BEYOND THE CRISIS: INTERNATIONAL INSTRUMENTS ON DIGITAL PIRACY
Bibliographic record
Abstract
This paper highlights the importance of international law with respect to the international business and legal debates on the means to tackle digital piracy. Indeed, a number of multilateral instruments provide for a legal framework to cope with several controversial issues: the extent of government regulation and oversight, the power to block access to certain websites or the role to be played by an Internet Service Provider. However, there is an urgent need to perfect the legal framework and to adopt a specific international treaty, in order to improve global standards for the consistent enforcement of intellectual property rights (IPR). The international society could seize the current negotiations on the so-called Anti-Counterfeiting Trade Agreement (ACTA), but IPR enforcement measures should not be circumvented by trade negotiations. It is time for the ACTA negotiators to bear in mind that, in a world that is going digital, Internet pirated goods also challenge business models, innovation and creativity.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.020 | 0.032 |
| Open science | 0.001 | 0.018 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".