Bibliographic record
Abstract
Abstract The relationship between freedom of speech and copyright protection has 2.01 increasingly attracted the attention of copyright lawyers.1 They have become troubled by the impact on freedom of expression of the recent extension of See, eg, P Samuelson, ‘Copyright, Commodification, and Censorship: Past as Prologue but to what Future?’ and PB Hugenholtz, ‘Copyright and Freedom of Expression in Europe’, in N Elkin-Koren and NW Netanel (eds), The Commodification of Information (The Hague: Kluwer, 2002), 63, 239; M Birnhack, ‘The Copyright Law and Free Speech Affair: Making-up and Breaking-up’ (2003) 43 Idea: J L & Technology 233; D Fewer, ‘Constitutionalizing Copyright: Freedom of Expression and the Limits of Copyright in Canada’ (1997) 55 U Toronto Faculty L Rev 175; P Drahos, ‘Decentring Communication: The Dark Side of Intellectual Property’, in T Campbell and W Sadurski (eds), Freedom of Communication (Aldershot: Dartmouth, 1994), 249.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.030 | 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; 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".