Inuit food security: vulnerability of the traditional food system to climatic extremes during winter 2010/2011 in Iqaluit, Nunavut
Bibliographic record
Abstract
Arctic climate change is an influential food security determinant because varying environmental conditions affect the ability of Inuit to harvest traditional food, thus impacting food security. This case study assesses how climatic extremes during winter 2010/2011 affected the vulnerability of the traditional food system in Iqaluit, Nunavut. This winter was statistically anomalous in terms of environmental conditions throughout the Canadian Arctic, which manifested locally via warmer temperatures and poorer sea ice conditions. The aim of this thesis is to determine whether these conditions impacted the procurement of traditional food and whether this caused food insecurity amongst vulnerable residents at the community level. The main objective is to identify and characterize locally relevant extreme climatic conditions during winter 2010/2011 (exposure), their subsequent effects on Iqaluit's traditional food system with a focus on public housing residents (sensitivity) and coping strategies used for dealing with food-related stresses (adaptive capacity). This mixed-methods approach involves analysis of instrumental records, interviews with local hunters and key informants, as well as surveys with public housing residents. Results show increased environmental stresses to the traditional food system compared to previous years, which negatively impacted hunters' harvests and residents' food supplies. Coping strategies alleviated some stresses, but resilience was particularly impeded for financially insecure households reliant on income support. Overall, the traditional food system was not as vulnerable to climatic extremes as anticipated, as broader social determinants had a greater influence on Inuit food security. However, when poor socioeconomic conditions, such as those associated with public housing, are coupled with poor environmental conditions, such as those experienced during winter 2010/2011, the vulnerability of the traditional food system is even further exacerbated.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".