The Air Connectivity Index: Measuring Integration in the Global Air Transport Network
Bibliographic record
Abstract
The authors construct a new measure of connectivity in the global air transport network, covering 211 countries and territories for the year 2007. It is grounded in network analysis methods, and is based on a gravity-like model that is familiar from the international trade and regional science literatures. It is a global measure of connectivity, in the sense that it captures the full range of interactions among all network nodes, even when there is no direct flight connection between them. The best connected countries are the United States, Canada, and Germany; the United States' score is more than two-thirds higher than the next placed country's, and connectivity overall follows a power law distribution that is fully consistent with the hub-and-spoke nature of the global air transport network. The measure of connectivity is closely correlated with important economic variables, such as the degree of liberalization of air transport markets, and the extent of participation in international production networks. It provides a strong basis for future research in areas such as air and maritime transport, as well as international trade.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".