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Record W4405130085 · doi:10.1139/facets-2024-0021

Inuit perspectives on climate change and well-being: a comparison between urban and remote communities in the Arctic

2024· article· en· W4405130085 on OpenAlexafffundvenueabout
Annabe U. Marquardt, Andrew S. Medeiros

Bibliographic record

VenueFACETS · 2024
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsYork UniversityDalhousie University
FundersCrown-Indigenous Relations and Northern Affairs CanadaDalhousie University
KeywordsClimate changeArcticGeographyThe arcticEnvironmental planningPhysical geographyEnvironmental resource managementEnvironmental scienceOceanographyGeology

Abstract

fetched live from OpenAlex

The generational knowledge of weather and climate is a foundational component of subsistence for Inuit in the Arctic. This knowledge is now challenged by the reality of anthropogenic climate change at a pace that, for Inuit, is impeding fundamental aspects of life in a single generation. To better understand how climate change moderates relationships between Inuit communities and the ecosystem services they rely on, the literature on how climate change is perceived in the circumpolar Arctic was systematically reviewed. The perspectives of Inuit as described in 75 studies were contrasted with those queried from a series of semi-structured interviews with 16 residents of Iqaluit, Nunavut. Within the literature, the themes most frequently mentioned in remote communities were concerns arising about the environment, community, and health. However, the inverse was true for studies that focused on urban communities. Participants from the semi-structured interviews described how colonialism still shapes knowledge translation, which has lasting effects on Arctic climate literacy for Inuit and non-Inuit. As such, an academic knowledge gap in the colonial context in which climate change operates was identified, which requires a way forward that can lead to improvements in the social context for Inuit.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.096
GPT teacher head0.395
Teacher spread0.299 · 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 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

Citations0
Published2024
Admission routes4
Has abstractyes

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