Bibliographic record
Abstract
This paper is one of the first attempts that sheds light on the gendered practices in the patent examination process. The findings reveal the share of female examiners and female inventors has increased over time but is still considerably low. Along these lines, when the patent examiner is a woman, the granted patent comprises a higher contribution of women inventors. These results are persistent when controlling for patent characteristics, collaboration type, sectors, and technological fields. Moreover, the processing time is longer when the examiner is a woman. This raises the question of whether female examiners’ requisitions might be more challenged by the patent representative(s) and inventors (of whom the majority are men) than those of male examiners; or of whether male examiners favor patents with a higher share of male inventors involved. Along these lines, patent attorneys/agents play a significant role in the examination process, as these are who represent the inventors and are in direct communication with the patent examiners. This paper highlights that in all the sectors and fields, the lowest share of female inventorship is associated with patents represented by male attorney(s) or agent(s) to a male examiner. The opposite of this trend is also applicable to female-examined patents, which contributes to addressing the latter question and suggests the likely presence of gender homophily in the patent examination process. Patent claims and patent citations are two measures of technological applicability and impact. These two measures are correlated. Interestingly, the average number of claims is higher for female-examined patents, while the citation impact of the patents is lower. This finding, combined with the fact that women receive lower citation rates for their patents, presents an important implication for gendered practices in citations in patents. These practices could induce stark imbalances in gender and inclusion in patenting, as male examiners are responsible for 81% of total patents granted in the USPTO. This study also sheds light on the importance of open innovation and collaborative entities in addressing gender disparities in patenting, as women are shown to be more involved in patents granted to more than one entity. This study brings forth one of the possible elucidations for gender differences in inventorship and calls for gender-responsive policy mechanisms to provide women an environment conducive to more patenting engagement.
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 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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".