‘If you got a tape on, you’re committed’: The revival of cassette tapes in Toronto’s New Wave of Traditional Heavy Metal scene
Bibliographic record
Abstract
Abstract At the height of music digitization and dematerialization, we still find collectivities of people who use obsolete forms of music media not out of necessity, but as a conscious and meaningful choice. This article focuses on a case study of a surprising revival of cassette tapes in the New Wave of Traditional Heavy Metal (NWOTHM) scene in Toronto, Canada. I consider two broad questions. First, if the music of the bands in the scene can be easily downloaded or ripped off of a CD, and conveniently stored on computers and other devices, what is the appeal of cassette tapes for their consumers? And second, what new meanings have been ascribed to cassette tapes in the Toronto NWOTHM scene – has the main function of cassettes as a music storage medium changed entirely? In this article, I (1) propose that Toronto NWOTHM scene members have rekindled an attraction to physical media formats to close the tangibility gap between music and listener; (2) suggest that subjective media associations between various time periods and/or music genres foster the historically informed consumption of cassettes; (3) demonstrate these two points in the traditional heavy metal subculture in Toronto and (4) outline new meanings that cassettes have undertaken in this context, such as souvenir, materialization of subcultural capital and symbol of commitment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.025 | 0.018 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".