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Record W2194283111 · doi:10.7603/s40743-015-0020-8

The Importance of Intercultural Fluency in Developing Clinical Judgment

2015· article· en· W2194283111 on OpenAlexaff
Eva Peisachovich

Bibliographic record

VenueGSTF Journal of Nursing and Health Care · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsYork University
Fundersnot available
KeywordsFluencySociocultural evolutionPsychologySubjectivityContext (archaeology)Social psychologyPedagogyCognitive psychologyEpistemologySociologyMathematics education

Abstract

fetched live from OpenAlex

Abstract The concept of intercultural fluency emerged from the data analysis of a recent study that explored internationally educated nurses’ (IENs) experience and understanding of clinical judgment when engaged in a simulated clinical environment. I observed that one’s prior sociocultural experiences and subjectivity have significance in the context of nursing care and patient outcomes. Further, this subjectivity can facilitate the development of expertise, which is a significant factor that can support IENs’ transition to nursing practice. In this context, intercultural fluency refers to a process that allows one to regress and progress on the continuum of novice to expert, as identified by Benner (1984). Benner’s model has been modified here to acknowledge that movement along the continuum is multidirectional and dependent on the social, cultural, or sociocultural context of a situation. The modified model illustrates that one may be a novice in one setting but an expert in another. The concept of intercultural fluency explains how one’s expertise can regress when one is in an unfamiliar situation or when one encounters cultural differences. This paper provides potential approaches to apply the concept of intercultural fluency in both the education of IENs and the nursing profession.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.236
GPT teacher head0.512
Teacher spread0.276 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueGSTF Journal of Nursing and Health CareSame topicCultural Competency in Health CareFrench-language works237,207