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Record W7126339161

Love in a life: the art songs of Gena Branscombe

2022· other· en· W7126339161 on OpenAlexaboutno aff
Regan Heather Russell

Bibliographic record

VenueOpenBU (Boston University) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsChoirMusicalDramaThe artsPopular musicMusicIncidental musicPerforming arts
DOInot available

Abstract

fetched live from OpenAlex

Gena Branscombe (1881–1977) was a Canadian American pianist, composer, conductor, educator, and advocate for music by women and American composers. In her day, she was well-known as a conductor of her own works and regularly performed the music of her contemporaries with her all-women’s chorus, the Branscombe Choral. Although she published hundreds of pieces for piano, voice, violin, orchestra, and mixed voices—among them the 1929 choral drama Pilgrims of Destiny—Branscombe’s music was largely forgotten in the mid- to late-twentieth century amidst a cultural moment in the arts that was dominated by men, those of European descent or training, and post-tonal compositional trends. This research project aims to revive Branscombe’s life, legacy, and music by examining her songs for voice and piano, both tracing their compositional development and suggesting song sets appropriate for recital performance. The paper analyzes dozens of original manuscripts, describes connections between texts and their musical settings, and explores Branscombe’s artistic purpose through her own words, from speeches given at various club meetings to letters written to her publishers. In these materials is revealed an incredible woman who was wrongfully lost to American classical music, a woman who deserves to be reintroduced to the music classroom and to the performance stage.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.006
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.196
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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