The Divergence and Convergence of Critical Reflection and Critical Reflexivity: Implications for Health Professions Education
Bibliographic record
Abstract
As a field, health professions education (HPE) has begun to answer calls to draw on social sciences and humanities (SS&H) knowledge and approaches for curricular content, design, and pedagogy. Two commonly used SS&H concepts in HPE are critical reflection and critical reflexivity. But these are often conflated, misunderstood, and misapplied. Improved clarity of these concepts may positively affect both the education and practice of health professionals. Thus, the authors seek to clarify the origins of each, identify the similarities and differences between them, and delineate the types of teaching and assessment methods that fit with critical reflection and/or critical reflexivity. Common to both concepts is an ultimate goal of social improvement. Key differences include the material emphasis of critical reflection and the discursive emphasis of critical reflexivity. These similarities and differences result in some different and some similar teaching and assessment approaches, which are highlighted through examples. The authors stress that all scientific and social scientific concepts and methods imported into HPE must be subject to continued scrutiny both from within their originating disciplines and in HPE. This continued questioning is core to the ongoing development of the HPE field and also to health professionals' thinking and practice.
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How this classification was reachedexpand
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 | 0.001 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".