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Record W2465844668 · doi:10.11575/prism/26717

Land-based Practice for Indigenous Health and Wellness in Yukon, Nunavut, and the Northwest Territories

2016· dissertation· en· W2465844668 on OpenAlexaboutno aff
Jennifer Redvers

Bibliographic record

VenuePRISM (University of Calgary) · 2016
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousGeographyEnvironmental planningEnvironmental protectionPhysical geographyEcology

Abstract

fetched live from OpenAlex

This thesis examines the cultural concept and role of the Land as healer in Indigenous communities in the Northwest Territories, Yukon, and Nunavut, and the importance of facilitating modern Land-based programs and activities for integrated health, education, and environmental outcomes. It describes a yet largely undefined field of professional practice currently being negotiated on the ground in communities. This valid form of integrative practice, centered in Indigenous pedagogy and wisdom, recognizes that people are intimately interwoven and connected with their traditional lands, and that directly cultivating this fundamental relationship can shape and influence all areas of interaction with society, including our health and wellness. Research methods were framed by an Indigenous methodology of narrative experience. Eleven Land-based practitioners were interviewed, and their narratives speak to the recognition of Land practice as an important part of individual and community resilience in the face of rapid colonial change and its subsequent challenges.

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)0.002
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 score0.534
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0140.011
Scholarly communication0.0030.001
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.290
Teacher spread0.279 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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