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Record W3181789003 · doi:10.33137/twpl.v43i1.35969

The weight of the voice: gender, privilege, and qualic apperception

2021· article· en· W3181789003 on OpenAlexvenueno aff
Archie Crowley

Bibliographic record

VenueToronto Working Papers in Linguistics · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsQualiaPrivilege (computing)PsychologyApperceptionTone (literature)Power (physics)Social psychologyIdentity (music)AestheticsLinguisticsCognitive psychologyConsciousnessComputer scienceArt

Abstract

fetched live from OpenAlex

For transmasculine individuals who undergo testosterone therapy, a lower pitch is often one of the most desired results, both for personal affirmation as well as for how a low pitch is gendered by others. This paper explores how members from a peer support group for transmasculine individuals articulate their experiences taking testosterone. During interviews participants discussed their apperception of the acoustic changes in their voices (Zimman 2012, 2018) as well as the recognition of this change by others. In this paper, I explore how their apperceptions of their voices are organized around a cluster of related qualia of the voice (Harkness 2014, 2017) such as “heaviness”, “deepness”, “resonance”, and social “weightiness”. As their voices lower in pitch over time and they are more frequently gendered as men in social spaces, they navigate shifting positionalities of privilege, and I show how their descriptions of their voices naturalize various qualia of the voice, linking “deepness” to the social “weight”, or power, of a voice.

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)0.004
metaresearch head score (Gemma)0.011
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.021
Scholarly communication0.0070.003
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.247
Teacher spread0.217 · 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
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

Citations5
Published2021
Admission routes1
Has abstractyes

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Same venueToronto Working Papers in LinguisticsSame topicMusicology and Musical AnalysisFrench-language works237,207