Measuring the Net Economic Value of Recreational Boating as Water Levels Fluctuate<sup>1</sup>
Bibliographic record
Abstract
Abstract: The purpose of this article was to show how the value of recreational boating can be assessed and how that value can be linked to water levels. Data were gathered via a survey of recreational boaters to determine days boated and willingness‐to‐pay (net economic value) for boating on Lake Ontario and on the St. Lawrence River in 2002. Depth measurements were taken at marinas and yacht clubs, boat launch ramps, and private docks. Stage‐damage curves were used to pinpoint at what water levels and to what extent boaters would be impacted. Boaters recreated an estimated 1.3 million days in 2002 and spent an estimated US$178 million in New York counties bordering Lake Ontario and the St. Lawrence River. The mean net economic value per day per boat (above current expenditures) was $69.36, with an estimated total net economic value of US$90 million. Using Lake Ontario as an example, the stage‐damage curves show that the overall negative impact would be small, between 245 and 248 ft. Maintaining water levels within that range for the entire boating season would be ideal for Lake Ontario boaters and associated businesses.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".