Benevolent and Benign? Using Environmental Justice to Investigate Waste‐related Impacts of Ecotourism in Destination Communities
Bibliographic record
Abstract
Abstract: We contribute to the diversification of environmental justice (EJ) by using it to frame ecotourism‐related solid waste management problems. Ecotourism is a service industry portrayed as benevolent (providing benefits), and benign (reducing negative impacts). We propose four characteristics shared by ecotourism‐based communities in the Global South and communities struggling with more conventional EJ conflicts. We apply these characteristics to the solid waste crisis in Tortuguero, Costa Rica, a renowned ecotourism destination. First, we show that, despite their general absences from the EJ literature, service industries such as tourism and hospitality can create environmental injustices that disproportionately impact certain types of communities. Second, we highlight the roles of location and socio‐economic marginality in siting ecotourism development, in complicating related environmental impact management, and in limiting local abilities to respond to environmental management shortcomings. Third, we provide an example of opportunities to introduce EJ concepts and theory into the study of tourism.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".