Bioeconomic Modelling of Wetlands and Waterfowl in Western Canada: Accounting for Amenity Values
Bibliographic record
Abstract
This study reexamines and updates an original bioeconomic model of optimal duck harvest and wetland retention by Hammack and Brown (1974, Waterfowl and Wetlands: Toward Bioeconomic Analysis. Washington, DC: Resources for the Future). It then extends the model to include the nonmarket (in situ) value of waterfowl and the ecosystem service and other amenity values of wetlands in addition to the value of ducks to hunters. The focus is the prairie pothole region of Western Canada. Results indicate that wetlands and duck harvests need to be increased relative to historical levels, confirming Hammack and Brown's original conclusions. Including amenity values leads to a significant increase in the quantity of wetlands and hunters’ harvests of ducks relative to models that focus only on hunting values.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".