Prof Carys Craig: Non Expressive Use. Right to Research in International Copyright Seminar 6.2.
Bibliographic record
Abstract
This cutting edge seminar series looks at legal academic writings at the intersection of intellectual property, human rights, text and data mining (TDM) research, international law, and advanced legal theory. It is intended for advanced students writing a major research paper on the topic.\nSEMINAR 6 part 2: Professor Carys Craig of Osgoode Hall Law School, York University, Canada talks about limits to copyright protection which form the basis of a Right to Research. Professor Craig is author of Craig, Carys J. (2017) "Globalizing User Rights-Talk: On Copyright Limits and Rhetorical Risks," American University International Law Review: Vol. 33 : Iss. 1 , Article 1.\nWhat are the human rights duties of states with relation to copyright and the right to research? What is the utility, or danger, of framing research interests as “rights”? What do TDM researchers need to do to perform their research? How do any of these steps implicate copyright or other exclusive rights? How does lack of copyright permission distort research outcomes? How does US law and EU law approach the issue of exceptions for research uses? How has the openness of fair use and fair dealing standards been by courts to permit TDM and other research uses? Is the openness unique to common law countries? In what ways do licensing practices enable or form barriers to TDM research in practice? These are just a few of the questions considered by our eminent group of scholars and writers over the 15 weeks of this seminar series.\nABOUT THE SERIES Promoting “learning” and “science” were among the first purposes of early copyright laws. And human rights laws require states to respect, protect and promote rights to impart and receive information and to benefit from advances in science. This lecture series brings these two strands of law into conversation, and perhaps conflict, to explore the actual and ideal dimensions of the right to research in copyright law. The lectures discuss legal academic writings at the intersection of intellectual property, human rights, text and data mining research, international law, and advanced legal theory. Each lecture is being edited and published under an open license to enable reuse in educational and other contexts.\nABOUT THE HOST Professor Sean Flynn teaches courses on the intersection of intellectual property, trade law, and human rights and is Director of the Program on Information Justice and Intellectual Property (PIJIP). At PIJIP, Professor Flynn designs and manages a wide variety of research and advocacy projects that promote the public interest in intellectual property and information law and coordinates PIJIP’s academic program.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 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; both teacher heads agree on what is shown here.
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".