Turning the Lens Inward: Cultural Competence and Providers' Values in Health Care Decision Making
Bibliographic record
Abstract
The population of older adults in the United States is growing in size and diversity, presenting challenges to health care providers and patients in the context of health care decision making (DM), including obtaining informed consent for treatment, advance care planning, and deliberations about end-of-life care options. Although existing literature addresses providers' need to attend to patients' cultural values and beliefs on these issues, less attention has been paid to how the corresponding values and beliefs of providers color the care they deliver and their assessments of older adults' DM capacity. The provider's challenge is to understand her own unacknowledged anxieties, prejudices, and fears around such charged issues as truth telling, individual agency, capacity, death and dying, and the value of life itself and address their impact on the delivery of care. A social constructivist perspective and the clinical concept of cultural countertransference are proposed as aides in achieving this awareness and improving care.
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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 | 0.030 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.097 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".