Are preferences over health states complete?
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
Most applied work in health economics accepts, if only implicitly, the axiom of completeness. Preferences over health states or health services are assumed to be well formed. They are effectively 'data' waiting to be collected. An alternative perspective suggests that values are initially incomplete and are constructed rather than just revealed in the process of answering choice-related questions such as willingness to pay or standard gambles. What might appear as measurement error may, therefore, be a more deliberate process of reflection and deliberation. This paper reports on a study that assessed the completeness of health preferences. The results show a mixed pattern. For most of the sample, values were stable over repeat administration, suggesting completeness. However, one-third of participants deliberately changed their answers and suggested that the interview process had forced them to think about their values more deeply. While it is premature to draw conclusions from this small sample, the suggestion is that completeness cannot be taken for granted.
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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.009 |
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