Bibliographic record
Abstract
The Law and Technology.- An Introduction to the Historical Development of Copyright Law and Copyright Exceptions.- The Shaping of Modern Copyright Law and Its Application to Higher Education Institutions.- The Law, Technology and Higher Education Institutions.- Higher Education Institutions: Development and Effect on Copyright Law.- An 'Invitation' to Copy? Case Studies from Australia, the United Kingdom and Canada.- The Law, Technology, Higher Education Institutions and Copyright Collecting Societies.- Copyright Collecting Societies: An Economic Insight and Their Significance in the Digital Age.- Show Me the Money: A Case Study into the Copyright Licensing Agency.- Solutions for the Digital Era: The Academic Author and Publisher in the Digital Era.- Conclusion: Recommendations for Academic Authors and Collecting Societies - A Proposal for the Future.
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 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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.022 | 0.023 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.055 | 0.009 |
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".