Cyclic movement primitives underlying two-handed alternating signs in signed language
Bibliographic record
Abstract
Biomechanical constraints have been described as underlying patterns in speech production: e.g., cyclic neural central pattern generators (CPGs) in the jaw that evolved for chewing have been claimed to affect syllabic patterns [MacNeilage 1998, Behav. Brain Sci. 21: 4] and cyclic patterns in tongue tip movement may span sequences of segments [Derrick & al. 2015, JASA-EL 137:3]. Similarly, we propose that otherwise unexplained universal aspects of sign languages may result from a preference for repeated alternating arm movements developed in human ancestors for quadrupedal locomotion. For example, in ASL-LEX corpus of 1000 ASL signs, 159 are balanced (not including signs without movement or articulated in the transverse plane, which has alternative properties we will address in the talk). Of those, 60% are alternating, and the alternating group had fewer iconic signs (30.5% vs 41%) and more repeated signs (61% vs 30%) than symmetrical signs. While both groups had a large proportion of signs realized on coronal plane, which makes them more visible in face-to-face communication (33% for alternating vs 52% for symmetrical), the former have more signs in midsagittal and coronal/transverse planes (63% vs 44%), as predicted. Supporting data from additional sign languages will be presented.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".