Bibliographic record
Abstract
This paper works to unveil the clandestine shift in patent law's normative base from a utilitarian justificatory rationale to a libertarian one; a trend the author refers to as libertarianism. By assuming that the social good is always attained by expanding patent rights in all domains, courts have dressed libertarian analysis in the commonly accepted language of utilitarianism. This surreptitious adoption of libertarian analysis is particularly disconcerting because it enables courts to avoid addressing the ethical and distributional effects of patent determinations. The marginalization of ethical and distributional concerns in patent discourse has been exacerbated by three (dubious) claims that courts, tribunals and legal commentators have offered to justify the judicial assumption of jurisdiction over patent eligibility for new classes of innovation: 1. that the determination of patent eligibility is merely a technical question of statutory interpretation; 2. that patenting is morally neutral; and 3. that the expansion of the patent regime is necessary for the development of technology-based industries. This paper argues that claim 1. is based on faulty reasoning, claim 2. is descriptively inaccurate and claim 3. lacks empirical support. Given the dubiousness of the above-mentioned justifications, the radical nature of the judicial assumption of jurisdiction over patent eligibility regarding new classes of innovation becomes clear. Traditionally, as a matter of institutional competence, courts avoided balancing complex issues of public interest in the absence of a strong signal from the legislature. With the advent of stealth libertarianism, revisionist courts have eschewed the complex balancing required for assessing the patent eligibility of new classes of innovation. In contrast, the author notes with approval that the Supreme Court of Canada in Harvard Mouse has resisted the trend toward stealth libertarianism by acknowledging that the patentability of higher life forms requires a level of analysis that exceeds the bounds of judicial competence. To guarantee a more just use of technology, we must ensure that our patent laws both create and reflect desired social outcomes as determined by enlightened and competent authorities. Given the multiple and multifarious competing interests at stake in issues of patent eligibility over new classes of innovation, the judiciary lacks both the capacity and the competency to make such determinations.
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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 | 0.035 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.007 | 0.073 |
| Scholarly communication | 0.024 | 0.032 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".