Anomalous climatic conditions during winter 2010–2011 and vulnerability of the traditional Inuit food system in Iqaluit, Nunavut
Bibliographic record
Abstract
ABSTRACT This study examines how climatic extremes during winter 2010–2011 affected the traditional food system in Iqaluit, Nunavut. This winter was anomalous throughout the Canadian Arctic, and manifested itself locally by warmer temperatures and decreased ice coverage. Drawing upon in-depth interviews with hunters (n = 25), a fixed question survey with public housing residents (n = 100), as well as analysis of remotely sensed sea-ice charts and temperature data from the Iqaluit weather station, this work identifies and characterises the extreme climatic conditions experienced, their subsequent effects on Iqaluit's traditional food system, and coping strategies used for dealing with food-related stresses. The results show increased environmental stress on the traditional food system compared to previous years. Freeze up occurred 59 days later than the average for the 1982–2010 period, while mean annual temperatures were 4.9ºC higher than the climatological mean, which negatively impacted hunters’ harvests and residents’ food supplies. Coping strategies alleviated some stresses, but adaptability was limited for financially insecure households reliant on income support. The study shows that when challenging socioeconomic conditions, such as those associated with public housing, are coupled with significant environmental stress, such as experienced during that winter, the vulnerability of the traditional food system is exacerbated. We suggest that winter 2010–2011 can be used as an analogue for exploring future food system vulnerabilities, with climate models projecting similar conditions in the coming decades.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".