Bibliographic record
Abstract
This dissertation investigates the place of articulation of allegedly ‘placeless’ consonants of Japanese - the moraic nasal /N/ and the glottal fricative /h/. In the discipline of phonology, these two consonants have typically been analyzed as having no place features of their own, on the grounds that their place features are predictable from the adjacent segments, that they often appear as outputs of debuccalization, and that they show high articulatory variability. While some researchers believe that certain segments are placeless both phonologically and phonetically, it has not been examined how these Japanese consonants appear in the surface phonetics. The current research instrumentally tests the hypothesis that they have articulatory targets, based on qualitative and quantitative examination of data produced by native speakers of Japanese. Such a study is important in order to fill the scientific gap between the phonological theories and phonetic approaches to the study of sounds. Ultrasound experiments were conducted on six native speakers of Tokyo Japanese, and the tongue movement was analyzed. The tracing of the overall tongue configurations on the ultrasound imaging was done by EdgeTrak (Stone 2005). The data for placeless segments were compared to those for the adjacent vowels, in terms of tongue shape, constriction degree and constriction location. The results involve three significant points: First, /N/ shows a significant dorsum raising for all speakers, while /h/ shows a pharyngeal constriction for 5 out of 6 speakers. Second, the constriction location is different across speakers: The location of /N/ ranges from post-alveolar to uvular, and the location of /h/ is either uvular or pharyngeal. Third, /N/ and /h/ had no more variability than /k/, which is widely assumed to be a velar-specified segment. This research empirically confirms that these two segments are articulatorily stable within a speaker but variable across speakers. This contradicts long-standing views about the segments in question. The individual variability may also lend support for the phonologization of different phonetic interpretations. Finally, the place-features of these same segments could be different across languages, and further instrumental studies of these sounds are encouraged.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".