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Record W4414253729 · doi:10.1080/22423982.2025.2560062

The Inuit Holistic service delivery model: a decolonised approach to community wellness in Nunavut

2025· article· en· W4414253729 on OpenAlexafffundabout
Gwen Healey Akearok, Lauren Nevin, Ceporah Mearns, Janna MacLachlan, Nancy Mike

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsNunavut Arctic CollegeNOSM UniversityQaujigiartiit Health Research Centre
FundersPublic Health Agency of Canada
KeywordsIndigenousScholarshipService delivery frameworkService (business)Community engagementDelivery systemArcticHealthcare deliveryThe arctic

Abstract

fetched live from OpenAlex

This paper examines the development and implementation of the Inuit Holistic Service Delivery Model, designed by Qaujigiartiit Health Research Centre and currently being piloted through the Inuusirvik Community Wellness Hub in Iqaluit, Nunavut. The model represents a paradigm shift away from siloed Western service delivery frameworks towards an integrated approach grounded in Inuit epistemology, language, and cultural practices. Drawing on Indigenous methodologies and community-based approaches, this paper articulates how the model's eight interconnected components create a comprehensive wellness system that honours Inuit Qaujimajatuqangit (Inuit knowledge) while addressing contemporary community needs. The innovative approach offers valuable insights for other jurisdictions seeking to decolonise service delivery systems and develop culturally responsive alternatives. This paper contributes to growing scholarship on Arctic Indigenous health and wellness frameworks by demonstrating how the Inuit Holistic Service Delivery Model deserves recognition in academic discourse as a unique and innovative approach to community wellbeing.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.616

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.006
Scholarly communication0.0040.003
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.068
GPT teacher head0.423
Teacher spread0.355 · 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 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

Citations2
Published2025
Admission routes3
Has abstractyes

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