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Record W2342093049 · doi:10.1177/0898010116642085

Embracing Our “Otherness”

2016· article· en· W2342093049 on OpenAlexaffabout
Natasha Prodan‐Bhalla, Diane Middagh, Sharon Jinkerson-Brass, Shabnam Ziabakhsh, Ann Pederson, Charlene King

Bibliographic record

VenueJournal of Holistic Nursing · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsIsland HealthB.C. Women's Hospital & Health Centre
Fundersnot available
KeywordsSociologyPsychology

Abstract

fetched live from OpenAlex

Theories on the importance of holistic and spiritual healing within nonconventional models of care are vast, yet there is little written about the practical, clinical-level interventions required to deliver such practices in collaborative cross-cultural settings. This article describes the learning experiences and transformative journeys of non-Indigenous nurse practitioners working with a Cultural Lead from an Indigenous community in British Columbia, Canada. The goal of the Seven Sisters Healthy Heart Project was to improve heart health promotion in an Indigenous community through a model of knowledge translation. The article describes the development of a bridge between two cultures in an attempt to deliver culturally responsive programming. Our journeys are represented in a phenomenological approach regarding relationships, pedagogy, and expertise. We were able to find ways to balance two worlds-the medical health services model and Indigenous holistic models of healing. The key to building the bridge was our willingness to be vulnerable, to trust in each other's way of teaching and learning, and allowing diverse viewpoints and knowledge sources to be present. Our work has vast implications for health promotion in Indigenous communities, as it closes the gap between theory and practice by demonstrating how Indigenous models can be integrated into mainstream health promotion practices.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.086
GPT teacher head0.424
Teacher spread0.338 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations10
Published2016
Admission routes2
Has abstractyes

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