Unusual canvasses: resolving copyright infringement through the lens of community customs
Bibliographic record
Abstract
The evolution of video game technology is outpacing intellectual property law. As augmented realities and online gaming environments continue to collapse the distinction between real and virtual worlds, they have rendered traditional frameworks for copyright law unworkable. Gaming environments were traditionally circumscribed by the magic circle. Video games now interact with the outside world in a way that obscures the divide between the public domain and the private. Such disruption undermines copyright's core purpose of balancing interests, and transforms issues such as implied license, fair dealing, and moral rights into enigmas. This article proposes a framework that redraws the magic circle using the consent-based customs of gaming communities. Only those who play at the vanguard have the expertise to reconcile copyright with modern video games without constraining creativity or innovation. Deferring to community norms restores compatibility between copyright and unusual canvasses while preserving the integrity of these interesting works.
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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 | 0.017 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.011 | 0.050 |
| Scholarly communication | 0.019 | 0.022 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".