Bibliographic record
Abstract
Citation (2013), "List of contributors", Music and Law (Sociology of Crime, Law and Deviance, Vol. 18), Emerald Group Publishing Limited, Bingley, pp. vii-viii. https://doi.org/10.1108/S1521-6136(2013)0000018002 Publisher: Emerald Group Publishing Limited Copyright © 2013 Emerald Group Publishing Limited Heitor Alvelos ID + Institute of Research in Design, Media and Culture, University of Porto, UPTEC PINC, Portugal Cecilia Blengino Dipartimento d Giurisprudenza, Università degli Studi di Torino, Torino, Italy Victor P. Corona Department of Social Sciences, Fashion Institute of Technology, New York, NY, USA Manuel Cuadrado- García Departamento de Comercialización e Investigación de Mercados, Universitat de València, Valencia, Spain Mitch Daschuk Department of Sociology, University of Saskatchewan, Saskatoon, Canada Mathieu Deflem Department of Sociology, University of South Carolina, Columbia, SC, USA Serona Elton Department of Music, Media, and Industry, University of Miami, Coral Gables, FL, USA Jon M. Garon Northern Kentucky University Chase College of Law, Highland Heights, KY, USA Sara Towe Horsfall Department of Sociology, Texas Wesleyan University, Fort Worth, TX, USA Juan D. Montoro-Pons Departamento de Economía Aplicada, Universitat de València, Valencia, Spain Cynthia R. Nielsen Ethics Program, Villanova University, Wayne, PA, USA James Popham Department of Sociology, University of Saskatchewan, Saskatoon, Canda Danwill D. Schwender Foldenauer Law Group, APLC, San Diego, CA, USA Jean-Marie Seca Department of Sociology, UFR Connaissance de l’Homme, University of Lorraine, NANCY CEDEX, France Masaya Takahashi Department of Education, Saitama University, Saitama, Japan Book Chapters Music and law Sociology of crime, law and deviance Music and law Copyright page List of contributors Introduction: The laws of music If reagan played disco: Rocking out and selling out with the talking heads of political campaigns and their unauthorized use of music Graduated responses to online piracy: Approaches taken in the united states and around the world Music identities, individualization, and ownership shifts: Empowering a litigious paradigm of copyright protection The band: Artistic, legal, and financial structures which shape modern music The policy of electro-amplified popular music in France: The liberal context and the regulation of rebellious cultures Strategic Afro-modernism, dynamic hybridity, and bebop’s sociopolitical significance Cultural norms of Japanese folk and traditional music Scraping the barrel of analogue amnesia: The soft rescue of magnetic obscurity over the final embers of ‘expanded’ pop stardom Prison and pop Understanding deviant music Stolen or released music? The social construction of piracy in Italy Empirical insights into recorded music consumer behavior and copyright infringement
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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 | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.739 | 0.753 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".