Turkey’s Role as a ‘Trans-European’ Energy Corridor
Bibliographic record
Abstract
Pronounced European Union (EU) reliance on oil and gas imports is exacerbated by the nature and limited number of its source regions. As Russia supplies one-quarter of EU gas consumption and 40 per cent of its total import requirements, while Middle Eastern Organization of Petroleum Exporting Countries (OPEC) states account for a slightly larger fraction of the EU’s imported oil, it makes political–economic sense for the EU to diversify its supply sources (European Commission, 2001, p. 2). Nonetheless, despite advocating greater diversification of energy sources and suppliers, the European Commission (Ibid., pp. 22–3) understands that the present profile of EU hydrocarbon dependence on Russia, the Caspian, the Middle East and North Africa is unlikely to change markedly. Especially in the context of EU–Russian energy relations, the EU has recognised Turkey’s potential value as a relatively secure and independent route for importing non-Russian energy supplies (Tekin and Walterova, 2007). This chapter analyses the role of Turkey as an independent (of Russia) conduit for third-party (notably Caspian and Middle Eastern) energy supplies to Europe, while remaining cognisant of the distinct possibility that Turkey, which is also highly dependent on Russian energy (especially gas) supplies, could also emerge as a new conduit for routing these supplies to the EU area. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".