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Record W4307462153 · doi:10.1017/lar.2022.91

Listening in/to Literature

2022· article· en· W4307462153 on OpenAlexaffabout
Tamara L. Mitchell

Bibliographic record

VenueLatin American Research Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American Literature Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsJazzArtHumanitiesPoeticsPoliticsLatin AmericansArt historyActive listeningMedia studiesSociologyPoetryPolitical scienceLiteratureLaw

Abstract

fetched live from OpenAlex

This essay reviews the following works: Tropical Riffs: Latin America and the Politics of Jazz. By Jason Borge. Durham, NC: Duke University Press, 2018. Pp. 266. $26.95 paperback. ISBN: 9780822369905. The Cry of the Senses: Listening to Latinx and Caribbean Poetics. By Ren Ellis Neyra. Durham, NC: Duke University Press, 2020. Pp. xvii + 222. $25.95 paperback. ISBN: 9781478011170. Hearing Voices: Aurality and New Spanish Sound Culture in Sor Juana Inés de la Cruz. By Sarah Finley. Lincoln: University of Nebraska Press, 2019. Pp. 252. $60.00 hardcover. ISBN: 9781496211798. Writing by Ear: Clarice Lispector and the Aural Novel. By Marília Librandi. Toronto: University of Toronto Press, 2018. Pp. xxi + 214. $88.00 hardcover. ISBN: 9781487502140. The Senses of Democracy: Perception, Politics, and Culture in Latin America. By Francine R. Masiello. Austin: University of Texas Press, 2018. Pp. 326. $25.95 paperback. ISBN: 9781477315040. Sonar: Navegación/localización del sonido en las prácticas artísticas del siglo XX. By Luz María Sánchez Cardona. Mexico City: Universidad Autónoma Metropolitana; Juan Pablos Editor, 2018. Pp. 171. $34.99 paperback. ISBN: 9786072815469.

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)0.005
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.107
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.034
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.005
Science and technology studies0.0130.014
Scholarly communication0.0260.024
Open science0.0020.017
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.1070.041

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 head0.087
GPT teacher head0.470
Teacher spread0.383 · 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 designQualitative
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

Citations4
Published2022
Admission routes2
Has abstractyes

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