Invoking Article 73 TRIPS in good faith: no recourse to ‘security exceptions’ for Russia’s violation of TRIPS
Bibliographic record
Abstract
The Russian war against Ukraine began in February 2014, when Russia invaded, annexed Crimea and triggered a separatist rebellion in the east, followed by the Russian army's overt invasion of the eastern Ukraine to support the rebels. 'International sanctions have been imposed during the Russo-Ukrainian War by a large number of countries, including the United States, Canada, and the European Union against Russia following the Russian invasion of Ukraine, which began in late February 2014 [] In response to the annexation of Crimea by the Russian Federation, some governments and international organisations, led by the United States and European Union, imposed sanctions on Russian individuals and businesses. As the unrest expanded into other parts of Eastern Ukraine, and later escalated into the ongoing war in the Donbass region, the scope of the sanctions increased. The Russian government responded in kind, with sanctions against some Canadian and American individuals and, in August 2014, with a total ban on food imports from the European Union, United States, Norway, Canada and Australia' .
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".