A Canadian perspective of pharmacy education for students belonging to diverse groups
Bibliographic record
Abstract
BACKGROUND: Attention to equity, diversity, and inclusion (EDI) is on the rise in Canada, the United States, and the world. While there are evolving efforts across various sectors, post-secondary institutions, in particular, are growing in EDI efforts. For health professional programs, including pharmacy, health disparities are addressed and improvements in health care are realized when faculty are committed to EDI in hiring, admissions, and teaching and learning. To inform the direction and highlight the importance of further EDI research, programming, and evaluation, this paper analyzes the existing literature in pharmacy education and the education of diverse groups. METHODS: Several databases were searched, resulting in 17 articles of varying scopes (e.g., reviews, commentaries, reports) that capture principles of pharmacy education for diverse or marginalized students. While other articles were screened for inclusion, the concepts of culture, equity, diversity, and inclusion were presented as part of classroom and curricular topics (e.g., learning about the topics) and did not contain mention or evaluation of the education of diverse or marginalized students in pharmacy. RESULTS: Pharmacy education literature for diverse and/or marginalized student groups is limited. While significant publications exist regarding pharmacy education about EDI, little attention has been given to how pharmacy programs and educators may adapt their teaching and learning practices, policies, procedures, and admission processes to move beyond the status quo. IMPLICATIONS: Findings from this review will better inform pharmacy education programs to engage in the research and practice of conscious continuous improvement of safe spaces for diverse pharmacy students.
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 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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".