Alan Krupnick: Resources for the Future Willingness to Pay for Mortality Risk Reductions in Electric Power Generation
Bibliographic record
Abstract
This presentation examines two surveys examining preferences over public policies and sources of mortality. These surveys examine cancer versus microbial infection from drinking water and health risks form nuclear versus thermal power generation. The two surveys involve risk communication and education components and both use choice experiments to assess the attributes of public programs design to reduce risks. The drinking water survey is based in Canada while the power generation survey is based in Japan. Both surveys involve two sources of risk. In the drinking water case the sources are either microbial illnesses and death or cancer illness and death arising as a byproduct of the treatment of microbials. In the power generation case the sources of mortality risk are the two different power generating systems. The oil and coal sector generates “routine ” health risks while nuclear power generation presents risks of “accidents. ” In the power generation survey the baseline level of risk is varied to test the impact of changing baseline on risk perception and valuation. Analysis of the two surveys, while still in preliminary stages, provides lessons on the possibilities for use of choice experiments in such public policy contexts. It also
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".