Bibliographic record
Abstract
Book Summary: Canada's Prince Edward Island is home to one of the oldest and most vibrant fiddling traditions in North America. First established by Scottish immigrants in the late eighteenth century, it incorporated the influence of a later wave of Irish immigrants as well as the unique rhythmic sensibilities of the Acadian French, the Island's first European inhabitants. In "Couldn't Have a Wedding without the Fiddler," renowned musician and folklorist Ken Perlman combines oral history, ethnography, and musical insight to present a captivating portrait of Prince Edward Island fiddling and its longstanding importance to community life. The book draws heavily on interviews conducted with 150 fiddlers and other Islanders, whose memories colorfully brings to life a time not so very long ago when virtually any occasion - wedding, harvest, house warming, holiday, or the need to raise money for local institutions such as schools and church - was sufficient excuse to hold a dance. And in those days, you simply couldn't have a dance without the fiddler!Perlman explores how fiddling skills and traditions were learned and passed down through the generations and how individual fiddlers honed their distinctive playing styles. He also examines the Island's history and material culture, fiddlers' values and attitudes, the role of radio and recordings, the fiddler's repertoire, fiddling contests, and the ebb and flow of the fiddling tradition, including efforts over the last few decades to keep the music alive in the face of modernization and the passing of old-timers. Rounding out the book is a rich array of photographs, musical examples, dance diagrams, and a discography. The inaugural volume in the Charles K. Wolfe American Music Series, Couldn't Have a Wedding without the Fiddler is, in the words of series editor Ted Olson, "clearly among the more significant studies of a local North American music tradition to be published in recent years."
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.803 | 0.781 |
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".