International Agreements, Data Protection, and EU Fundamental Rights on the International Stage: Opinion 1/15 (EU-Canada PNR) of the Court of Justice of the EU
Bibliographic record
Abstract
In Opinion 1/15, the Grand Chamber of the Court of Justice of the European Union applied the fundamental right of data protection to a pending international agreement of the EU. In its first ruling on the compatibility of an international agreement with the EU Charter of Fundamental Rights, the Court found that a draft agreement between the EU and Canada for the transfer of airline passenger name record data could not be concluded in its current form, since it was adopted under the wrong legal basis and several of its provisions were incompatible with fundamental rights. This annotation deals with a number of important issues that the Opinion raises, in particular the legal basis for international agreements on data sharing; its implications for the fundamental rights to data protection and privacy; the role that international law played in the Opinion; the use of international agreements and adequacy decisions for data transfers; how the Court dealt with issues of foreign law; and the impact the Opinion may have on the EU’s conclusion of international agreements in the future.
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 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.014 | 0.022 |
| Scholarly communication | 0.021 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.029 | 0.024 |
| Insufficient payload (model declined to judge) | 0.004 | 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".