Beneficios económicos de los servicios ecosistémicos recreativos del turismo de naturaleza con tiburón ballena en la Bahía de La Paz, México
Bibliographic record
Abstract
Economic benefits from nature-based tourism activities with whale sharks (Rhincodon typus) in La Paz Bay have not been quantified monetarily. The study aims are: 1) to estimate the economic benefits of recreational ecosystem services of nature-based tourism activities with whale shark and, 2) to establish a base line that could assist to propose differentiated access fees by visitor’s provenance. We conducted 134 interviews to tourists who swam with whale shark. Survey included sociodemographic, site quality, and experience perception aspects. The economic benefits of nature-based tourism with whale shark were estimated appliyin the market price method and it yields a value about 3.292 million US$, highlighting that domestic visitor´s has a higher benefit appreciation from the activity than foreign visitor´s. Hypothesis test indicates that there is not statistically significant difference among travel and total cost, but there is statistical significative difference between average travel cost and total cost by domestic and foreign visitor respectively. Meanwhile, ANOVA shows that there is not statistical difference regarding average travel cost between tourist provenance (domestic, American, Canadian, European and other); but there is not significative difference for average total cost by visitor´s provenance. These results give the opportunity to set a base line to propose differentiated access fees by tourist provenance, which would enforce and encourage sustainable finance for the protected area of whale shark at La Paz Bay, if implemented.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".