A following sibilant increases the ambiguity of a sibilant continuum
Bibliographic record
Abstract
We examined the effect of three following contexts: /s/, /∫/, and vowel, on the categorization of a /s/-/∫/ continuum. Unlike previous findings of a shift in category boundary due to context (Mann & Repp, 1980), we found that in the context of a following sibilant, listeners found the target sibilant to be more ambiguous (shallower categorization slopes and responses closer to chance) than when followed by a vowel (p < 0.001). There was also a tendency for the /∫/ context (which affects pronunciation) to create more ambiguity than the /s/ context (which does not) (p = 0.057). On half of the trials, participants heard the following context as part of the same syntactic phrase as the target (e.g. "Whenever they fra? Shelly gets upset") and on half heard it was part of a different phrase (e.g. "Whenever they fra? Shelly, John gets upset"). Pronunciation usually is more affected when target and context are in the same phrase (Holst & Nolan, 1995). Listeners tended to perceive target sibilants as more ambiguous when the following sibilant was part of the same phrase (p = 0.01) suggesting a role for top-down knowledge in interpreting segmental information.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".