Bibliographic record
Abstract
New folk music and folk-song materials in this comprehensive study are particularly important for singers, folk music enthusiasts, ethnomusicologists, comparative and cultural studies scholars, and those interested in Canadian culture. LaRena Clark was a great singer and knew many fine songs. Her wide repertoire covers almost the complete range of types and topics of traditional Anglo-Canadian songs. Comparison with other collections in Canada, the United States, the British Isles, and Australia indicate just how unique and far-reaching it was. Clark's background and her varied ancestry shaped her repertoire. The account of her parents' activities gives a vivid picture of folk life in rural Ontario during the early years of this century. She knew some Canadian songs previously unreported, and she wrote songs with a strong Canadian flavour. Musically, Clark's songs are a microcosm of practices characteristic of British folk music throughout the English-speaking world. Particularly noteworthy is her constant reworking of traditional materials, procedures, forms, and individual tunes.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.439 | 0.452 |
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".