The Importance of Intercultural Fluency in Developing Clinical Judgment
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".