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Record W2090078394 · doi:10.1159/000351059

Harsh Voice Quality and Its Association with Blackness in Popular American Media

2013· article· en· W2090078394 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhonetica · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPsychologyAssociation (psychology)Quality (philosophy)Stereotype (UML)Identity (music)Social psychologyArtAesthetics

Abstract

fetched live from OpenAlex

Performers use various laryngeal settings to create voices for characters and personas they portray. Although some research demonstrates the sociophonetic associations of laryngeal voice quality, few studies have documented or examined the role of harsh voice quality, particularly with vibration of the epilaryngeal structures (growling). This article qualitatively examines phonetic properties of vocal performances in a corpus of popular American media and evaluates the association of voice qualities in these performances with representations of social identity and stereotype. In several cases, contrasting laryngeal states create sociophonetic contrast, and harsh voice quality is paired with the portrayal of racial stereotypes of black people. These cases indicate exaggerated emotional states and are associated with yelling/shouting modes of expression. Overall, however, the functioning of harsh voice quality as it occurs in the data is broader and may involve aggressive posturing, comedic inversion of aggressiveness, vocal pathology, and vocal homage.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.324
Teacher spread0.295 · 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