What Should Clinicians and Patients Know About the Clinical Gaze, Disability, and Iatrogenic Harm When Making Decisions?
Bibliographic record
Abstract
While clinicians, ethicists, and policymakers are increasingly aware that race, ethnicity, sexuality, gender, and class biases interfere with care provision, disability is not always considered as a confounding factor.This article explores the way embodiment affects personal and professional values.When patients who live with bodies others might not fully comprehend or embrace refuse-or challenge-clinical interventions, they offer real opportunities for clinicians to grasp the central role that embodied experience plays in how patients make health decisions and thereby avoid harming patients or undermining their relationships with patients.The American Medical Association designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 Credit™ available through the AMA Ed Hub TM .Physicians should claim only the credit commensurate with the extent of their participation in the activity.Disabled lives are as valid as nondisabled lives, but they are not the same. Andrew Solomon 1Creating space is difficult.The world does its best to resist.
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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 | 0.025 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.011 | 0.025 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 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".