Bibliographic record
Abstract
This paper studies how the commercialization of innovation affects patent disclosure. I measure the innovation disclosure by using textual analysis methods to construct the readability scores of each patent's detailed description, background, and summary texts. To identify the causal impact of innovation commercialization on innovation disclosure, this paper uses the difference-in-difference approach. First, this paper uses the 1980 Bayh-Dole Act, which gave universities potential realization of the economic benefits of the inventions as an exogenous shock and leverages the readability change of university patents and non-university patents. Second, this paper considers the technology transfer offices (TTOs) establishment as another exogenous shock of innovation commercialization to patent inventors. This paper finds a decrease in readability in patent detailed description by inventors affiliated with universities after the 1980 Bayh-Dole Act and the TTO's establishment. Such decrease in readability did not apply to patent background and summary text. This paper points out a possible strategic innovation disclosure behavior, a finding that when inventors foresee innovation commercialization, they would strategically decrease the readability of patent detailed descriptions and lower openness in sharing how to make and use the invention.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".