The Philosophy behind Fair Use: Another Step towards Utilitarianism
Bibliographic record
Abstract
iParadigms, a company involved in plagiarism detection, was hold not liable for the unauthorized use and archival of students’ papers. Both the District and Appellate Courts of Virginia, in fact, maintained that the exception of fair use applied to the copyright infringement action. As the relevant facts represent a novelty in case law, it might plausible the hypothesis that iParadigms precedent is not going to be followed in forthcoming cases. This investigation is an attempt to appreciate the possibilities that such an event could happen. In particular, the attention is focused on the special nature of the Copyright Act which is simultaneously backed by opposite theoretical backgrounds such as utilitarianism and moral desert as well as personhood theories, among others. The prevailing of one theory over another shall depend on how liberally or strictly the fair use doctrine shall be interpreted. Despite findings demonstrate judges have applied the fair use doctrine according to the correct conceptions of justice, the discussion ends up recommending a new system of plagiarism detection that drastically reduces the likelihood of copyright infringement actions.
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 | 0.065 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.124 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.011 | 0.024 |
| Insufficient payload (model declined to judge) | 0.003 | 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".