Improving the Organizational Mechanisms of Domestic Tourism in The Socio-Economic Development of Regions as an Important Factor in Preserving the Environment
Bibliographic record
Abstract
This article discusses the improvement of organizational mechanisms for domestic tourism in the socio-economic development of the regions of the Republic of Uzbekistan. It substantiates that organizing this process is an important factor in preserving the environment. In organizing these processes, international experience, legislation, and applied methods have been thoroughly studied. Recommendations are provided regarding improving the organizational mechanisms of domestic tourism in the regions of the Republic of Uzbekistan and preserving the environment. Highlights: Domestic tourism boosts socio-economic development in Uzbekistan regions. Environmental preservation requires effective tourism management and organization. International experience, laws, and methods improve tourism mechanisms. Key words: the International Organization for Standardization (ISO) introduced the ISO 14001 (EMS), in England, the BS 7750 Specification for Environmental Management Systems; in Canada, CAN/CSA Z750-94: Guidelines for an Environmental Management System; in the EU, EMAS; and the international “European Center of Ecological and Agrotourism” (ECEAT). ECEAT, “European Center of Ecological and Agrotourism” (ECEAT).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".