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Record W4412325471

The value of Inuit participation when conserving the common eider duck in Arctic Canada and Greenland

2015· article· en· W4412325471 on OpenAlexaffabout
Grant Gilchrist, Flemming Ravn Merkel, Christian Sonne, Scott G. Gilliland, Anders Mosbech, Samuel A. Iverson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsEiderArcticThe arcticGeographyValue (mathematics)OceanographyPhysical geographyFisheryGeologyStatisticsBiologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

The northern common eider duck nests in the eastern Canadian Arctic and west Greenland, and migrates to winter in Atlantic Canada and southwest Greenland. The eider is harvested for its meat, feather down and eggs and its ongoing conservation is the shared responsibility of Canada, Greenland, Denmark, and northerners. This presentation will review the meaningful involvement and direct participation of Inuit during many aspects of historical and ongoing eider duck conservation efforts. These include studies that examined the sustainability of harvest, the establishment of new harvest regulations, long term monitoring of breeding colonies in remote coastal locations, reporting on emerging disease epidemics, and ongoing field studies which examine the impacts of polar bear predation under changing sea ice conditions. This presentation will review how working relationships were established between Inuit and scientists, training implemented, and how information was gathered rigorously; all efforts which have contributed to the shared priority of northern eider conservation.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.825

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.003
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.362
Teacher spread0.300 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2015
Admission routes2
Has abstractyes

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