Bibliographic record
Abstract
High volume in the form of high sound pressure level (SPL) is ingrained in the aesthetics of many forms of popular music, most obviously in rock and its associated sub-genres, but also in many other genres and styles including various forms of dance music, hip hop, reggae and electronic music. The primary site of expression of the notion of loud-as-good is in the performance of music in public spaces or venues (live, recorded or a blend of both). The reproduction of discourses of loud-as-good is woven through popular music culture, from bands in tiny rehearsal studios to the world record for “loudest” band (Deep Purple or The Who, depending on the year of publication of the Guinness Book of Records). Loud-as-good discourse has been satirised in other media: the “mockumentary”, This is Spinal Tap (1984) and Douglas Adams’ The Hitchhiker’s Guide to the Galaxy, both of which are addressed here. This essay identifies five discourses of loudness as they appear in music journalism, and in fiction. These are: loud-as-good, loud-as-bad; loud-as-good for the audience, but bad for the journalist; loud-as-good for the journalist, but bad for the audience; loud-as-irrational.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.041 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| 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".