Bibliographic record
Abstract
This paper, commissioned for the now defunct UK Strategic Advisory Board for Intellectual Property, looks at some aspects of UK patent law and asks whether some of the activities it rewards deserve the protection they get. The argument is that patent law should more precisely match and reward the advance the inventor discloses, that patents should not be granted for activities that need no stimulus or are already adequately stimulated by other intellectual property laws, that specifications should disclose all the inventor knows about the invention to as wide an audience as possible, that only activities the patent holder and the public fairly expect to be included with the patent’s claims should be caught, and that patents should be enforced in ways that do not unfairly benefit patentees and unnecessarily restrain industry. While the paper deals with the specifics of U.K. law, many of the general points it makes - for example, on overbroad patents, overlapping protection, disclosure of best methods of practising the invention, overbroad claim interpretation and the injunction remedy - apply equally to the laws of other countries.
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 | 0.025 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.037 |
| Scholarly communication | 0.015 | 0.030 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.023 | 0.022 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".