Exploring the boundaries of a new moral order for tourism's global code of ethics: an opinion piece on the position of animals in the tourism industry
Bibliographic record
Abstract
This opinion piece reviews the claim by the United Nations World Tourism Organization (UNWTO) that its Global Code of Ethics “is an important frame of reference for the responsible…development of world tourism”. Most of the prescriptions contained within the Code's 10 Articles and accompanying sections focus on human rights, freedoms and benefits and much less on specific aspects of the environment. The Code's overriding anthropocentric tone denies any chance for it to be a truly responsible creed. Being responsible should mean taking care of human needs, and the needs of the millions of animals used in the tourism industry for human enjoyment and benefit. The code fails to be truly responsible: the “frame of reference” is not inclusive or protective of the welfare of those beings who, by their involvement as workers, entertainers and competitors, are an important part of the tourism industry's operations whether acknowledged or not. Animal ethics is an area of scholarship that is virtually terra incognita in tourism studies. The paper recommends that the UNWTO reconvene to amend the Code. Good practice is illustrated, and a draft Article 11 for a revised UNWTO Code is provided. Respect and animal welfare is advocated, but not the more extreme position of animal rights.
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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 | 0.021 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.043 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.018 | 0.020 |
| 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".