Bibliographic record
Abstract
This article explores the relationship between arbitration courts and the preliminary reference procedure foreseen in Article 267 TFUE. It starts by explaining the importance of preliminary references in the development of legal integration in the European Union. Afterwards discusses the case law of the Court of Justice of the European Union concerning the admissibility of preliminary references sent by arbitration courts. Special attention will be given to the “Merck Canada Inc.” order, in which the Court of Justice answered a preliminary reference sent by a compulsory Portuguese arbitration court established by law to rule on intellectual property conflicts regarding generic drugs . I argue that in “Merck Canada Inc.” the Court of Justice should have refused to answer the questions submitted because the referring arbitration court was not a last instance court and did not satisfied structural requisites of a “court or tribunal of a Member State”. The same does not apply to tax arbitration courts, which not only fulfil those requisites, but should also be considered as “courts or tribunals of a Member State against whose decisions there is no judicial remedy under national law” submitted to the obligation to refer foreseen in §3 of art. 267 TFEU.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.016 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 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".