Decision-making in the Unified Patent Court: Ensuring a balanced approach
Bibliographic record
Abstract
The Unified Patent Court (UPC) will become a central player in the future development of European patent law. For this reason it becomes important to ensure that UPC‘s decision-making reflects the double-function of the Court as an adjudicator of individual disputes and a policy maker. Because of its institutional design, the UPC will be biased towards technology based values. Therefore, there is a risk that non-technical values and interests will be either overlooked or underdeveloped in UPC decision-making which is likely to jeopardize public trust and legitimacy of its decisions. This paper analyses how these blind spots can be covered in patent litigation before the UPC within the current legislative framework. The paper focuses on the role of UPC judges as case-managers and decision-makers, on the potential role of third party interveners, and addresses the key role of the parties in establishing the basis for UPC decisions.
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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 | 0.197 | 0.205 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.018 | 0.024 |
| Scholarly communication | 0.048 | 0.024 |
| Open science | 0.006 | 0.018 |
| Research integrity | 0.026 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 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".