Some inventory-related asymetries in the patterning of tongue root harmony systems
Bibliographic record
Abstract
Earlier studies (e.g., Casali 2003, 2008) have presented evidence of significant differences in assimilatory tendencies in vowel systems that have an [ATR] contrast in high vowels (“/2IU/ systems”) and those that have an [ATR] contrast only in non-high vowels (“/1IU/ systems”). Whereas assimilatory dominance of [+ATR] vowels is highly characteristic of the former, [-ATR] dominance is more typical of the latter. This paper investigates some further differences in the characteristic patterning of the two systems. I present evidence that /2IU/ and /1IU/ systems show essentially opposite markedness relations in respect to their non-low vowels, as diagnosed by distributional restrictions and positional neutralization. In /2IU/ systems it is quite common for [-ATR] vowels [ɪ], [ʊ], [ɛ], [ɔ] to be more widely distributed than their [+ATR] counterparts [i], [u], [e], [o], suggesting that the former are unmarked. In contrast, /1IU/ systems characteristically treat [-ATR] [ɪ], [ʊ], [ɛ], [ɔ] as marked relative to their [+ATR] counterparts. Low vowels do not show the same kind of striking reversal of markedness tendencies in the two systems that non-low vowels do. I argue, nevertheless, that some system-related differences can be observed in the patterning of low vowels as well.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".