Living with uncertainties: Qeqertarsuarmiut perceptions of changing sea ice
Bibliographic record
Abstract
In Qeqertarsuaq on Disco Island, west Greenland, residents continue to rely on sea ice for the harvest of maritime resources across the Arctic seasons. Sea ice is important to local households because it represents an essential platform for everyday harvesting efforts along the coast. The article considers coastal dwellers' ways of engaging with environmental forces (such as winds, currents, and sea ice), in a time where climate change crisis narratives feature Inuit populations as increasingly ‘exposed’ victims on an envisioned ‘front-line’ of global warming. Since melting glaciers and ice remain the focus of climate crisis-driven narratives, which inevitably obscure the more complex engagements that abound locally, the article considers local experiences that reflect underlying socio-environmental relations. These relations are expressed through Qeqertarsuarmiut narratives that reflect interactions with a familiar environment and suggest how locals engage with an environment that has always been perceived as lively, shifting, and ever changeable. These coastal narratives reflect the complexities of local livelihoods in ways that run counter to the dominant crisis narratives about Arctic climate change. By focusing on sea ice and how it is represented in environmental change science narratives, and conversely, what it means to a Greenlandic coastal community, the article explores alternative receptions of climate change in Qeqertarsuaq.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.020 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".