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Record W2129271808 · doi:10.18357/ijih41200812316

Balancing the Medicine Wheel through Physical Activity

2013· article· en· W2129271808 on OpenAlexaffvenue
Lynn F Lavallée

Bibliographic record

VenueInternational Journal of Indigenous Health · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMartial artsFriendshipIdentity (music)Symbol (formal)Meaning (existential)Mental healthIndigenousThe artsPsychologySocial psychologyPsychology of selfSociologyAestheticsVisual artsPsychotherapistComputer scienceArt

Abstract

fetched live from OpenAlex

This article highlights the findings of a research project based on the medicine wheel teachings of balance between the physical, mental, spiritual, and emotional aspects of oneself. Specifically, this traditional approach to understanding health was used to explore the impacts of physical activity on emotional, spiritual and mental well-being. Four female participants in a martial arts program at an urban Friendship Centre told their stories at two sharing circles. Afterwards, they were given six weeks to develop symbols that represented the meaning of the martial arts program to them and how it had impacted their lives. The participants named this second method “Anishnaabe Symbol-Based Reflection.” This article provides a brief overview of these Indigenous methods and explains how they were applied to this research project. The article then focuses on two key themes that emerged from the Aboriginal women’s stories: issues related to identity and to a sense of not deserving good things in life. The women described how they were able to work through some of their identity issues and their low sense of self-worth through their participation in the martial arts program.

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)0.002
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 score0.913
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.024
GPT teacher head0.374
Teacher spread0.350 · 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

Citations46
Published2013
Admission routes2
Has abstractyes

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