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Record W2286578171 · doi:10.1017/s0954394515000216

Language contact and contextual nasalization in Louisiana French

2016· article· en· W2286578171 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguage Variation and Change · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNasalizationNasal vowelLinguisticsVowelNasalityVariety (cybernetics)Variation (astronomy)SyllableLanguage contactHistoryPsychologyComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

ABSTRACT This paper examines variation in Louisiana French nasalized vowels across two time periods: 1977 and 2010–2011. Non-contrastive nasal vowels are typical of English, while contrastive nasal vowels are typical of French. Louisiana French is an endangered language variety. Instead of simplifying to a single type of vowel nasality, as might be expected in a situation of heavy language contact and language shift, Louisiana French maintains a system of phonetic and phonemic nasal vowels. Digitized interviews with 32 native speakers from lower Lafourche Parish provide 2801 data points for analysis. In contrast with previous assertions in the literature, quantitative analyses reveal that contextual nasalization operates almost exclusively within the domain of the word, not the syllable.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.961
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.302
Teacher spread0.277 · 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