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Education and Practice

2004· article· en· W2315823273 on OpenAlexaffabout
Dawn Doutrich, Marni Storey

Bibliographic record

VenueFamily & Community Health · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsVancouver Biotech (Canada)
Fundersnot available
KeywordsCultural competenceCompetence (human resources)NursingTranscultural nursingMedical educationHealth professionalsHealth carePsychologyQualitative researchMedicinePedagogySociologyPolitical science

Abstract

fetched live from OpenAlex

This article reports on a collaborative project linking Washington State University College of Nursing Vancouver and Southwest Washington Health District. Designed to improve the cultural competence and public health skills of registered nurses who are baccalaureate student nurses, quantitative and qualitative evaluative analyses were used to document and describe themes and strategies. The Inventory to Assess the Process of Cultural Competence Among Healthcare Professionals (IAPCC) was useful in measuring the students' progress toward cultural competence, and significant changes were documented. Themes that lead students toward population-focused nursing practice were uncovered as well as barriers to the process of cultural competency.

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)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.066
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0060.003
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0660.023

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 head0.107
GPT teacher head0.456
Teacher spread0.349 · 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 designNot applicable
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

Citations54
Published2004
Admission routes2
Has abstractyes

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