Spatial and Temporal Properties of Gestures in North American English /r/
Bibliographic record
Abstract
Systematic syllable-based variation has been observed in the relative spatial and temporal properties of supralaryngeal gestures in a number of complex segments. Generally, more anterior gestures tend to appear at syllable peripheries while less anterior gestures occur closer to syllable peaks. Because previous studies compared only two gestures, it is not clear how to characterize the gestures, nor whether timing offsets are categorical or gradient. North American English /r/ is an unusually complex segment, having three supralaryngeal constrictions, but technological limitations have hindered simultaneous study of all three. A novel combination of M-mode ultrasound and optical tracking was used to measure gestural relations in productions of /r/ by nine speakers of Canadian English. Results show a front-to-back timing pattern in syllable-initial position: Lip then tongue blade (TB), then tongue root (TR). In syllable-final position TR and Lip are followed by TB. There was also a reduction in magnitude affecting Lip and TB gestures in syllable-final position and TR in syllable-initial position. These findings are not wholly consistent with any theory advanced thus far to explain syllable-based allophonic variation. It is proposed that the relative magnitude of gestures is a better predictor of timing than relative anteriority or an assigned phonological classification.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".