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Record W2135276058 · doi:10.7202/1068869ar

Can Spiritual Ecograms be Utilized in Mental Health Services to Promote Culturally Appropriate Family and Couples Therapy with Indigenous People?

2020· article· en· W2135276058 on OpenAlexaffvenue
Nicole Elliott

Bibliographic record

VenueFirst Peoples Child & Family Review An Interdisciplinary Journal Honouring the Voices Perspectives and Knowledges of First Peoples · 2020
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIndigenousSpiritualityMental healthFamily therapyPsychotherapistPsychologyMedicineAlternative medicine

Abstract

fetched live from OpenAlex

Research addressing the potential utilization of spiritual ecograms with Indigenous families and children, specified by experienced professional in the field of Native-American psychology, was critiqued and reviewed in order to attend to its influence and applicability regarding the literature of Indigenous family therapy, and how it could be beneficial in therapy with Indigenous families. The literature review presents an effective tool, providing an in-depth exploration of spiritual strengths of the family and or children that incorporates spirituality into techniques commonly used in family therapy practice. Study results (Limb & Hodge, 2011) show that this tool is consistent with Native-American culture (Brucker & Perry, 1998; Green, 2010; Paniagua, 2005; Trujillo, 2000) and highlights many beneficial qualities for its utilization in practice. Limitations and recommendations for future research are also 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)0.006
metaresearch head score (Gemma)0.012
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 score0.012
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
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 head0.030
GPT teacher head0.354
Teacher spread0.323 · 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

Citations4
Published2020
Admission routes2
Has abstractyes

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