DEFINING OF CRITERIA AND INDICATORS OF SUSTAINABLE ECOTOURISM MANAGEMENT FOR PROTECTED AREAS OF OUR COUNTRY
Bibliographic record
Abstract
Significant changes have occurred in the understanding and activities of tourism in parallel with the economic, political and technological developments experienced in recent years. In particular, sustainable tourism that protects the natural, cultural and social resources in the long term and supports this process with economic development, and the types of tourism called ecotourism have gained importance. In parallel with these developments, the natural and cultural resources with a national and international importance and the applicability and sustainability of ecotourism activities in protected areas, which are regarded as an important tool that will preserve biological diversity as a fortune and carry it to the future, have become more prominent. Above all, there is a need for criteria and indicator sets that will contribute to the measurement and monitoring of sustainability to ensure the sustainable management of ecotourism activities in protected areas. Although a large number of criteria and indicator sets that will serve the purpose of sustainable ecotourism management have been developed around the world, no criteria and indicator set that will serve the purpose has yet been developed in our country. The purpose of this study is to determine the criteria and indicators at the national level for sustainable ecotourism management to be carried out in protected areas. Therefore, potential criteria and indicators have been developed by using all kinds of scientific studies such as books, articles, papers and theses about protected areas, sustainable tourism and ecotourism, and such as ITTO Process, The Pan- European Forest Process, Montreal Process, Tarapato Proposal, Dry-Zone Africa Process, The Near East Process, Central America Process and CIFOR various criteria and indicator sets with UNWTO, GSTC that have been accepted around the world as materials
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".