The Heterogeneous Effects of the Music Modernization Act and Co-Occurring Federal Regulation on the Release of New Music in the United States
Bibliographic record
Abstract
I examined the impact of the Music Modernization Act (MMA) and a co-occurring regulation on the release activity by composers and musical performers. The analysis uses a negative binomial count model with artist fixed effects to identify incremental release activity. Demographic and music copyright covariates were included to identify heterogeneity. While not impacting release activity overall, I identified increased release activity among composers (increasing with composer credits) as well as younger and female performers. These findings are observed in two instances: (1) during the post-period after the MMA was enacted and (2) during the negotiation period while the MMA was written and debated. Additionally, while there has been a significant increase in the release of singles, this phenomenon appears to be driven by the growth of music streaming. This work identifies the extent to which this new law and federal regulation have encouraged recording artists to increase their release activity.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".