Analysis of the Status and Potential of the Passenger Transport Market in China and Central Asia Inspiration for the Initiative «One Belt One Way»
Bibliographic record
Abstract
Central Asia, being an important zone in the Silk Road Economic Belt of the China Road «One Belt-One Way», is an important economic channel for China, connecting European countries by land. Transport communication is the basis of the work of the initiative «One belt-one path», therefore it is important and priority. Although the development of land connections (railways, highways) between China and Central Asia has made significant progress, passenger services, especially air passenger services, are still underdeveloped. The paper explains the state of development and existing problems of the bilateral air passenger transport market between China and Central Asia through the data analysis and policy studies of the «Bilateral Air Agreement». Three policy recommendations are put forward within the framework of the «One Belt-One Way» initiative. First, China and five Central Asian countries should use the platform created by the initiative «One Belt-One Way» to actively negotiate new bilateral air agreement between governments in the field of law, airports of general aviation, capacity and airline access to further ease regulations. Considering concerns that five Central Asian countries may have regarding the protection of their national airlines, the negotiation of an aviation agreement between China and Central Asia may use a model of negotiations between US and Canada on bilateral aviation agreement. Second, given the capacity of airports and rapid economic development of China’s second and third level cities, Governments’ preferential airport policies in China’s second- and third-tier cities could be extended to attract Chinese and Central Asian airlines to operate direct flights between these cities and Central Asia. Third, to allow and encourage private and budget airlines to enter China-Central Asia airline market. These airlines can use their own price advantages to open up new markets that are not sufficiently attractive to traditional airlines.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".