Bibliographic record
Abstract
<p>The distribution of lexical stress is sensitive to the weight of rhythmic units such that heavier units more strongly attract stress. This paper addresses the question: what is the rhythmic unit relevant for weight computation? The traditional approach links weight to the <em>syllable</em>: weight is computed over the syllable rime (review in Blevins 1995), possibly with limited onset-sensitivity (Kelly 2004, Gordon 2005, Ryan 2013). I present experimental data which challenge this view, and support a recently proposed non-syllable-based alternative according to which weight is computed over the total vowel-to-vowel <em>interval</em> (Steriade 2012). Using a nonce word production paradigm, I test how likely participants are to stress the initial vs. final vowel in bi-vocalic sequences, manipulating the consonantal interlude separating the two vowels between a single C (e.g. <em>aka</em>) and CC cluster (<em>akra</em>). Initial stress is more likely with CC than C -- medial consonants contribute weight to pull stress to the initial vowel, CC contributing more weight than C. This is incompatible with syllable constituency which parses C/CC in the onset of the final syllable (<em>a.ka</em>, <em>a.kra</em>), and supportive of interval constituency which parses C/CC in the initial interval (<em>ak*a</em>, <em>akr*a</em>).</p>
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".