Sound affects: Visualizing music, musicians and (sub)cultural identity in BECK and Scott Pilgrim
Bibliographic record
Abstract
Abstract This article discusses the portrayal of popular music in comics as both a product of sensory and emotive experience, and as a determinant of social identity and labour. To this end, it focuses on the Japanese serialized manga BECK and the Canadian graphic novel series Scott Pilgrim. These two works offer comparable perspectives on music and the social mythos of musicianship, as well as sharing similar young male protagonists and social contexts, despite their disparate settings in Tokyo and Toronto, respectively. Through a comparative reading of these texts, this analysis examines contemporary comic book techniques as well as the cross-cultural dynamics of Japanese and Anglo-American comic book cultures, specifically with regard to the portrayal of workers in fields of cultural production. In order to examine their interrelated depictions of music as both sensorial experience and enactment of collective identity, I first draw on the canon of comic book semiotics established by Scott McCloud, Ian Hague, and others to examine the techniques employed by these texts in communicating music as an emotive sensorial experience. In particular I will concentrate on their use of diagrammatic techniques and visual caricature as a means of communicating music – not through attempted synaesthetic effects, but rather through emotive evocation. Second, I look at their representation of musicianship as an area in which the mythology of artistic entrepreneurialism coexists with imperatives of collective identity and lifestyle. I examine the sociologically idiosyncratic manner in which these comics reflect and build upon these mythologies through the filters of class, cultural and generational identity, creating narratives that at times perpetuate – and at others subvert – the grand entrepreneurial narratives ascribed to musicianship within contemporary neo-liberal notions of creative labour.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".