Vowel but not consonant identity and the very informal English lexicon
Bibliographic record
Abstract
This paper studies the phonological properties of shitgibbons, a class of insulting English compounds made up of a monosyllabic obscenity followed by a trochaic innocuous noun. Our experimental data shows that in addition to these categorical prosodic requirements, there are gradient segmental requirements: native speakers judge shitgibbons as more wellformed when their two stressed vowels are identical (e.g. shit-whistle is better than fuck-whistle), but matching word-initial consonants do not improve wellformedness. A corpus study of English compounds shows that both vowel identity and initial consonant identity are overrepresented in the lexicon. Our explanation for the mismatch between the lexicon and the experiment relies on a typological asymmetry: vowels interact across intervening consonants in many languages, but consonants do not selectively interact across other intervening consonants in this way, e.g. the two matching [f]’s in fuck-frisbee cannot be compelled to match while ignoring the intervening coda [k]. The analysis is implemented as a MaxEnt grammar, with a locality bias that prevents assigning weight to the constraint that demands initial consonant matching.
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.
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 | 0.002 | 0.002 |
| 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 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".