Bibliographic record
Abstract
This thesis looks at the role of older North American pop music as cultural waste in new media environments. It builds on existing scholarship examining the political implications of collecting, recirculating and archiving cultural ephemera. I argue that as discredited and obsolete media, the discarded physical remains of failed or forgotten music— such as old vinyl records—provide personal and alternative ethnographies of North American mass culture. Crucial to this research is the concept of remediation, whereby media are made and remade in new conditions. In particular, I examine an assemblage of music I call 'B- music' (from B-movie) that is revisited primarily for its weirdness. Failed eccentrics, forgotten trends, indecipherable outsiders and other such curiosities are viewed as transgressive or revelatory after having been excavated and re-articulated as such. While such content has conventionally been relegated to the secondhand stores and donation bins that have constituted the networks of recirculation, they are increasingly accessible to less serious collectors and listeners through digitally mediated channels. I argue that remediating such content, or converting it to digital formats, making it available to global audiences via the internet, performs a valuable process in revisiting and reshaping the history of cultural industries.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.015 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".