Innovative Deviance: A Theoretical Framework Emerging at the Intersection of Copyright Law and Technological Change
Bibliographic record
Abstract
This paper explores the relationship between emerging technology-enabled behaviors and established copyright law in the United States. Challenges implicated by recent technological developments have given rise to a consensus among policy-makers, scholars, public interest advocates, and various other stakeholders that copyright reforms are needed. Debates over what shape the potential reforms ought to take have been strident, unrelenting, and seemingly paralyzing to the cause. Meanwhile, courts have continued to adjudicate cases testing the balance between existing copyright doctrines and new methods of creating, managing, and sharing protected works. The paper describes a recent exemplar involving mass digitization, Authors Guild v. HathiTrust, and critically reflects upon the courts’ fair use analyses before articulating an emerging theoretical framework for understanding and explaining the intersection of copyright law and technological change based on the sociological concept of innovative deviance.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.007 | 0.129 |
| Scholarly communication | 0.015 | 0.021 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".