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Record W2589817104 · doi:10.5334/gjgl.229

Predicting prosodic structure by morphosyntactic category: A case study of Blackfoot

2017· article· en· W2589817104 on OpenAlexaff
Joseph W. Windsor

Bibliographic record

VenueGlossa a journal of general linguistics · 2017
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLinguisticsProsodyPhonologyNounVowelPhonotacticsPsychologyMorphemeComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

This study examines phonetic correlates to three prosodic categories in Blackfoot: the syllable (σ), the prosodic word (ω), and the phonological phrase (φ). I provide evidence that the Blackfoot σ is recognizable by an obligatory process of vowel coalescence and the φ is recognizable by an obligatory process of right edge aspiration. The ω can be distinguished from these other two prosodic constituents by an optional phonetic process which mimics intersyllabic vowel coalescence, but does not apply obligatorily.The prosodic categories investigated in this study are then correlated to three morphosyntactic categories: morphological agreement suffixes, lexical morphemes (adjectives and nouns), and demonstratives. This correlation is used to argue that morphological and syntactic processes function differently at the interface with phonology (cf. Russell 1999), ultimately raising questions with “word-internal syntax” analyses of Blackfoot suffixation which are derived through cyclic head movement (Bliss 2013; Wiltschko 2014) using the Mirror Principle (Baker 1985).This article is part of the Special Collection: Prosody and costituent structure

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.039
GPT teacher head0.373
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations32
Published2017
Admission routes1
Has abstractyes

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Same venueGlossa a journal of general linguisticsSame topicPhonetics and Phonology ResearchFrench-language works237,207