Bibliographic record
Abstract
Almost since its inception, punk has been declared dead. What does it mean to live attached to something that is always, at least a little bit, gone? Examining how Justin Pearson merges personal accounts of death and mourning with a sense of punk that is rooted in loss in his memoir of his participation in a North American punk culture since the 1990s, From the Graveyard of the Arousal Industry, this article considers how a focus on living in the wake of the death of punk might shift scholarly and popular narratives told about punk. Punk outlives its death in the 1970s with a redemptive rebirth in which it became the subject of an anti-capitalist narrative. The article considers how Pearson’s memoir explores a different framework by insisting that punk may not be able to separate itself from the wider world, and that while this might appear to deal a death blow to punk, it also names a persistent set of conditions that define punk. After placing the memoir in the context of this redemptive account of punk as well as among those who see its limits, the article offers an analysis of several scenes addressing personal losses that merge with Pearson’s attachment to punk-as-something-dead-and-gone. The deaths that Pearson associates with punk rock are personal, but they also register the larger significance of loss for a subculture that cannot stop declaring its own demise, including especially the loss of a fantasy that sees punk as a refuge from the world.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.019 | 0.028 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.008 |
| 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".