Exploring racism and racialization in the work of healthcare chaplains: a case for a critical multifaith approach
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
The global COVID-19 pandemic has revealed healthcare settings as sites of much-needed scrutiny as to the workings of racism and racialization in shaping healthcare encounters, health outcomes, and workplace conditions. Little research has focused on how healthcare chaplains experience and respond to social processes of racism and racialization. We apply a critical race lens to understand racism and racialization in healthcare chaplaincy, and inspired by Patricia Hill Collins, propose a "critical multifaith approach." Drawing on research in healthcare in Canada and England, we generated four composite narratives to analyze racialization's variability and resistances employed by Indigenous, Arab, Black, and White chaplains. The composites disclose complex intersecting histories of colonialism, religion, race, and gender. Developing a critical multifaith perspective on healthcare delivery is an essential competency for chaplains wanting to impact the systems in which they serve in the direction of more equitable human flourishing.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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 it