How Does the WHO’s Framework for Functioning, Disability and Health (ICF) Provide an Ethical Foundation for 21st Century Clinicians?
Bibliographic record
Abstract
The WHO’s twenty-first century framework for health, the International Classification of Functioning, Disability and Health (the ICF), integrates many elements of people’s lives to enable people to create a unique self-portrait. ICF language illustrates the evolution of concepts like “impairment” and “disability”. In this essay we illustrate how the ICF’s approach to health ranges well beyond traditional biomedical diagnosis as the entry point for services and offers opportunities to contextualize a person with any health “impairment” in terms of their functioning, personal values and preferences, and environments. We argue that the use of the ICF makes it possible for health services to provide care that addresses Beauchamp and Childress’s four ethical principles . Justice is served by the universality of the ICF. Incorporating the voices and values of people respects individual autonomy. Codesigning approaches to care with providers facilitates achievement of beneficence (doing the right things in the context of people’s own voices and values) and avoids maleficence (doing things judged not to be in the best interests of the person). We believe that this ICF-based approach to health and health care offers a unique ethical framework.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".