A STAR-based Cointegration Analysis of Globalization and Air Transport in Türkiye
Bibliographic record
Abstract
This study employs the smooth transition autoregressive (STAR) model-based cointegration tests developed by Kapetanios et al. (2006) and Maki (2010) to investigate the long-term relationship between air transport and globalization, including its economic, social, and political dimensions in Türkiye. STAR models reflect the smooth nature of real-world processes and can capture the complex and nonlinear relationships between variables that linear models struggle to represent effectively. We offer a novel methodological approach to examine the relationship between air transport and globalization in Türkiye, providing valuable insights for policymakers and researchers. Our empirical results reveal a long-term equilibrium relationship between air transport and overall globalization and the economic and political dimensions of the globalization index. These results imply that both variables move together in the long run. However, no cointegration was found between air transport and the social dimension of globalization.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".