Breaking barriers: The link between stronger IPRs and trade in services
Bibliographic record
Abstract
As innovation becomes more prevalent and systematically integrated into service industries, service firms increasingly turn to intellectual property rights (IPRs) as a means of safeguarding their intellectual assets. The reliance on these legal rights becomes even more pronounced when service companies endeavour to expand their global reach and tap into international markets where the protection of IPRs is relatively weak, and imitation is more widespread. Disparities in the level of IPRs protection and enforcement across countries can pose significant barriers to cross-border trade and investment in service sectors where the safeguarding of intellectual property (IP) is fundamental. The risk of IP infringement and the limited protection afforded to patents, copyrights and trademarks in certain countries can discourage the expansion of businesses into these markets, limiting the overall growth and accessibility of services in those areas. This paper studies the relationship between trade in services and the strength of IPRs protection at the international level. More specifically, it uses data for 94 countries over the period of 1990-2010 to put forward new empirical evidence about the impact of global strengthening of IPRs protection on cross-border trade in services.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".