Rosemont/Chabanel : soundtrack for an industrial badlands
Bibliographic record
Abstract
During 1999 and 2000, I lived in a district of Montreal known for its textile factories. Vast, Borg-cube shaped monstrosities line the streets. Freight trains shudder past daily, the tracks littered with fabric offcuts and used plastic sheeting. At all hours of the day and night the factory machines whirr, filling the streets below with their chatter and the smells of solvent and dye. On freezing winter mornings, I would watch the workers arrive in their buses from the suburbs. North-Indian, Korean, Guatemalan, Croatian; the all-purpose undifferentiated mass of immigrant labour upon which modern economies prosper. The Rosemont and Chabanel districts are badlands, the industrial unconscious of modern trade. Rosemont / Chabanel is an attempt to render this environment as a sonic experience. Although electroacoustic sounds have been used, none of the sounds originate from the actual environment. The sonic environment is a constructed one, intensely processed, technologically mediated.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.047 |
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".