A Journey of Critical Consciousness: An Educational Strategy for Health Care Leaders
Bibliographic record
Abstract
Healthcare leaders who develop a critical perspective of the relationship between culture and health; value respect for differences, inclusiveness, equity, and social justice; and use their power to enact these values in their spheres of influence, both professionally and personally, are better able to improve care for a diversity of clients. Graduate students can be assisted to develop such a critical perspective through a course designed as a journey of critical consciousness. We describe this journey that takes students through phases of awareness, reflection, and action in which they come to understand the concepts of critical theory and discourse analysis and begin to use these to create changes in their work settings in the direction of equity and social justice. We suggest broader implications for programs and invite readers to begin their own journeys of critical consciousness.
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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 | 0.031 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.025 | 0.030 |
| Scholarly communication | 0.027 | 0.029 |
| Open science | 0.004 | 0.034 |
| Research integrity | 0.012 | 0.025 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".