Disability discrimination and misdirected criticism of the quality-adjusted life year framework
Bibliographic record
Abstract
Whose values should count - those of patients or the general public - when adopting the quality-adjusted life year (QALY) framework for healthcare decision making is a long-standing debate. Specific disciplines, such as economics, are not wedded to a particular side of the debate, and arguments for and against the use of patient values have been discussed at length in the literature. In 2012, Sinclair proposed an approach, grounded within patient preference theory, which sought to avoid a perceived unfair discrimination against people with disabilities when using values from the general public. Key assumptions about general public values that beget this line of thinking were that 'disabled states always tally with lower quality of life', and the use of standardised instruments means that 'you are forced into a fixed view of disability as a lower value state' (Sinclair, 2012). Drawing on recent contributions to the health economics literature, we contend that such assumptions are not inherent to the incorporation of general public values for the estimation of QALYs. In practice, whether health states of people with disabilities are of 'lower value' is, to some extent, a reflection of the health state descriptions that members of the public are asked to value.
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How this classification was reachedexpand
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 | 0.085 | 0.309 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".