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Record W2574449319 · doi:10.1177/1536600616684580

Singing by Number in Mid-Nineteenth-Century America

2017· article· en· W2574449319 on OpenAlexaff
Linda Hansen

Bibliographic record

VenueJournal of Historical Research in Music Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Methods and Practices
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSingingFacilitatorContext (archaeology)SpiritualismMusic educationMusicalHistoryMusic historyHistory of musicVisual artsSociologyPsychologyAestheticsLiteraturePedagogyArtSocial psychology

Abstract

fetched live from OpenAlex

Recognizing the broad potential of singing as a facilitator of moral instruction, academic learning, and societal participation, New Hampshire native Asa Fitz (1810–1878) was committed to advancing music and music education. A prolific publisher, editor, and author, he was involved in the production of dozens of works filled with songs and music, designed to further everything from reform movements to congregational singing, spiritualism to family life. As a singing master and music teacher, he instructed both children and other teachers, promoting his song books, his instructional techniques, his personal principles, and his overriding belief that everyone could, and should, learn to sing. Yet, for all that he was well known during his lifetime, little scholarly attention has been paid to the man, his philosophical underpinnings, or his disparate publications. This article focuses on the development of his “new system of figured music,” culminating with the publication of School Songs for the Million! in 1850. It briefly reviews the concept and expressions of alternate systems of musical notation in early to mid-nineteenth-century America and then places Fitz within that context, as he created, developed, and promoted his system to children and teachers. Though School Songs for the Million! was not as commercially successful as some of his other titles, it serves to demonstrate Fitz’s willingness to experiment with unconventional and controversial ideas in an effort to advance participation in music.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.241
GPT teacher head0.561
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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