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Record W4413820541 · doi:10.1139/as-2025-0024

Nunavimmiut Knowledge of climate change and its impact on environment, wildlife, and harvest activities in Hudson Strait, Nunavik

2025· article· en· W4413820541 on OpenAlexafffundvenueabout
Mathilde Lapointe St‐Pierre, Peter H. May, Barrie Ford, Kyle H. Elliott, Murray M. Humphries

Bibliographic record

VenueArctic Science · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMcGill UniversityMakivik Corporation
FundersArcticNet
KeywordsWildlifeClimate changeGeographyEnvironmental protectionPhysical geographyEnvironmental resource managementEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

Climate change is impacting the Arctic more than other ecosystems, and, within the Arctic, some regions are being affected more than others. Studying areas of concentrated climate change impact in the Arctic and understanding how these focused changes are impacting northern communities is an important knowledge priority. The Hudson Strait, located between Nunavik and Nunavut in the eastern Canadian Arctic, is the entry point for the Atlantification of Hudson Bay and eastern Arctic Ocean and is a region of critical importance to Nunavimmiut, the Inuit of Nunavik. We documented Nunavimmiut Knowledge on the impacts of climate change on the environment, wildlife, and Inuit harvest activities through semi-directed interviews with 30 local experts in five communities located along the Hudson Strait and northern Hudson Bay. Nearly all local experts we interviewed observed that climate change has affected the seasonal timing and thickness of sea ice around communities. Local experts also reported associated changes in wildlife abundance and distribution, with increased sightings of Atlantic walrus ( Odobenus rosmarus rosmarus Linnaeus, 1758) and polar bears ( Ursus maritimus Phipps, 1774) and decreased observations of seals ( family Phocidea). Environmental change in the Hudson Strait is impacting Inuit life and food security, accelerating the need to align research and management with local priorities.

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 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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.046
GPT teacher head0.392
Teacher spread0.346 · 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 teacher head, not a consensus.

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
Published2025
Admission routes4
Has abstractyes

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