Bibliographic record
Abstract
Twice in the last two years the Supreme Court of Canada, in the absence of legislative guidance from Parliament, has been called upon to resolve fundamental conflicts in applying the provisions of the Patent Act to unique characteristics of biotechnological innovations, particularly in relation to higher life forms. The result in each case has been a bare 5-4 majority. The lack of a strong majority on basic issues of patent law such as the statutory definitions of “composition of matter” and “use” is not surprising. The very nature of patentability as protection for innovation means that the interpretation of the Patent Act can never be finalized or definitive; protection of innovation requires an inherently indeterminate text in relation to key terms. This presumptively open-ended framework, however, is not particularly well-suited to the task of dealing with innovation involving life itself. Complex and controversial issues of innovation, knowledge management and ethics are being decided, with much uncertainty and unpredictability, by bare majorities. The time has long since come to recognize that the drafters of the Patent Act did not anticipate inventions that could reproduce themselves, and for Parliament to enact amendments accordingly.
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 | 0.033 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.053 |
| Scholarly communication | 0.020 | 0.015 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.051 | 0.028 |
| Insufficient payload (model declined to judge) | 0.004 | 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".