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Record W3012388727 · doi:10.1002/wat2.1433

Water, ice, and climate change in northwest Greenland

2020· article· en· W3012388727 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWiley Interdisciplinary Reviews Water · 2020
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeographyOceanographyClimate changeArcticFjordSea iceFisheryGeology

Abstract

fetched live from OpenAlex

Abstract Along the coastal areas of northwest Greenland, sea ice is crucial to people's livelihoods. People in the region have long depended on hunting marine mammals such as seals; walrus; narwhal, beluga, fin, and minke whales; and polar bears, as well as fishing for fjord cod, Greenland halibut, salmon, and Arctic char. Terrestrial animals such as reindeer and Arctic foxes have also been of some importance, as have musk ox in some areas. However, the effects of a changing climate on the marine environment are stark, immediate, and tangible. Ice is melting, and coastal waters are warming. Sea ice, glaciers, coastlines, and seas have become sites and objects for new forms of environmental governance shaped by ideas of unique and fragile ecosystems under threat at a moment of planetary crisis. Conservation organizations frame the Arctic as a zone of climate change crisis and have launched campaigns—underpinned by narratives of ruination—to protect what are termed last areas of ice. However, Inuit organizations are also working to ensure that environmental governance and conservation policymaking do not exclude local communities in the region and are campaigning for protected marine areas in which wildlife management systems and community‐based monitoring take note of indigenous rights and incorporate indigenous knowledge. This article is categorized under: Science of Water > Water and Environmental Change Human Water > Rights to Water Human Water > Water Governance Water and Life > Conservation, Management, and Awareness

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.004

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.

Opus teacher head0.082
GPT teacher head0.388
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it