Bibliographic record
Abstract
Using data collected by the author's firm as consultants in the recent ‘Blurred Lines’ case, in which the family of Marvin Gaye, Jr accused Pharrell Williams, Robin Thicke and Clifford Harris, Jr of infringing musical elements of Gaye's ‘Got to Give It Up’, this article addresses the relatively neglected issue of the apportionment of value that is directly attributable to an intellectual property asset. Such apportionment is particularly complex in the case of recorded music, which may include multiple copyright holders and requires two steps described in the article. The first is determining what portion of the copyright to a work is relevant to charges of infringement; the second is determining the multiple factors that contribute to the financial success of that work. The author argues that in this case, in which the supposedly infringed musical elements are covered by only half of one of the two relevant copyrights and in which much of the song's value is demonstrably attributable to non-copyright factors, considerably less than a quarter of the value of the ‘Blurred Lines’ could rightfully be attributed to the contested elements protected by Gaye's copyright.
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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 | 0.015 | 0.129 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".