Bibliographic record
Abstract
A weak theory is not very attractive, a double-weak one even less so. The double-weak theory of speech perception serves mainly as a cover story for postponing rumination on the deeper principles that ultimately underlie human speech communication. Instead, it adopts minimal assumptions about the relation among symbols, sounds, and gestures that provides a rationale for immediately pursuing some hunches about empirical generalizations, or primitive “laws.” It is hoped that some of these may be akin to Kepler's laws of planetary motion or eighteenth century “gas laws” that may serve as grist for later, more deeply explanatory theories. The active search for such empirical laws in speech perception starts from existing hypotheses about the general structure of surface phonological representations (e.g., features, phonemes, syllables) and proceeds by constructing detailed statistical models that accord with the fine structure of human responses in parametrically controlled speech perception experiments. Some examples and possible extensions of existing models are presented.
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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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".