Protecting Intermediate Innovations When Ideas Are Scarce: Patents or Secrecy?
Bibliographic record
Abstract
ABSTRACT Patenting an intermediate research innovation can lead to competition for the development of a final commercial innovation and potentially induce wasteful duplicative R&D efforts. This study examines the effects of different protection strategies and patent life on the incentives to protect an intermediate innovation by considering a two‐stage sequential innovation model. In this model, the success of a patentable final innovation depends on information about prior intermediate innovations and on complementary inspiration received by innovators. Protecting an intermediate innovation through secrecy can be socially superior if the final innovation involves a high cost and the idea essential to its implementation is common. Acquisition of specialized assets under patenting may increase duplication of resources, and secrecy can act as a social control to limit the entry by many firms. If the idea for the final innovation is scarce, on the other hand, patenting can be optimal for both the innovator of an intermediate innovation and society, and the innovator's incentive is well aligned with social welfare. A broad patent scope can facilitate the adjustment of patent life to align private incentives with the social optimum when the idea for the final innovation is scarce.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".