Valuing the Recreational Uses of Pakistan’s Wetlands: An Application of the Travel Cost Method
Bibliographic record
Abstract
According Global 200, which scientifically ranks outstanding terrestrial and aquatic ecosystems in 238 ecoregions worldwide, the Indus Ecoregion is one of the 40 priority Ecoregions. Keenjhar lake, Pakistan's largest freshwater lake and a Ramsar site, is located in the Lower Indus Basin of the Indus Ecoregion. This study applies a single-site truncated count data travel cost model in order to estimate the value visitors place on recreation in Keenjhar. We estimate the recreational use value associated with Keenjhar lake to be PKR 3.46 billion (or USD 42.2 million). This estimate is based on an annualized mean consumer surplus per visit of PKR 9, 500 (or USD 116) and assumes average daily visits of 1, 000. Changing the model specification reduces consumer surplus only by about 5%. Policy makers can use these estimates on the recreational value of the lake to assess the returns to conservation investments.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".