Cross-dialectal synchronic variation of a diachronic conditioned merger in Tlingit
Bibliographic record
Abstract
Abstract Crosslinguistically rare sounds may be uncommon as a result of being phonologically marked (Trubetzkoy 1939) or due to articulatory or perceptual biases (Maddieson 1998). Certain types of sound changes are often argued to have roots in articulatory and perceptual biases (Blevins 2004). But in cases where there is limited data available, such as with understudied languages, it may be difficult to find evidence for the roots of sound changes. Synchronic variation can be used to provide evidence for diachronic sound changes (Blevins 2004; Lindblom 1990; Ohala 1993), which is particularly useful when historical data is limited. In this investigation we discuss phonetic biases, including acoustic and perceptual factors, that contribute to a set of sound changes in Tlingit, a critically endangered Indigenous language of Alaska, British Columbia, and the Yukon, that resulted in a primary split-merger (Blust 2012). This investigation provides further support for including explicit discussion of synchronic variation as part of the description of understudied languages. We propose that there should be a stronger emphasis on documenting and analyzing variation within understudied languages because excluding variation potentially masks significant intralinguistic and crosslinguistic phenomena.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".