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Record W2770007846 · doi:10.3354/cr01501

Ice over troubled waters: navigating the Northwest Passage using Inuit knowledge and scientific information

2017· article· en· W2770007846 on OpenAlexaffabout
Bindu Panikkar, Benjamin Lemmond, Brent Else, M. S. Murray

Bibliographic record

VenueClimate Research · 2017
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeographyArcticSea iceOceanographyArchipelagoArctic ice packPhysical geographyArchaeologyGeologyMeteorology

Abstract

fetched live from OpenAlex

Sea ice throughout the Arctic is undergoing profound and rapid change. While ice conditions in the Canadian Arctic Archipelago have historically been more stable than conditions in the open ocean, a growing body of evidence indicates that the major thoroughfares in much of the western and central Canadian Arctic, including the Northwest Passage, are increasingly vulnerable to climatic forcing events. This is confirmed by the observations of Inuit elders and experienced hunters in the communities of Cambridge Bay, a hamlet along Dease Strait, and Kugluktuk, a hamlet situated at the mouth of the Coppermine River where it meets Coronation Gulf. People in these hamlets now face new navigational challenges due to sea-ice change. Navigation practices described by elders and hunters reflect an intimate knowledge of the land and ice topography, currents, and weather conditions for hundreds of kilometers around their communities, although people reported increasing unpredictable weather and ice conditions, making travel more treacherous. Many emphasized the importance of traditional knowledge and survival skills as necessary to adapt to ongoing and impending changes. They expressed particular concern that younger generations are untrained in traditional navigation practices, landscape- and weather-reading abilities, and survival practices. However, elders and hunters also stressed the need for more localized weather information derived from weather stations to help with navigation, as current weather and ice conditions are unprecedented in their lifetimes.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.401

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.191
GPT teacher head0.519
Teacher spread0.328 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2017
Admission routes2
Has abstractyes

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