Justice in Educational Content: A Guide to Racial and Cultural Representation in Academic and Clinical Teaching and Assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Case-based instruction is broadly used in health professions education, including physical therapy education. Case-based instruction can support achievement of higher-order, applied, learning objectives and clinical reasoning. Instructors strive to represent the diversity of the clinical population in case studies and may have explicit intercultural competency objectives. The inclusion of cultural, racial, and ethnic characteristics in cases or assessments can potentially reinforce stereotypes or inaccurately emphasize these characteristics as direct predictors of health profile. Furthermore, as most physical therapy faculty creating cases are from a White majority stance, there is a risk that inclusion of cultural elements risks inappropriate and biased representation. POSITION AND RATIONALE: Well-intentioned instructors risk substituting cultural, racial, and ethnic characteristics for social and structural determinants of health. Race is a social, not biologic construction and should not be confused. Informed instructors guided by evidence-based strategies can achieve rich case depictions that do not convey inaccurate risk or alienate learners. DISCUSSION AND CONCLUSION: A curriculum design strategy is offered for case development that brings explicit attention to representation of race and culture. This tool serves as a self-reflective and improvement tool. Continued community and student engagement is necessary to achieve high-quality and instructive case studies.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it