Bibliographic record
Abstract
Qualitative descriptions of speech accompanying verbs of quotation (e.g. "She was like, 'I'm not going in there!'") characterize quoted speech as a mimetic performance (Buchstaller 2003, Winter 2002) with "selective depictions" of the quotees words (Clark and Gerrig 1990, 1). The current study aims to quantify the performative and mimetic nature of quoted speech by comparing acoustic measurements of 539 vowel productions obtained through narratives of personal experience (Labov and Waletzky 1967) as told between friends. First and second formant frequencies were measured at the temporal midpoint of each vowel using PRAAT5.3 (Boersma and Weenink 2012), and compared using MANOVA tests in R. The dependent variables were F0, F1, F2, and duration while condition (quoted or non-quoted) served as the independent variable. Results indicate that mainly female speakers showed phonetically shifted vowel quality features when moving from narrative style speech to quoting voices for characters in their stories.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".