Toothless Trade? Implications of the Federal Circuit’s ClearCorrect Decision for the Enforceability of Intellectual Property Protections in Digital Trade under USMCA
Bibliographic record
Abstract
Digital trade is growing faster than trade in goods and services and comprises a key area for innovation and intellectual property concerns. The United States-Mexico-Canada Agreement (“USMCA”) acknowledged this development by including chapters devoted to both digital trade and intellectual property. In 2015, the Federal Circuit held that the International Trade Commission (“ITC”) does not have jurisdiction over unfairly traded digital goods. Without exclusion orders issued by the ITC, the United States lacks a powerful tool to enforce the USMCA provisions protecting intellectual property in unfairly traded digital goods. This comment explores the implications of the Federal Circuit’s 2015 ClearCorrect decision for the United States’s enforcement obligations under USMCA and provides options to intellectual property rights holders and practitioners interested in protecting the domestic industry’s digital goods from intellectual property rights infringement.
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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 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.052 | 0.033 |
| Insufficient payload (model declined to judge) | 0.006 | 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".