The arch not the stones: Universal feature theory without universal features
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is a growing consensus that phonological features are not innate, but rather emerge in the course of acquisition. If features are emergent, we need to explain why they are required at all, and what principles account for the way they function in the phonology. I propose that the learners’ task is to arrive at a set of features that account for the contrasts and the phonological activity in their language. For the content of the features, learners use the available materials relevant to the modality (spoken or signed). Formally, contrasts are governed by an ordered feature hierarchy. The concept of a contrastive hierarchy is an innate part of Universal Grammar, and is the glue that binds phonological representations and makes them appear similar across languages. Examples from the Classical Manchu vowel system show the connection between contrast and phonological activity. I then consider the implications of this approach for the acquisition of phonological representations. The relationship between formal contrastive hierarchies and phonetic substance is illustrated with examples drawn from tone systems in Chinese dialects. Finally, I propose that the contrastive hierarchy has a recursive digital character, like other aspects of the narrow faculty of language.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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