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Record W2562659182 · doi:10.5430/jnep.v7n5p68

A reflexive exercise to promote cultural humility among doctoral nursing students

2016· article· en· W2562659182 on OpenAlexvenueno aff
Beth Mastel‐Smith, Susan Yarbrough

Bibliographic record

VenueJournal of Nursing Education and Practice · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsnot available
Fundersnot available
KeywordsCultural humilityHumilityReflexivityCultural diversityPsychologyCultural competenceMedical educationNurse educationNursingMedicinePedagogySociologySocial science

Abstract

fetched live from OpenAlex

Background: The U.S. population is becoming increasingly diverse; however, nursing remains a predominantly Caucasian profession. To promote positive outcomes among diverse patients, nurses must rely on rigorous transcultural research. When conducting research with people different from oneself, knowledge of one’s own values and beliefs is a necessary first step. In Transcultural Nursing Research, a required doctoral course, the first assignment is a reflexive exercise followed by online discussion about one’s personal culture and the origins of values and beliefs. Objectives: To (a) examine students’ responses to a reflexive exercise for evidence of cultural self-awareness, cultural humility, and insights gained and (b) assess the effectiveness of the teaching method.Methods: The setting was online within the Learning Management System (LMS), Blackboard. Participants: The sample consisted of twelve doctoral students enrolled in Transcultural Nursing Research. Methods: Student consent was obtained after course grades were submitted. Data was extracted from the LMS, de-identified, coded, categorized and collapsed into themes.Results: Four themes emerged from the data: “different versus familiar”, “cultural experiences”, “memories” and “reflections and implications”.Conclusions: Posts reflected insight into cultural awareness, values and humility. Students identified growth opportunities for themselves and their children. Suggestions for future education and research are presented.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.584
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
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 head0.164
GPT teacher head0.548
Teacher spread0.385 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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