The mixed experience of private sector involvement in biodiversity management in Costa Rica
Bibliographic record
Abstract
Biodiversity under threat in Costa Rica The small Latin American country of Costa Rica is generally known as ‘environmentally friendly’, and therefore has become a paradise for thousands of ecotourists. The Costa Rican Tourism Institute (ICT, Instituto Costarrecense de Turismo) has initiated an expensive advertising and image promoting campaign with the slogan ‘Costa Rica – no artificial ingredients’. The target groups are North American citizens (USA and Canada), between 25 and 54 years of age, who earn $75,000 or more a year, and have a university education ( Tico Times , 7 Aug. 1998). In 1999, the number of tourists reached 1 million ( Tico Times , 17 Dec. 1999). A quarter of the country is considered to be protected (see Fig. 11.1). The World Bank and the Global Environmental Facility (GEF) have spent millions of dollars to support official nature conservation measures and the responsible governmental departments. NGOs provide information and environmental education on site. Nevertheless, the current condition of the biodiversity in Costa Rica is disappointing. Despite regulations, management initiatives and international financial support, Costa Rica, formerly densely forested, has become an agricultural country. Virgin forests have become rare and are found nowadays only in remote or protected areas. Since the arrival of multinational companies, large areas have been transformed into monocultures, resulting in the pollution of both soil and water.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".