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Record W2000178240 · doi:10.5172/jamh.5.3.202

An evidence-based formative evaluation of a cross cultural Aboriginal mental health program in Canada

2006· article· en· W2000178240 on OpenAlexaffabout
William R. Thomas, Gerard Bellefeuille

Bibliographic record

VenueAustralian e-Journal for the Advancement of Mental Health · 2006
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsMacEwan UniversityDiagnostic Services Manitoba
Fundersnot available
KeywordsFormative assessmentSocial connectednessEmpowermentSpiritualityThematic analysisMental healthQualitative researchPsychologyGrounded theoryPedagogyMedical educationSociologyPsychotherapistMedicineAlternative medicinePolitical scienceSocial science

Abstract

fetched live from OpenAlex

This article reports on a formative evaluation of a Canadian cross cultural Aboriginal mental health program that combined the healing properties of the Aboriginal healing circle and the self-awareness and empowerment practices of the psychotherapy technique known as ‘focusing’. The study was formative in nature and grounded in qualitative inquiry. Out of the data analysis, five salient themes surfaced that captured the breadth of the participants’ first-hand experiences of the piloted program: experience, relationships, spirituality and connectedness, empowerment, and self-awareness. The findings were interpreted using the therapeutic criteria for both the focusing and healing circle components of the program. Implications of the research include the need for further research to be conducted with, for and by Aboriginal people to ensure that their worldview is acknowledged and put into practice, and the need to acknowledge existing frameworks of healing and knowledge within Aboriginal communities.

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)0.078
metaresearch head score (Gemma)0.110
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: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.820

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0780.110
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.006
Science and technology studies0.0080.003
Scholarly communication0.0030.002
Open science0.0050.004
Research integrity0.0020.002
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 head0.188
GPT teacher head0.574
Teacher spread0.386 · 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

Citations35
Published2006
Admission routes2
Has abstractyes

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