A policy tool for island transport cost inequality: Exploration of the application of the Transport Equivalent Threshold on Greek islands
Bibliographic record
Abstract
Many islands face accessibility problems that burden both the cost and the time of sea transport. In Greece, with more than 100 inhabited islands, the Transport Equivalent Threshold (TET) was recently introduced to support passengers (subsidizing ticket costs) and businesses (subsidizing transportation costs). The purpose of this study is to explore: (a) the spatial distribution of beneficiaries of TET; (b) the quantities, value and features of the freight transported to and from the islands; (c) to map the geography of the beneficiaries in relation to island size and location. Results reveal the unequal economies of Greek islands, and inter-island competition as well as the high disparities policy tools for businesses have to operate within. Moreover, the importance of radial transport links with the metropolitan area of Athens and the dependence of all islands on imports is highlighted. They also indicate the relative importance of geography in the magnitude and frequency of transport for goods and passengers among the Ionian and Aegean Seas, but also within the different clusters of the Aegean. The TET approach is one of the possible approaches that can and have been used to face transport and travel issues that people and businesses on islands face.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".