Exploring the Impact of International Tourism on Regional Sustainable Development: A Methodological Approach for Enhancing Effectiveness
Bibliographic record
Abstract
The main purpose of the article is to investigate strategies for enhancing the effectiveness of the impact of tourism on the sustainable development of the region.To do this, the main scientific task was to model and evaluate the impact of the impact of tourism on the sustainable development of the region.The prerequisites for the study were the low efficiency of tourism in the region, where over the past decades there has been practically no policy for the development of the recreational sector, where the authors of the article live.The object of the study is the system of sustainable development of the region.The research methodology involves the use of modern methods of analysis and modeling.As a result, we have obtained a graphical model and associated strategies for increasing the effectiveness of the impact of tourism on the sustainable development of the region.The novelty of the obtained results of the study lies in the development and application of a novel methodological approach to modeling the increase in the effectiveness of the impact of tourism on the sustainable development of the region.The study is limited by taking into account the specifics of only one particular region.This aspect will be expanded in further studies.A separate issue for further research will be the study of the impact of tourism not only on the sustainable development of the region of the Silesian Voivodeship, but also of Poland as a whole.
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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 | 0.026 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".