Bibliographic record
Abstract
The Internet and the digitisation of content have allowed new pathways to production and distribution. This is positive from one perspective, as it allows many once-excluded individuals access to the creative process. However, technological innovation has also lowered "natural" barriers to widespread copyright infringement. Copyright owners have sought expanded copyright protection as a result. Different interests groups have variously responded. Some have declared copyright of little relevance. Others advocate recognition of "users' rights;" the view articulated in CCH Canadian Ltd v. Law Society of Upper Canada. I argue that while unchecked copyright expansion could be undesirable when thinking about the public domain, it may not be necessary to conceive of an extra layer of users' rights in order to achieve a balanced copyright. A workable compromise can be found in further consideration of authorship in copyright, a concept which dictates the nuances of copyright as a whole.
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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 | 0.030 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.025 | 0.029 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".