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Record W4293221711 · doi:10.1017/s1752196321000493

Defining the Songs of Incarceration: The Lomax Prison Project at a Critical Juncture

2022· article· en· W4293221711 on OpenAlexaff
Velia Ivanova

Bibliographic record

VenueJournal of the Society for American Music · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPrisonImprisonmentJunctureCriminologySociologyGender studiesPolitical scienceLinguistics

Abstract

fetched live from OpenAlex

Abstract This article illuminates an underexplored moment in the formation of the well-known archive of recordings of incarcerated people collected by the folklorists John and Alan Lomax. In 1934, John Lomax wrote to 350 correctional institutions across the country, asking officials to transcribe the texts of songs “current and popular among prisoners or ‘made up’ by them.” Despite contacting institutions incarcerating people of many races, ethnicities, genders, and ages, however, the Lomaxes ultimately continued to center on music performed by Black men in Southern prisons. Because of this, I position the letter as a critical juncture in the formation of the Lomaxes’ prison work. Choices made by prison officials (whether to respond to the letter and in what manner to respond) and by the Lomaxes themselves (whether to express interest in songs addressed by correspondents) were influenced by perceptions of the role of music in relation to criminality, imprisonment, reform, and race. These perceptions in turn defined the boundaries of the Lomax prison project. The correspondence considered in this article therefore offers a counternarrative to popular representations of music and incarceration and suggests the limits of the well-known Lomax prison song collection.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0030.001
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 head0.023
GPT teacher head0.251
Teacher spread0.228 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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