Music as a Cosmopolitical Practice
Bibliographic record
Abstract
Music as a Cosmopo liti cal Practice 1 Yesterday eve ning we went to a free show in Scarborough, one of the annual Feast in the East events-this time in a park on Prairie Drive, against the train tracks, with high-rises looming in most directions, mostly Bangladeshi families playing in the park, dense, exuberant green vegetation everywhere almost growing visibly in the short steamy Canadian summer.A free dinner for every one was served-a bowl of curried vegetables, a bitter melon salad, and a slice of grilled rice.Kids played on the swings, little groups of people sat on the grass and ate together.There were three acts billed-Sandro Perri, Bernice, and New Chancebut in the end only Sandro Perri played.We spread a towel out on the grass and ate and Sandro's band started playing.For their second song, they played "Double Suicide, " this song that I'd last heard Sandro sing with Ryan Driver at Cinecycle in maybe 2005 or 2006.They'd projected the Japa nese movie of that name over their performance-in fact, I think that was the name of the duo too.After they finished the song, they started another and it began to rain torrentially.I ran to the car and brought back four umbrellas, throwing them on the blanket.It really started to rain hard so we all clustered under the mass of umbrellas as the ground slowly flooded.We juggled the umbrellas around to stop the rain coming in between the cracks.The kids laughed.There wasn't
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.046 | 0.009 |
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".