Bibliographic record
Abstract
recalls sitting at a Syracuse Symphony Orchestra board meeting in 1968, " listening to the usual crying about money, and I said , 'Gee, Jerry Lewis does this thing on television.Maybewecandosomething for orchestras."'In June of that year, Syracuse radio station WONO, which Fogel and a friend had purchased five years earlier and converted to a classical music format, broadcast the nation's first radio marathon.It raised $8,000 for the Syracuse Symphony."We'd only expected to raise $5,000, so that was a success," says Fogel.The next year the marathon raised $11,000, and just like that Fogel had developed the concept of using radio marathons to raise funds for orchestral organizations.The concept caught on with other symphonies, many of which asked Fogel to come and help them organize similar broadcasts.He has traveled to more than 60 cities, throughout the United States and in Canada, to act as a consultant on fund -raising radio marathons.He reports that radio marathons have raised more than $35 million for orchestras in the almost 10 years since they were widely adopted.
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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 | 0.000 | 0.000 |
| 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".