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Record W3163639528 · doi:10.1177/21582440211015202

The Medicine Wheel Revisited: Reflections on Indigenization in Counseling and Education

2021· article· en· W3163639528 on OpenAlexaff
Lloyd Hawkeye Robertson

Bibliographic record

VenueSAGE Open · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsIndigenizationCurriculumSociologyContext (archaeology)ModernityConceptual frameworkSpiritualitiesEpistemologyEngineering ethicsSocial sciencePedagogyAnthropologyMedicineSpiritualityAlternative medicineHistory

Abstract

fetched live from OpenAlex

Indigenization involves relating traditional cultures to modern methods, concepts, and science to facilitate their use by those populations. Despite attempts to indigenize both the practice of counseling and the content of educational curricula, mental health and educational deficits in Amerindian communities have remained. This article suggests indigenization in the North American context is often based on a reified view of culture that discounts naturalistic and scientific approaches, and that this dynamic inhibits progressive cultural change at institutional and community levels. A secular approach to indigenization is proposed that relates modern conceptual thought to traditional cultures in a way that is consistent with traditional constructs. The medicine wheel, traditional to North American Great Plains cultures, is applied to counseling to illustrate how concepts found in aboriginal cultures could inform modern practice with wider applications to curriculum development. Related tensions involving interpretations of aboriginal spiritualities and modernity are discussed.

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)0.038
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0270.138
Scholarly communication0.0190.026
Open science0.0040.017
Research integrity0.0220.041
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.399
Teacher spread0.366 · 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
Published2021
Admission routes1
Has abstractyes

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