Variability in American English s-retraction suggests a solution to the actuation problem
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.
Bibliographic record
Abstract
Abstract Although formulated by Weinreich, Labov, and Herzog in 1968, the actuation problem has remained an unsolved problem in understanding sound change: if sound change is conceived as the accumulation of coarticulation, and coarticulation is widespread, how can some speech communities resist phonetic pressure to change? We present data from American English s-retraction that suggest a partial solution. S-retraction is the phenomenon in which /s/ is realized as an [ʃ]-like sound, especially when it occurs in an /stɹ/ cluster (‘ street ’ pronounced more like [ʃtɹit] than like [stɹit]). The speech of English speakers judged not to exhibit s-retraction shows a large coarticulatory bias in the direction of retraction. Further, there is also substantial interspeaker variation in the extent of this bias. We propose that this interspeaker variation, coupled with the coarticulatory bias, facilitates the initiation of sound change. In this account, sound change begins when a listener accidentally interprets an extreme case of a phonetic effect as an articulatory target and then adjusts her own speech in response. This adoption of a new target requires phonetic variation that predates the change. Thus, sound change is predicted to be biased toward phonetic effects that exhibit interspeaker variability, and if sound change requires an accident that is rare, then sound change itself is correctly predicted to be rare as well.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it