International Comparative and Competitive Advantage of Post-Soviet Countries in Tourism
Bibliographic record
Abstract
In this study, the comparative and competitive advantage of Post-Soviet countries in the tourism sector is examined. Firstly, whether the tourism sector of the countries included in the sample developed between 1995 and 2018 was examined. Revealed Comparative Advantages Index which is developed by Balassa and Expanded Balassa Index were used to analyze the comparative and competitive advantage of countries, respectively, which are the main purpose of the study. The results of the study, which are calculated based on the data obtained from the database of the World Bank, provide information especially regarding the advantageous position of Georgia regarding Balassa Index. In addition to Georgia, Armenia, Kyrgyz Republic, Moldova, Tajikistan, Azerbaijan, Estonia and Uzbekistan have international comparative advantage and when the situation of the countries is evaluated over the EB index it is concluded to, Tajikistan and Georgia have strong, Kyrgyz Republic and Moldova have medium, Latvia, Estonia, Armenia, Lithuania and Belarus have weak competitive advantage. The research is important in terms of the policies that Post Soviet countries will form within the scope of tourism sectors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".