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Record W4415270474 · doi:10.1111/capa.70034

<i>Nuna Aliannaittuk Auttuq</i>—Thawing of the Beautiful Lands of Inuvialuit: Lessons for Sensing Policy

2025· article· en· W4415270474 on OpenAlexaffabout
Karla Jessen Williamson, Jen Bagelman, Sarah Wiebe, Maéva Gauthier, Dwayne ‘Atjgaliaq’ Drescher

Bibliographic record

VenueCanadian Public Administration · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsInuvialuit Regional CorporationUniversity of VictoriaUniversity of Saskatchewan
Fundersnot available
KeywordsClimate changeIndigenousFutures contractTraditional knowledgePublic policyHonourGovernment (linguistics)

Abstract

fetched live from OpenAlex

Abstract This article, co‐led by an Inuk scholar, Inuvialuit graduate student, and non‐Indigenous academic co‐investigators, explores the implications of climate displacement research for public administration, policy, and governance, with a specific emphasis on sensing in relation to policy. Drawing on diverse forms of evidence, we highlight the role of storytelling and sensory experience in shaping climate policy. We reflect on the outcomes of a unique gathering, “Changing Climate Conversations,” where Inuvialuit climate change leaders engaged with Environment Canada officials. Through unipkait (Inuit forms of storytelling) we used murals, music videos, and film, to evoke Inuvialuit youth knowledge on climate change in Tuktoyaktuk, Northwest Territories, Canada. The youth deliberations challenged conventional climate discourse, emphasizing the importance of Indigenous knowledge and perspectives in policymaking. Our findings underscore the need for justice‐oriented policies that honour diverse voices and promote ecological and social justice, enacting inclusive policy futures that center Indigenous sovereignty in environmental governance.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.055
GPT teacher head0.409
Teacher spread0.354 · 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 designTheoretical or conceptual
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 routes2
Has abstractyes

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