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Record W4401014158 · doi:10.3390/languages9080259

Plural Alternations and Word-Final Consonant Syllabification in Brazilian Veneto

2024· article· en· W4401014158 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

VenueLanguages · 2024
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPluralLinguisticsSyllableConsonantAlternation (linguistics)SyllabificationSuffixWord (group theory)Variety (cybernetics)MathematicsHistoryComputer scienceVowelArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

In Brazilian Veneto (a heritage variety of Veneto spoken in several areas of Brazil), a stem alternation targets the plurals of masculine nominals ending in a consonant. While nominals with a word-final rhotic or nasal are pluralized by adding the masculine plural suffix /−i/ ([bi't∫̑er]→[bi't∫̑eri] ‘glass’), pluralization in nominals with a final lateral involves deletion of the consonant (e.g., [ni'sol]→[ni'soi] ‘bedsheet’). I argue that these differences stem from word-final laterals having a distinct representation from rhotics and nasals: while the latter are represented as codas, the former are represented as onsets of empty-headed syllables. Based on a corpus analysis, I show that (a) speakers’ productions of these plurals are stable, and (b) other patterns of pluralization (namely, in monosyllables and words with final stress on a CV syllable) are consistent with the proposal. In addition, the behaviour of laterals with respect to resyllabification, metaphony and intervocalic consonant deletion further suggest that laterals are represented as onsets word-finally.

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)0.000
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 score0.869
Threshold uncertainty score0.675

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.404
Teacher spread0.367 · 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