Language Universals and Misidentification: A Two-way Street
Why this work is in the frame
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Bibliographic record
Abstract
Certain ill-formed phonological structures are systematically under-represented across languages and misidentified by human listeners. It is currently unclear whether this results from grammatical phonological knowledge that actively recodes ill-formed structures, or from difficulty with their phonetic encoding. To examine this question, we gauge the effect of two types of tasks on the identification of onset clusters that are unattested in an individual's language. One type calls attention to global phonological structure by eliciting a syllable count (e.g., does medifinclude one syllable or two?). A second set of tasks promotes attention to local phonetic detail by requiring the detection of specific segments (e.g., does medifinclude an e?). Results from five experiments show that, when participants attend to global phonological structure, ill-formed onsets are misidentified (e.g., mdif-->medif) relative to better-formed ones (e.g., mlif). In contrast, when people attend to local phonetic detail, they identify ill-formed onsets as well as better-formed ones, and they are highly sensitive to non-distinctive phonetic cues. These findings suggest that misidentifications reflect active recoding based on broad phonological knowledge, rather than passive failures to extract acoustic surface forms. Although the perceptual interface could shape such knowledge, the relationship between language and misidentification is a two-way street.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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