Data Protection, Data Transfers, and International Agreements: the CJEU’s Opinion 1/15
Bibliographic record
Abstract
Christopher Kuner Mi 26 Jul 2017On 26 July the EU Court of Justice (CJEU) issued Opinion 1/15, which is its most significant ruling on the international dimensions of data protection law since its 2015 judgment in Case C-362/14 Schrems (previously discussed in a Verfassungsblog debate).In Opinion 1/15, the Grand Chamber of the Court found that the draft agreement between the EU and Canada for the transfer of passenger name record (PNR) data may not be concluded in its current form, since several of its provisions are incompatible with EU fundamental rights law.As the Court's first ruling on the compatibility of a draft international agreement with the EU Charter of Fundamental Rights, the judgment has important implications for many areas of EU law.
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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 | 0.046 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.032 | 0.010 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.101 | 0.044 |
| Insufficient payload (model declined to judge) | 0.004 | 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".