One of These Things Is Not Like the Others: The Idea of Precedence in Health Technology Assessment and Coverage Decisions
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
Health plans often deliberate covering technologies with challenging purposes, effects, or costs. They must integrate quantitative evidence (e.g., how well a technology works) with qualitative, normative assessments (e.g., whether it works well enough for a worthwhile purpose). Arguments from analogy and precedent help integrate these criteria and establish standards for their policy application. Examples of arguments are described for three technologies (ICSI, genetic tests, and Viagra). Drawing lessons from law, ethics, philosophy, and the social sciences, a framework is developed for case-based evaluation of new technologies. The decision-making cycle includes (1) taking stock of past decisions and formulating precedents, (2) deciding new cases, and (3) assimilating decisions into the case history and evaluation framework. Each stage requires distinctive decision maker roles, information, and methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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