Bibliographic record
Abstract
Having looked at the external and internal challenges facing the move towards more sustainable tourism, and the impacts of tourism, you should now be wondering how sustainability in tourism can be turned into more than an ideal. Perhaps one of the most obvious way to achieve this is simply to regulate the sector. After all regulation worked for the ozone layer: scientists raised the alarm in the 1970s that a hole was appearing in the atmosphere’s ozone layer, caused by Ozone Depleting Substances or ODS (most notably CFCs) and resulting in adverse effects on human health and the environment. By 1987 the Montreal Protocol was established to phase out the use of ODS, and by June 2015, all countries in the United Nations, the Cook Islands, Holy See, Niue and the supranational European Union had ratified the original Protocol. The result was a 98% drop in ODS since ratification, and the hole is expected to have fully repaired itself by 2050. A significant achievement in terms of international cooperation, based on scientific advice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.038 | 0.006 |
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".