Bibliographic record
Abstract
Introduction Over the edge - Roger Beebe (University of Florida), Denise Fulbrook (Duke University), Ben Saunders (University of Oregon) Discourses/Histories Same as it ever was? Rock Culture. Same as it ever was! Rock Theory - Lawrence Grossberg (University of North Carolina at Chapel Hill) Elvis everywhere or the New Musicology meets Popular Music Studies in a Post-Classical World - Robert Fink (UCLA) Think about What You're Trying To Do To Me: Rock Historiography and the Construction of a Raced-based Dialectic - John J. Sheinbaum (University of Denver) Hijacked Hits and Antic Authenticity: Cover Songs, Race and Postwar Marketing - Michael Coyle (Colgate University) New Spaces / New Maps Why isn't Country Music Culture? - Trent Hill (University of Washington) Everything and the Girl: Feminism, rock Music and the Cultural Construction of Female Youth - Gayle Wald (George Washington University) Satellite Rhythms: Channel V, Asian Music Video and the Transnational Gender - Lisa Ann Parks (University of California, Santa Barbara) The Feminization of Rock - Tony Grajeda Rock's Reconquista: Space, Sound and the Music of America - Josh Kun (UC Riverside) Desires/Affects A Fan's Notes: Identification, Desire and the Haunted Sound Barrier - Warren Zanes Re-Mapping the Present: Kurt Cobain and the Future of Nostalgia - Roger Beebe (University of Florida) DC Punk and the Production of Authenticity - Jason Middleton Queen Theory: Notes n the Pet-Shop Boys - Ian Balfour (York University, Ontario)
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.485 | 0.165 |
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".