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Record W165134944

Chapter 9. Be careful what you throw out: Gemination and tonal feet in Weledeh Dogrib

2010· book-chapter· en· W165134944 on OpenAlexaboutno aff
Alessandro Jaker

Bibliographic record

VenueScholarSpace (University of Hawaii at Manoa) · 2010
Typebook-chapter
Languageen
FieldArts and Humanities
TopicLinguistic Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsSpeech recognitionLinguisticsComputer sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

The Weledeh dialect of Dogrib (Tłįchǫ Yatiì) is spoken by people of the Yellowknives Dene First Nation, in and around Yellowknife, Northwest Territories. Within the formal framework of Lexical Phonology (Kiparsky 1982), this paper argues for an over-arching generalization in the phonology of Weledeh Dogrib: the constraint NoContour-Ft, which prefers (High-High) and (Low-Low) feet, but militates against (High-Low) and (Low-High) feet. NoContour-Ft is satisfied differently in different morphophonological domains: vowel deletion at the Stem Level, gemination at the Word Level, and High to Mid tone lowering at the Postlexical Level. This analysis requires that consonant length be treated as phonological in Dogrib—that is, consonant length contributes to syllable weight and mora count—even though there are no minimal pairs based on consonant length. Similarly, the distinction between High and Middle tone does not distinguish any lexical items, but is nevertheless important for the prosody of the language. Thus the paper makes a methodological point about the importance of allophonic alternations for phonological theory. Our view of what counts as contrastive or allophonic, however, is to a large extent theory-dependent; therefore, the paper also emphasizes the importance of phonetic measurements when doing fieldwork.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0160.000

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.

Opus teacher head0.044
GPT teacher head0.234
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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