Introduction to Part Two of <em>New Fronts in the Copyfight</em>
Bibliographic record
Abstract
This article introduces the second part of New fronts in the copyfight: Multidisciplinary directions in critical copyright studies (the first part of which appeared in DSCN Vol. 4 [2014]). The article surveys recent and ongoing developments of note in the global intellectual property regime, such as the Trans-Pacific Partnership, and relates these to the articles included in this second instalment of this series: "It's creativity, Jim, but not as we know it" by Carolyn Guertin; "Transproperty" by Daniel Downes; and the guest editor's review of Rosemary Coombe et al's collection Dynamic Fair Dealing: Creating Canadian culture online. Cet article présente la deuxième partie de New fronts in the copyfight: Multidisciplinary directions in critical copyright studies (dont la première partie a paru dans DSCN Vol. 4 [2014]). L'article enquête sur l'évolution récente et les développements actuels qu'il convient de remarquer au sein du régime mondial de la propriété intellectuelle, comme le partenariat transpacifique, et les rattache aux articles inclus dans la deuxième tranche de cette série : « It's creativity, Jim, but not as we know it » de Carolyn Guertin; « Transproperty » de Daniel Downes; et la critique de l'éditeur invité de la collection Dynamic Fair Dealing: Creating Canadian culture online de Rosemary Coombe et al.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.215 | 0.064 |
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".