New risks, New Strategies: Greenlandic Inuit Responses to Climate Change.
Bibliographic record
Abstract
INTRODUCTION: As climate change accelerates, its effects are especially pronounced in the Arctic region. The Arctic's indigenous people are facing increasing challenges, most notably their ability to harvest food resources. Changes in sea-ice conditions related to climate change may be increasing the risk of injuries during travel on ice for Greenlandic Inuit hunters and fishers. METHODS: Data collection included participant observation, informal interviews, and formal semi-structured interviews. Participants included male hunters and fisherman ( n = 19) and women who travel on sea ice ( n = 8). RESULTS: Observations of climate change by Greenlandic Inuit include changing wind and snow patterns; the sea ice that is forming now is not as solid or as thick, making travel especially dangerous; and there is more open water and less sea ice; variation in local weather patterns, such as an increase in precipitation and fog, and large storms develop at an increasing rate. Many fishermen observe that halibut is being replaced by cod, which is unusual but not surprising considering that cod is a warmer water fish than halibut. In addition, in general there are fewer fish. Others report that there are more pilot whales and killer whales in Uummannaq and an increased number of humpback and narwhal whales in Ilulissat. Acceptable risks/injuries include frostbite and losing fingers. Younger generations are hunting less. The shift from the traditional mode of teaching is seen by older hunters as placing younger Inuit at greater risk of injuries while traveling on the sea ice. Many hunters and fishers are seeking wage employment in other communities.
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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 | 0.014 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".