Bibliographic record
Abstract
The traditional vocal music of Nova Scotia is a collage of genres reflecting its population and distinct history. Serving as a historic nautical gateway between North America and Europe, the continuous influx of populations led to the formation of many communities ranging from the urban epicenter of Halifax to the smallest of rural communities and coastal outports. Though largely akin to the musical traditions of the Western European colonizers of the 17th-19th centuries (predominantly English, Irish, Scottish, German, and French), the combination of song variants, repertoires from other cultures and traditions, and original compositions led to the emergence of a uniquely Nova Scotian canon. Acknowledging that previous scholarship, economic, and editorial forces had a direct influence concerning what musics were explored, gathered, and promoted, this dissertation examines the published transcriptions of Nova Scotian traditional vocal repertoires spanning 1912-2005. I restrict this study to the repertoire encoded in conventional pitch labels of the Western European tradition, as that was the medium through which previous transcribers of these oral repertoires encoded this music. This repertoire is examined through quantitative inquiry, employing set-class theory and successive interval arrays. Through the creation of tonic-based successive-interval arrays for nearly two thousand melodies spanning twenty-seven publications, I present a meta-analysis of the pitch-spaces encoded by the transcribers of this repertoire and identify normative collection sizes, scalar patterns, and outliers. I also make new transcriptions, based on commercially available field recordings of attributed source materials, to enable a cursory comparison and audit of previous transcriptions in order to comment on the quality and issues surrounding differing interpretations. The pedagogical merits of using the tonic-based successive-interval array for teaching music spanning a limited number of pitches, containing chromaticism, and modal repertoire is also explored. As such, this work serves to assemble and present a detailed overview of transcribed materials in print.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".