Stance, style, and intimacy: Interlocutor-based prosodic variation in a non-binary speaker
Bibliographic record
Abstract
Recent research has demonstrated how speakers build stances from combinations of linguistic features and how styles accumulate from stances. However, most sociophonetic studies use generalized analyses of stance that focus solely on the highlighted speaker, glossing over variation based on interlocutor and context. This interlocutor-based variation is particularly relevant to LGBT people, who often adjust styles based on perceived safety and visibility. This study tests the generalizability of stance analyses by focusing on interlocutor-based variation. I examine the production of a specific stance by a single speaker in conversation with four interlocutors: in particular, a young non-binary Canadian’s use of pitch, voice quality, and timing to create intimacy with their girlfriend, brother, friend, and interviewer. The speaker recorded thirteen social interactions with their phone, then joined the researcher for an interview. From the resulting 5.5 hours of data, I highlight intonational phrases (IPs) where the speaker and the interlocutor created intimacy using cues including alignment with the interlocutor, positive descriptions of the interlocutor, confidential questions and revelations, invitations to share experiences, and feedback showing attentive listening. For each speaker-interlocutor pair, I code each participant’s first 30 IPs after the initial 10 minutes for voice quality, intonation, average pitch, and utterance length. Although the speaker draws on the same linguistic resources to create intimacy, they draw more on particular resources with different interlocutors. For example, with the interviewer, they use a lot of creaky voice and frequent feedback. With their five-year-old brother, they use higher, dynamic pitch and shorter utterances. In addition, analyzing the speech of the speaker and interlocutors together reveals patterns of pitch accommodation. This study highlights the need to ground the study of stance in social interaction, embracing interplay between conversation participations. The findings challenge generalizable coding schemes for stance, suggesting that interlocutor-based variation makes it difficult to share schemes between speakers, let alone data sets. Finally, it contributes a non-binary voice to conversations about LGBT style-shifting, and provides sociophonetic groundwork for understanding queer and trans intimacies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".