Bibliographic record
Abstract
Gitksan is a Tsimshianic language spoken by the peoples living along the upriver areas of the Skeena river, British Columbia (Rigsby, 1986; Tarpent, 1987). Two dialects are identified: ‘East’ and ‘West’ (Rigsby, 1986). There are socio-culturally distinct and linguistically variable groups within these categories, including similarity with Nisgha (Tarpent, 1987), creating a dialect continuum. This paper provides an overview of the environments in which uvular lowering of vowels occurs across dialects. Uvular lowering has been previously attested in Gitksan (Brown, 2010; Yamane-Tanaka, 2006) as well as cross-linguistically within neighboring language families (Bessell, 1992; Walker & Rose, 2015). This paper incorporates existing research on uvular lowering and vowel inventory structures in Gitksan into a phonological account of the alternation of the short vowels [a] and [?] (Rigsby, 1986). This paper analyses two word lists, demonstrating patterns of vowel lowering adjacent to uvulars and the dialectal alternation of short [a, ?]. Measurements of F1, F2, and their slope over long vowels are presented as evidence of uvular lowering, contrasted between varying speakers. This paper uses a phonological rule-based account of the distribution of [a, ?], supported by analysis of vowel qualities. The paper concludes by presenting preliminary conclusions relating to an overall vowel shift within dialects of Gitksan, drawing parallels to English dialectology (Prichard, 2015; Riebold, 2015). I suggest that both variations in uvular lowering between speakers and phonological alternations of [a, ?] are evidence of a systemic shift in vowel quality between dialects, which creates predictable alternations when analysed as such. Future directions for this research include exploration into the reality of the underlying phoneme of both [a, ?], as well as further analysis of the overall vowel shift.
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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 | 0.001 |
| 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) | 0.002 | 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".