Have environmental preferences and willingness to pay remained stable before and during the global Covid-19 shock?
Bibliographic record
Abstract
This study tests the stability of environmental preferences and willingness to pay (WTP) values using a discrete choice experiment (DCE) across three countries pre and post the peak of the first wave of the Covid-19 pandemic. A DCE examining the public's preferences for alternative environmental management plans on the high seas, in the area of the Flemish Cap, was carried out in Canada, Scotland and Norway in late 2019 and was rerun in early May 2020 shortly after the Covid-19 pandemic had officially peaked in the three countries. The same choice set sequence is tested across the two periods, using different but nationally representative samples in each case. Entropy balancing, a multivariate reweighting method, is used to achieve covariate balance between the pre and post Covid samples in the analysis. The results suggest that both preferences and WTP remain relatively stable in the face of a major public health crisis and economic upheaval.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".