Global economic value of shark ecotourism: implications for conservation
Bibliographic record
Abstract
Abstract Amid declining shark populations because of overfishing, a burgeoning shark watching industry, already well established in some locations, generates benefits from shark protection. We compile reported economic benefits at shark watching locations and use a meta-analytical approach to estimate benefits at sites without available data. Results suggest that, globally, c. 590,000 shark watchers expend > USD 314 million per year, directly supporting 10,000 jobs. By comparison, the landed value of global shark fisheries is currently c. USD 630 million and has been in decline for most of the past decade. Based on current observed trends, numbers of shark watchers could more than double within the next 20 years, generating > USD 780 million in tourist expenditures around the world. This supports optimistic projections at new sites, including those in an increasing number of shark sanctuaries established primarily for shark conservation and enacted in recognition of the ecological and economic importance of living sharks.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".