Accounting of Profits to Remedy Biotechnology Patent Infringement
Bibliographic record
Abstract
A number of important agricultural biotechnology patent disputes have arisen in Canada since the 2004 Supreme Court of Canada decision in Monsanto v. Schmeiser. Typically, defendants no longer contest issues of patent validity or infringement. Instead, the controversies have shifted to discussions about applicable remedies for infringement. The Schmeiser case ostensibly marked a fundamental change in the appropriate method for conducting an accounting of the profits that a defendant infringer must disgorge to a plaintiff patentee. The remedy of accounting of profits in patent cases, however, remains mired in definitional and conceptual confusion, which the Schmeiser case has brought to the forefront of disputes. The lack of clarity and certainty is harmful to all stakeholders in the patent system. This article makes three key contributions in the field of agricultural biotechnology patents. First, it exposes a largely unrecognized problem pertaining to the legal remedy of accounting of profits for patent infringement. To address this problem, the article corrects misunderstandings about recent court decisions pertaining to the accounting of profits remedy. Second, the article critically examines the discourse used to discuss accounting of profits, which includes sometimes inconsistent concepts, terms, and definitions. This article proposes strategies to facilitate definitional and conceptual coherence in order to establish a framework for future jurisprudence and scholarship on this topic. Finally, the article provides insights into the unsustainability of current trends in this area of law.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".