Beyond Theories: The Intellectual Property Dynamics in the Global Knowledge Economy
Bibliographic record
Abstract
This Article critically examines the inadequacy of theoretical postulates on intellectual property. It acknowledges that theorizing around intellectual property is an important ongoing but elusive intellectual adventure that is critical for law and policy direction on intellectual property. Perhaps, at no time is this fact more obvious than in the extant post-industrial epoch or the era of Global Knowledge Economy (“GKE”). The latter is spurred by advances in bio- and digital technologies. Both phenomena drive significant shift and transition in intellectual property jurisprudence and in the tide of innovation from physical to life sciences. They also supervise implosions in new and complex domains or sites for knowledge and information generation. As its feature, the global knowledge economic order is undergirded by an institutional and structural shift in international intellectual property lawmaking and governance, provoking a serendipitous counter-regime dynamic in diverse sites for contestations around intellectual property. The pivotal role of intellectual property in the GKE presents intellectual property as an increasingly multidisciplinary subject with complex issue linkages in virtually all fronts, including public health, human rights, biodiversity, biotechnology, biopiracy, the environment, ethics, culture, indigenous knowledge, electronic commerce, and research ethos. Overall, these and many more issue linkages to intellectual property are part of the latter’s open-ended dynamics in the GKE. They are constitutive of a myriad of factors that task and shape policy and theory on intellectual property as the knowledge economy continues to unravel.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.056 |
| Scholarly communication | 0.017 | 0.041 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".