Bibliographic record
Abstract
Coastal fishermen and whalers on the island of Qeqertarsuaq in Disko Bay, west Greenland, have relied on the harvest of marine resources for the continuation of livelihoods across the generations. More recently, however, Qeqertarsuarmiut and other Inuit residents in other parts of the circumpolar North have increasingly been portrayed as somehow more ‘ exposed’ or ‘ vulnerable’ victims located on the frontline of a geographically determined global crisis narrative about climate change, which inadvertently ignores the reality of coastal livelihoods in the Arctic today. Qeqertarsuarmiut often narrate a different story about their experiences with environmental changes, which is instead rooted in their continued familiarity and engagement with non-human agents (such as winds, sea ice and marine mammals) as these are encountered during seasonal harvesting efforts along the coast. So while environmental fluctuations are certainly observed, interactions with a familiar coastal environment, nevertheless, continue to foster a relationship predicated on an enduring patience and concomitant flexibility towards shifting ice conditions, local weather vagaries and the moods of non-human agents rather than risks or vulnerable exposures.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.008 |
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".