“It's Not that Simple”: A Collaborative Comparison of Sea Ice Environments, Their Uses, Observed Changes, and Adaptations in Barrow, Alaska, USA, and Clyde River, Nunavut, Canada
Bibliographic record
Abstract
The Arctic environment, including sea ice, is changing. The impacts of these changes to Inuit and Iñupiat ways of life vary from place to place, yet there are common themes as well. The study reported here involved an exchange of hunters, Elders, and others from Barrow, Alaska, USA, and Clyde River, Nunavut, Canada, as members of a larger research team that also included visiting scientists. Although the physical environments of Barrow and Clyde River are strikingly different, the uses of the marine environment by residents, including sea ice, had many common elements. In both locations, too, extensive changes have been observed in recent years, forcing local residents to respond in a variety of ways. Although generally in agreement or complementary to one another, scientific and indigenous knowledge of sea ice often reflect different perspectives and emphases. Making generalizations about impacts and responses is challenging and should therefore be approached with caution. Technology provides some potential assistance in adapting to changing sea ice, but by itself, it is insufficient and can sometimes have undesirable consequences. Reliable knowledge that can be applied under changing conditions is essential. Collaborative research and firsthand experience are critical to generating such new knowledge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".