Water quality advisory impacts on recreation behaviour and associated economic costs
Bibliographic record
Abstract
One of the major rationales for improving water quality is to increase the benefits and enjoyment of water-based recreation yet quantifying these behavioural responses and values remains challenging. We apply a recreation demand model using a large, multi-year data set on camping trips and water quality advisories across provincial parks in Alberta. The recreation data includes information on over 447,000 trips by 225,700 individuals over a five-year period. We use a nested logit model to understand people’s recreation choices to one of 76 campgrounds. We find that the presence of a water quality advisory has a negative impact on the likelihood of visiting an affected campground. On the one hand, this suggests that advisories work in limiting human contact with unsafe water, but these behavioural changes also carry economic costs. We estimate that the welfare costs of a beach advisory are $14 per camping trip. We use the model to evaluate the welfare impacts of removing all beach advisories. These results can be used to inform the design of policies aimed to improve lake water quality.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".