Migration of European Judicial Ideas Concerning Jurisdiction Over Google on Withdrawal of Information
Bibliographic record
Abstract
Google's position in the information market has caused interesting legal developments insofar as its obligations are concerned. On various grounds, courts worldwide have begun to impose injunctions on Google that require the company to withdraw the search results—in fact, information sources—that its search engines provide. This article looks at this recent phenomenon of imposing obligations on Google to withdraw some information through the lens of judicial dialogue. In particular, we analyze the “inspiring” role of the Court of Justice of the European Union (CJEU) in itsGoogle Spainjudgment. This case represents a clear migration of some ideas that might be perceived as universal. Some courts outside of Europe—such as Canada—are gaining “inspiration” from the CJEU'sGoogle Spainjudgment in order to reinforce their own decisions. The legitimacy and techniques of this process are also discussed in this article.
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 | 0.024 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.039 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.017 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".