Bibliographic record
Abstract
Songsters are one type of street literature published in the English-speaking world since the seventeenth century. Essentially, songsters are inexpensive collections of secular song lyrics sold to a broad audience of literate consumers. British publishers probably exported songsters to North America during the eighteenth century, but, in the first half of that century, Americans began to publish a few of their own. By 1860, songsters had become much more common in the United States. Improvements in printing technology and in the transportation system, as well as changing attitudes towards public education and a continued interest in music-making by amateurs provided a supportive climate for these text-only music publications. During the antebellum period Northerners dominated American songster publishing. Apart from a few publishers in the Upper South, Southerners brought out songsters only occasionally. However, after eleven Southern states formed the Confederacy in 1861, Southern publishers in those states began to take over the niche which Northern firms had held. Despite shortages in supplies, equipment, and manpower, and in spite of transportation difficulties and an ever-growing inflation rate, publishers in the Confederacy were able to produce more songsters during the Civil War than their predecessors had in the four decades before the war. This increase in songster production came about not only because Northern publishers could not sell their goods in the Confederacy, but also because consumers, many of them Confederate soldiers, accepted the songsters, purchasing enough of them to motivate further production. Two factors, patriotism and economics, influenced the types of pieces compilers selected for their songsters. In order to determine how those factors and the relationship among compilers, publishers, and consumers affected the compilation of songsters, the contents of thirty-eight songsters were examined, as were contemporary advertisements, publication notices, sheet music, letters, diaries, and memoirs. An analysis of these documents reveals that most compilers chose songs which satisfied consumers' tastes, because compilers and publishers wanted their songsters to sell well. Compilers, publishers, and consumers have all had an impact on the contents of the songsters.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".