Music and Canadian Nationhood Post 9/11: An Analysis of Music Without Borders: Live
Bibliographic record
Abstract
Cultural memory] is a field of contested meanings in which [people] interact with cultural elements to produce concepts of the nation, particularly in events of trauma, where both the structures and the fractures of a culture are exposed.(Sturken 2-3)The terrorist attacks of September 11, 2001, were followed by innumerable artistic outpourings: music, film, and literature were among the many cultural expressions that raised funds for victim relief and helped us come to terms psychically with a previously unthinkable event.Within the United States, a series of benefit concerts were quickly organized; through these events, the structures of a culture were evident (the richness of Western popular music) as were the fractures (the vulnerability of musicians live from undisclosed locations for fear of further attacks).On September 21, 10 days after the attacks, the first mass-mediated benefit concert, America: A Tribute to Heroes, aired on stations both within the United States and internationally.On the weekend of October 20-21, more concerts ensued in the United States: The Concert for New York City (New York), United We Stand (Washington DC), and Country Freedom Concert (Nashville) brought together millions of viewers in an attempt to raise funds, bind together again a wounded-and still bleeding-American community.That same weekend, on the other side of the 49th parallel, millions of Canadians were watching Music Without Borders: Live, a benefit concert held in Toronto, Ontario.Unlike the earlier concerts that raised money for American victims of the 9/11 terrorist attacks, this concert was held as a benefit for Afghani refugees.This concert, then, marked a distinct change of focus relative to the previous events.While this shift
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".