Tax Obstacles for the Development of an Effective Euro-Mediterranean Free-Trade Area. An IFTA model for the European Union?
Bibliographic record
Abstract
As we know, the European Union has faced the challenge of harmonization in the tax field with varied results. We may think that the advanced harmonization in indirect taxes (custom duties, VAT and excise duties) has reduced the distortions that they may create in the intra-EU commerce. Far from this assumption, in the paper we will underline how the lack of a complete harmonization may create competitive advantages in certain countries and sectors. Specifically, we will examine how the road haulage sector is affected by the differences in diesel excise duties among Member States. The proposal for a Euro-Mediterranean Free-Trade Area would face the same problems as the European Union. If there are distortions inside the European Union, the extension of the free trade area to other mediterranean countries would possibly worsen it. This is why we suggest the establishment of a system equivalent to the IFTA (International Fuel Tax Agreement), existing in the United States and Canada, in order to achieve an efficient haulage system free of tax distortions.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".