How Culture Is Understood in Faculty Development in the Health Professions: A Scoping Review
Bibliographic record
Abstract
PURPOSE: To examine the ways in which culture is conceptualized in faculty development (FD) in the health professions. METHOD: The authors searched PubMed, Web of Science, ERIC, and CINAHL, as well as the reference lists of identified publications, for articles on culture and FD published between 2006 and 2018. Based on inclusion criteria developed iteratively, they screened all articles. A total of 955 articles were identified, 100 were included in the full-text screen, and 70 met the inclusion criteria. Descriptive and thematic analyses of data extracted from the included articles were conducted. RESULTS: The articles emanated from 20 countries; primarily focused on teaching and learning, cultural competence, and career development; and frequently included multidisciplinary groups of health professionals. Only 1 article evaluated the cultural relevance of an FD program. The thematic analysis yielded 3 main themes: culture was frequently mentioned but not explicated; culture centered on issues of diversity, aiming to promote institutional change; and cultural consideration was not routinely described in international FD. CONCLUSIONS: Culture was frequently mentioned but rarely defined in the FD literature. In programs focused on cultural competence and career development, addressing culture was understood as a way of accounting for racial and socioeconomic disparities. In international FD programs, accommodations for cultural differences were infrequently described, despite authors acknowledging the importance of national norms, values, beliefs, and practices. In a time of increasing international collaboration, an awareness of, and sensitivity to, cultural contexts is needed.
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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 | 0.027 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.017 | 0.022 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".