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Record W2792160692 · doi:10.1159/000481783

Rhotics and Palatalization: An Acoustic Examination of Upper and Lower Sorbian

2017· article· en· W2792160692 on OpenAlexaff
Phil Howson

Bibliographic record

VenuePhonetica · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Two of the major problems with rhotics are: (1) rhotics, unlike most other classes, are highly resistant to secondary palatalization, and (2) acoustic cues for rhotics as a class have been elusive. This study examines the acoustics of Upper and Lower Sorbian rhotics. Dynamic measures of the F1-F3 and F2-F1 were recorded and compared using SSANOVAs. The results indicate there is a striking delay in achievement of F2 for both the palatalized rhotics, while F2, F1, and F2-F1 are similar for all the rhotics tested here. The results suggest an inherent articulatory conflict between rhotics and secondary palatalization. The delay in the F2 increase indicates a delay in the palatalization gesture. This is likely due to conflicting constraints on the tongue dorsum. There was also an overlap in the F2 and F2-F1 for both the uvular and alveolar rhotics. This suggests a strong acoustic cue to rhotic classhood is found in the F2 signal. The overall formant similarities in frequency and trajectory also suggest a strong similarity in the vocal tract shapes between uvular and alveolar rhotics.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.022
GPT teacher head0.242
Teacher spread0.220 · 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 designObservational
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

Citations9
Published2017
Admission routes1
Has abstractyes

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