Economic Burden and Costs of Drowning in Costa Rica
Bibliographic record
Abstract
Surf-related drowning fatalities are recognized as a serious public health issue in Costa Rica. Using data obtained from the Costa Rican Judicial Investigation Department, this study estimates the long-term economic impact of surf-related drowning fatalities based on the Value of a Statistical Life Year (VSLY) and an estimate of the direct costs associated with search and rescue, emergency services, and postmortem care. Between 2001 and 2022, surf-related drowning fatalities in Costa Rica resulted in a direct cost (DC) of >$2.0 million per year (USD) for search and rescue, >$87k/yr in costs to the families for repatriation (R) of the deceased, and a long-term economic burden (VSL) of ∼$100 million per year. On average, each drowning in Costa Rica results in a >$2 M cost (VSL+DC+R), which provides a benchmark to assess the net benefit of educational and legislated initiatives (e.g., lifeguards and warning systems) to reduce the number of surf-related drowning fatalities in the country.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".