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Record W4281967289 · doi:10.1177/10778004221099968

“Connection With the Creator So Our Spirits Can Stay Alive”: A Community-Based Participatory Study With the Métis Nation of Alberta (MNA)—Region 3

2022· article· en· W4281967289 on OpenAlexaffabout
Carla Ginn, Craig W. C. Ginn, Cheryl Barnabé, Lawrence Gervais, Judy Gentes, Doreen Dumont Vaness Bergum, Noelle Rees, Ashley Camponi

Bibliographic record

VenueQualitative Inquiry · 2022
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsMétis National CouncilUniversity of Calgary
Fundersnot available
KeywordsHonestyParticipatory action researchSociologyIndigenousMental healthCourageCitizen journalismCommunity-based participatory researchSocial connectednessIdentity (music)Inclusion (mineral)HumilityPsychologySocial psychologyEnvironmental ethicsGender studiesAestheticsPsychotherapistPolitical scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

In this article, we describe our Métis-guided community-based participatory research exploring health protective factors for mental health and addiction within the Métis Nation of Alberta (MNA)—Region 3. There is much research regarding the detrimental effects of colonialism but a lack of Métis-guided research contributing to understanding of individual, family, and community well-being. The primary aim of our study was to explore health protective factors for mental health and addiction challenges. Our study was informed by Indigenous ways of knowing, focusing on the connectedness of all things, and participatory action research, a philosophy and method focused on inclusion and community incorporation of local knowledge. Participants described the need to foster respect, trust, courage, wisdom, humility, truth, humor, esteem, honesty, acceptance, identity, and love, emphasizing well-being through connection with Creator. All authors but the first are members of the MNA—Region 3.

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)0.010
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.367
GPT teacher head0.507
Teacher spread0.140 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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