Inuit adaptability to changing environmental conditions over an 11-year period in Ulukhaktok, Northwest Territories
Bibliographic record
Abstract
ABSTRACT Current understanding of climate change impacts, adaptation and vulnerability among Inuit in the Arctic is relatively static, rooted in the community and time that case studies were conducted. This paper captures the dynamism of Inuit–climate relationships by applying a longitudinal approach to assessing vulnerability to climate change among Inuit in Ulukhaktok, Northwest Territories, Canada. Data were collected in 2005 and 2016 following a consistent methodology and analytical framework. Findings from the studies are analysed comparatively together with longitudinal datasets. The data reveal that many of the climatic changes recorded in 2005 that adversely affected hunting activities have been observed to be persisting or progressing, such as decreasing sea ice thickness and extent, and stronger and more consistent summer winds. Inuit are responding by altering travel routes and equipment, taking greater pre-trip precautions, and concentrating their efforts on more efficient and accessible hunts. Increasing living and subsistence costs and time-constraints, changes in the generation and transmission of environmental knowledge and land skills, and the concentration of country food sharing networks were identified as key constraints to adaptation. The findings indicate that the connections between subsistence activities and the wage economy are central to understanding how Inuit experience and respond to 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 | 0.000 | 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 | 0.001 |
| 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".