The Role of Utility Models in Patent Filing Strategies: Evidence from European Countries
Bibliographic record
Abstract
We examine the role of utility models (UM) in patent filing strategies. With an extensive patent family data from European countries, we explore the structures and characteristics of patent families, which include UMs. A simple typology of patent families with UM members is introduced. We document that the geographical scope of most patent families with UM members is purely national, which is in line with the conventional view that the UM mechanism covers technologically and economically marginal inventions. However, the image of a UM as a signal of a minor invention is an oversimplification. Applicants exhibit a mixture of uses for the UM and there exists a subset of UM filings linked to inventions the inventive step of which meets or exceeds the threshold required for patent protection. Some UMs are members of international patent families, indicating that applicants may have some strategic motives to use UMs in international filing. The findings highlight that both types of IPR documents (UMs and patents) should be taken into account when working with data on patent families, analysing patent filing strategies, and constructing patent-based indicators such as patenting propensities.
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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 | 0.031 | 0.131 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".