Bibliographic record
Abstract
Previous research demonstrated that there are no fixed motor programs or tasks in speech, and there is evidence for subphonemic planning in speech within a word across up to two phoneme boundaries [Derrick and Gick (Submitted)]. Because this evidence is word-internal, it could be suggested that speakers simply memorize many motor programs for each word and draw on them as needed. We demonstrate that speech planning extends across three phonemes, two syllables and a morpheme boundary. Participants produce more up-flaps the first flap of words such as “editor” and “auditor”, which often end with the tongue tip up, versus alveolar taps in “edify” and “audify,” which end with the tongue tip down. We also demonstrate planning across word boundaries. Participants also produce more up-flaps in “edit” and “audit” if these words are followed by “a,” which has a double flap sequence, than if the words are followed by “the,” which does not. Planning across morpheme and word boundaries would ultimately require memorization of an infinite number of motor programs or tasks.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".