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Record W2914477539 · doi:10.5206/notabene.v11i1.6614

Behind the Bandstand: Jay G. Sims and the Internal Workings of the Sousa Band

2018· article· en· W2914477539 on OpenAlexvenueno aff
Caitlin D. McAlister

Bibliographic record

VenueNota bene · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTheater, Performance, and Music History
Canadian institutionsnot available
Fundersnot available
KeywordsPurchasingScholarshipPosition (finance)Broad bandHistoryManagementEngineeringMedia studiesSociologyPolitical sciencePhysicsBusinessLawOperations managementOptics

Abstract

fetched live from OpenAlex

From 1919 to 1932 trombonist, Jay G. Sims, served as the personnel manager for the Sousa Band. The Harry Ransom Center at University of Texas at Austin holds Sim's business correspondences which divulge his crucial role in the band’s operations, shedding light on his contributions to the band's success as a touring group. Notwithstanding so, there is relatively little information about him in the existing scholarship on John Philip Sousa and the Sousa Band. This paper explores Sims’ position as personnel manager for the Sousa Band through an examination of his correspondences. There is particular focus on his day-to-day functions, including his input on hiring decisions and recruitment of members, as well as purchasing of equipment for the band’s performances. Furthermore, Sims’ correspondence offers a rare, behind-the-scenes glimpse of the Sousa Band, one of the most famous touring musical groups of the early-twentieth century. By using Sims’ own documents as a primary source, it is possible through letters and invoices, not only to determine the exact nature of Sims’ role within the Sousa Band, but also how his administrative position impacted the band’s operations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.178
Teacher spread0.167 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2018
Admission routes1
Has abstractyes

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