Should digital files be considered a commons? Copyright infringement in the eyes of lawyers
Bibliographic record
Abstract
In this article, we draw on a survey conducted with elite upcoming lawyers from all around the world to shed new light on the ethical acceptability of file sharing practices. Although file sharing is typically illegal, our findings show that lawyers overwhelmingly perceive it as an acceptable social practice. The main criterion used by lawyers to decide on the ethical acceptability of file sharing is whether or not the infringer derives any monetary benefits from it. Further, our findings show that lawyers in the public sector (including judiciary and academia) are even more tolerant of online copyright infringement than those in the private sector. Interestingly, our data suggests that this is largely the result of self-selection: lawyers who lean more on the side of broad disclosure and social sharing tend to orient themselves toward the public sector. Implications for the current state of the debate on the reform of copyright law are discussed.
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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 | 0.010 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.026 | 0.019 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.021 | 0.013 |
| Insufficient payload (model declined to judge) | 0.020 | 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".