Bibliographic record
Abstract
Kalasha, a Northwestern Indo-Aryan language spoken in a remote mountainous region of Pakistan, is relatively unusual among languages of the region as it has lateral approximants contrasting in secondary articulation-velarization and palatalization (/ɫ/ vs /lʲ/). Given the paucity of previous phonetic work on the language and some discrepancies between descriptive accounts, the nature of the Kalasha lateral contrast remains poorly understood. This paper presents an analysis of fieldwork recordings with laterals produced by 14 Kalasha speakers in a variety of lexical items and phonetic contexts. Acoustic analysis of formants measured during the lateral closure revealed that the contrast was most clearly distinguished by F2 (as well as by F2-F1 difference), which was considerably higher for /lʲ/ than for /ɫ/. This confirms that the two laterals are primarily distinguished by secondary articulation and not by retroflexion, which is otherwise robustly represented in the language inventory. The laterals showed no positional differences but did show considerable fronting (higher F2) next to front vowels. Some inter-speaker variation was observed in the realization of /ɫ/, which was produced with little or no velarization by older speakers. This is indicative of a change in progress, resulting in an overall enhancement of an otherwise auditorily vulnerable contrast.
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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 | 0.000 |
| 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) | 0.004 | 0.001 |
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".