Bibliographic record
Abstract
In the coastal areas of Northwest Greenland, water, ice and land intermingle with the lives and trajectories of humans and animals, take on a multitude of shapes and forms, and give rise to a complexity of social relations. However, as in other parts of the Arctic, the effects of climate change are increasingly evident. Sea ice cover during winter and spring is less extensive than people living in the region today have known it to be, while icebergs calve from tidewater glaciers at arate faster than they and scientists have previously observed. Glacial ice mass is diminishing and increased meltwater runoff from glacial fronts affects water temperature, ocean depths and circulation patterns, as well as the formation and thickness of sea ice and the movements of marine mammals and fish. These changes have profound implications for local livelihoods and mobilities, the wider regional economy, and human-animal interactions. In this article, I consider what some of the effects of climate change mean for people and their surroundings in Northwest Greenland’s Upernavik area and draw attention to liquescence as a counter to the “ice is melting” narrative that typically understands climate change as liquification. While the scientific monitoring of sea ice, glacial ice loss, and surface melt on the inland ice in the Upernavik region—and in the wider Northwest Greenland area—is well established, and contributes to the regular updating of state of the ice reports for the Arctic, little attention has been given to what these changes to ice and water mean for people and for human and non-human relational ontologies. Thinking of this in terms of liquescence, rather than liquification is a way of moving toward a deeper appreciation of people’s experiences and sense-making of the changes happening to them and to their surroundings as affective, sensorial and embodied.
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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 | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.075 | 0.019 |
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".