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Record W4200589542 · doi:10.1177/13634615211056830

Inuit wellness: A better understanding of the principles that guide actions and an overview of practices

2021· article· en· W4200589542 on OpenAlexafffundabout
Marie-Helene Gagnon Dion, Sarah Fraser, Louisa Cookie-Brown

Bibliographic record

VenueTranscultural Psychiatry · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsWork (physics)PsychologyPublic relationsSociologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

By imposing non-Inuit ways of doing within households and communities, colonization has created a rift between generations and impacted the transmission of Inuit practices and knowledge. Inuit care-providers continue to support their fellow community members with individual and collective approaches to wellbeing. The objectives and design of the current project were developed with community members who play an active role in mobilization and wellness. Inuit and non-Inuit research assistants conducted 14 individual interviews and 2 group interviews (total of 19 participants) with key informants involved in community wellness work. Then an Elder (third author) shared her knowledge regarding traditional practices. In this study we describe three underlying principles regarding wellness practices as well as five approaches and the mechanisms by which these approaches seem to impact personal and collective wellbeing. This study highlights how Inuit culture and knowledge can support children, family and community wellbeing in the ways of being together and of taking care of each other. The study responds to an expressed desire named by our partners to document Inuit approaches as well as the principles and practices underlying such approaches and how they are related to self-determination.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.196
GPT teacher head0.411
Teacher spread0.215 · 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

Citations7
Published2021
Admission routes3
Has abstractyes

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