climate change.
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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 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 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".