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Record W4321238598 · doi:10.3389/feart.2023.1076774

Indigenous self-determination in cryospheric science: The Inuit-led Sikumik Qaujimajjuti (“tools to know how the ice is”) program in Inuit Nunangat, Canada

2023· article· en· W4321238598 on OpenAlex
L. Beaulieu, Andrew Arreak, R. Holwell, S. Dicker, O. Qamanirq, L. Moorman, K. Wilson, Rebecca A. Segal, S. Crichton, Trevor Bell

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFrontiers in Earth Science · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMount Royal UniversityOkanagan University CollegeMemorial University of NewfoundlandUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaThe Arctic Eider Society
FundersEnvironment and Climate Change Canada
KeywordsIndigenousSea iceArcticGeographyTraditional knowledgeRemote sensingMeteorologyOceanographyGeologyEcology

Abstract

fetched live from OpenAlex

Inuit have lived along the shoreline of the frozen Arctic Ocean for centuries. Our wellbeing, culture, and identity are closely tied to safe and dependable ice access. As the ice becomes more unpredictable with a changing climate, Elders and experienced ice users recognize that their accumulated wisdom and experience of safe ice travel—their Inuit Qaujimajatuqangit ( IQ ; a term used to describe Inuit knowledge and values) of sea-ice—must be shared and applied in new ways for the benefit of younger generations. Here we illustrate one such application that enables young Inuit scientists to learn and apply the tools and skills they need to create operational community-scale sea-ice maps ( Sikumik Qaujimajjuti , or “tool to know how the ice is”). Our cross-cultural partnership approach—called the Sikumiut-SmartICE model—focuses on developing the skills of young Inuit to create the maps, while non-Indigenous partners provide mentorship, tools, and training. Our novel maps incorporate culturally relevant ice terminology, on-ice monitoring data and observations, and IQ -grounded interpretations of ice features and travel conditions from near-real time optical and radar satellite imagery. The layers of data are integrated into a local GIS, enabling the creation of maps that reflect local and seasonal travel patterns and meet our information needs in information content, extent and frequency. The maps are posted and shared through social media platforms preferred by the community. The maps are a trusted source of travel information because they are made by one of our own, using local language, experience, and IQ . The Sikumik Qaujimajjuti program illustrates the incredible potential of Indigenous self-determination in cryospheric science when the scientific merit of IQ is fully recognized, when Indigenous researchers are able to access technologies and training to apply their IQ , and when non-Indigenous partners mentor and support young Indigenous scientists.

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)0.007
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.011
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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