Validity and reliability of contingent valuation and life satisfaction measures of welfare: An application to the value of national Olympic success
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
Abstract The contingent valuation method (CV) has long been used to estimate nonmarket values of environmental and other public goods and amenities. Recently, life satisfaction (LS) measures have been used to estimate nonmarket values. This article empirically compares CV and LS measures of welfare. We elicit willingness‐to‐pay (WTP) estimates for medals won by Canadian athletes and LS measures using Canadian survey data collected before and after the 2010 Winter Olympic Games. These data permit comparative analyses of reliability and validity of CV and LS measures. Both exhibit econometric reliability. CV and LS WTP estimates for medals increase after the Olympics. CV measures of WTP exhibit temporal reliability but LS measures of welfare lack temporal reliability and are significantly greater than CV measures.
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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 | 0.002 | 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 | 0.000 | 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 it