Quality over Quantity: Nonmarket Values of Restoring Coastal Dunes in the U.S. Pacific Northwest
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
We design a choice experiment to examine public preferences for coastal dune ecosystem restoration in the U.S. Pacific Northwest. Dunes are a public good whose natural state is now rare. Respondents are asked to choose among hypothetical projects that vary by project size, restoration quality, recreation access, flooding risk, and cost. Restoration quality is defined as closeness to the natural ecosystem. We find that increasing restoration quality results in significantly higher welfare gains than increasing the size of restoration area. Maintaining recreation access is preferred, and programs with recreation restrictions yield positive willingness to pay only if accompanied by the highest restoration quality.
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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) | 0.001 | 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 it