Risky Gifts and Uncertain Business: A Discussion of Results from a Survey on Commissioning in New Music
Bibliographic record
Abstract
What are the risks involved in commissioning new music? Through interviews with 24 commissioners, performers, and composers based in Canada, the us , Australia, and France, we develop a model of the different types of risk encountered during the commissioning process. Despite providing the money for a commission, we found that commissioners are least exposed to financial risk as it is classically defined; commissioning fees really do behave like the philanthropic gifts they are legislated to be. Composers were likewise little exposed to financial risk, concerning themselves instead primarily with the uncertainty inherent to the creative process. We found that it is actually performers who are most exposed to financial risk, especially when they act as “middlemen” between commissioning bodies and composers. Burdened with compliance to a variety of Occupational Health and Safety laws and cash-flow issues stemming from conflicting outcomes and funding schedules, we found that performers were caught in a pincer between composers’ desires to take aesthetic risks and the obligations created by the philanthropic gift.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".