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Record W2991291813 · doi:10.3390/ijerph16234782

Link to the Land and Mino-Pimatisiwin (Comprehensive Health) of Indigenous People Living in Urban Areas in Eastern Canada

2019· article· en· W2991291813 on OpenAlexafffundabout
Véronique Landry, Hugo Asselin, Carole Lévesque

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec en Abitibi-Témiscamingue
FundersSocial Sciences and Humanities Research Council of CanadaPolar Knowledge Canada
KeywordsIndigenousSafeguardingGeographyElement (criminal law)Key (lock)Urban communityIdentity (music)Environmental planningSocioeconomicsSociologyPolitical scienceMedicineEcology

Abstract

fetched live from OpenAlex

Mino-pimatisiwin is a comprehensive health philosophy shared by several Indigenous peoples in North America. As the link to the land is a key element of mino-pimatisiwin, our aim was to determine if Indigenous people living in urban areas can reach mino-pimatisiwin. We show that Indigenous people living in urban areas develop particular ways to maintain their link to the land, notably by embracing broader views of “land” (including urban areas) and “community” (including members of different Indigenous peoples). Access to the bush and relations with family and friends are necessary to fully experience mino-pimatisiwin. Culturally safe places are needed in urban areas, where knowledge and practices can be shared, contributing to identity safeguarding. There is a three-way equilibrium between bush, community, and city; and mobility between these places is key to maintaining the balance at the heart of mino-pimatisiwin.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.034
GPT teacher head0.349
Teacher spread0.315 · 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 designObservational
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

Citations20
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public Health→Same topicIndigenous Health, Education, and Rights→French-language works237,207→