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Record W2884693475 · doi:10.5430/jnep.v8n12p29

Otsin: Sharing the spirit--Development of an indigenous rural nursing practice course

2018· article· en· W2884693475 on OpenAlexafffundvenue
Sheila Blackstock

Bibliographic record

VenueJournal of Nursing Education and Practice · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsThompson Rivers UniversityUniversity of Alberta
FundersThompson Rivers University
KeywordsIndigenousCultural safetyContext (archaeology)CurriculumSociologyNursingPedagogyMedicineGeographyEcology

Abstract

fetched live from OpenAlex

Otsin is the spirt of Gitxsan Peoples and is reflected by the Gitxsan author sharing the journey in the development of a unique third year undergraduate nursing practice course. The nursing practice course immerses students in a combined rural and an interdisciplinary indigenous nursing practice. The practice course is based on a student centered, context-based teaching pedagogy using a two-eyed seeing approach. The theoretical tenet of place is reconceptualized to reflect Indigenous communities and rural nursing practice. The metaphor of weaving together cedar strips is used to reflect a journey that takes students through the experiences of living and practicing in a rural northern community while embracing on the land experiences, cultural practices, traditions, language and ceremonies. The traditional academy curricula are challenged to broaden the lens beyond the classroom theatre walls to rural, indigenous nursing practice experiences. The weaving of the cedar strips together and allows students to construct their understanding of the impacts of colonization on Indigenous Peoples and an opportunity to be guided by the community to practice cultural safety.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.002

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 head0.110
GPT teacher head0.494
Teacher spread0.384 · 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

Citations2
Published2018
Admission routes3
Has abstractyes

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