Development of tourism environmental management in Kazakhstan based on successful international experience
Bibliographic record
Abstract
Object: The aim of this research is to analyze the best examples of international experience in tourism environmental management and the possibilities of using them in the Kazakhstan example. Methods: Several methods as comparison, analyzing case studies, and theoretical literature review have been used during the research. Findings: The authors show that Kazakhstan meets difficulties with tourism environmental management, even though it has a great potential to be one of the world leaders in this field. Consequently, the authors recommend several directions on how Kazakhstan tourism environmental management should be developed through international experience. Conclusions: The article defines the approaches that some of the developed and developing countries, which have improved the tourism industry through the environmental management tools such as, Australia (DEC), UK (win-win development), New Zealand (Marine Mammals Protection Act), Canada (Tourism Destination Model), Ecuador (Tourism associations), Costa Rica (tourism environmental management strategy), and Botswana (the community — based ecotourism). As a result, Kazakhstan can easily use all these approaches to develop its tourism environmental management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".