Language and cluster-specific effects in the timing of onset consonant sequences in seven languages
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we draw on available data from previous experiments to explore cross-linguistic variation in articulatory overlap in CC onset clusters, taking into account the role of cluster composition. Our sample includes articulography recordings of eleven clusters for seven languages. We find that cross-linguistic variability is conditional on cluster composition. Previous suggestions that languages may have individual global articulatory timing profiles for consonant clusters in terms of an overall relatively lower or higher degree of overlap are not confirmed for our sample. All included languages converge on a relatively higher degree of overlap for some of the clusters, whereas only some of the languages additionally extend into the lower overlap range, particularly for stop-sonorant sequences. Manner and voicing are further identified as factors conditioning variation in consonantal overlap. Overall languages differ in their degree of overlap in multi-faceted ways, but the relative effects of cluster composition work in the same direction across languages.
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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 | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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