Bibliographic record
Abstract
The largest and most varied of the various collections of Newfoundland vernacular songs, Kenneth Peacock's three-volume Songs of the Newfoundland Outports, was fIrst published in book form in 1965.tAt a price of $15.00 for all three volumes, it was a bargain, but unfortunately it has long been out of print and available only occasionally as a very expensive second-hand item.2This long-awaited CD-ROM version of the work will therefore be greeted with a very warm welcome by aficionados of Canadian folk music who have previously found it difficult to become acquainted in detail with the treasures that Peacock noted and/or recorded in Newfoundland in 1950-52 and 1958-62.It is, to put it bluntly, a "must buy" for all lovers of Newfoundland song and for anyone interested in the spread of English and Irish folksong outside the countries of origin.The aim of this review is to do two things: to explain and evaluate how Jim Payne and Don Walsh have adapted Peacock's print publication to this digital format (and how they have gone beyond print), and to provide as many examples as we have space for of Peacock's collecting, as a taster to induce anyone who does not know the collection to explore it further.Since the CD-ROM contains over forty photographs, numerous .sound-clips,and over fIve hundred songs obtained from nearly one hundred informants, what we print here can only be a small sampling.But, as far as possible, our chosen musical examples will provide a
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".