Ecotourism, Animals and Ecocentrism: A Re-examination of the Billfish Debate
Bibliographic record
Abstract
The aim of this paper is to discuss the topic of who, or what, is deserving of moral consideration in nature as this applies to the emerging discourse on tourism, animals and ethics. The paper focuses primarily on deep green or ecocentric ethics, and more specifically, on how this perspective differs from other theories of environmental ethics—especially animal liberation—when it comes to the treatment of animals used for tourism. The debate on billfishing as ecotourism is resurrected for the purpose of explaining (i) why it is important to understand key differences between ecocentric and animal liberation ethics; and (ii) how both theories could have been used to better inform the billfishing debate that took place over a decade ago. The paper concludes with a call for the continued use of environmental ethics theory in clarifying whether certain human- animal practices should be viewed as ecotourism or not.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".