<i>Say goodbye to my little FRAND</i> : is the withdrawal of the European Commission’s Regulation on standard essential patents a missed opportunity or a dodged bullet?
Bibliographic record
Abstract
Abstract The European Commission’s proposal for a Regulation on the licensing and enforcement of Standard Essential Patents (SEPs) aimed to revolutionize the global SEP licensing and enforcement landscape through a variety of interventionist measures. The proposal was widely welcomed in some quarters but roundly criticized in others, and it was ultimately withdrawn. This article examines the complexities of the current SEP licensing and enforcement landscape and the criticism that has been levied against the status quo. It goes on to assess the challenges that might have come with implementing key aspects of the proposed regulation, and the achievability of its stated objectives. It also considers the worldwide effect the regulation of this area of law might have had for patent owners, product manufacturers and small/medium sized enterprises and the broader implications for technological innovation and international regulatory harmony.
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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 | 0.016 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.018 | 0.034 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".