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Record W2484521639 · doi:10.1075/cilt.308.17bea

Patrons sociolinguistiques chez trois générations de locuteurs acadiens

2009· book-chapter· en· W2484521639 on OpenAlexaffabout
Louise Beaulieu, Władysław Cichocki

Bibliographic record

VenueAmsterdam studies in the theory and history of linguistic science. Series 4, Current issues in linguistic theory · 2009
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of New BrunswickUniversité de Moncton
Fundersnot available
KeywordsPluralSuffixMorphemeVariation (astronomy)VerbLinguisticsZero (linguistics)VowelPsychologyHistoryHumanitiesMathematicsPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Verbs in Acadian French mark third-person-plural subject-verb agreement with the traditional suffix - ont , that is realized by the nasal vowel /õ/ ( les enfants i-jou-ont “the children play”), as well as by the zero morpheme that is generally found in contemporary French and that is represented in writing as - ent ( les enfants i-jou-ent, les enfants jou-ent ). This study reports on variation in the use of these forms by three generations of speakers from northeastern New Brunswick (Canada) and addresses Labov’s “transmission problem”: how children learn to talk differently from their parents, and yet in the same direction, over several generations. Data from a stratified corpus of 16 adult speakers show an ongoing change: the zero morpheme is replacing the traditional - ont suffix. The main external factor that conditions this variation is social network: speakers with closed affi liation networks tend to conserve the traditional variant while those who have open networks use the zero morpheme almost exclusively. Among closed network speakers there is a significant age-by-gender interaction: older males have the highest frequencies of occurrence of the traditional -ont variant followed by younger females; younger males and older females have the lowest frequencies. The main internal conditioning factor is verb class, where classes are arranged according to the number of bases or stems. Verb classes with a small number of bases (for example, arriver “to arrive”, appeler “to call”) are more likely to be associated with conservation of the traditional suffix, while those with larger numbers of stems (including verbs such as avoir “to have”, aller “to go”, faire “to do” that have suppletive forms) are less likely. The corpus of children’s data includes recordings made with 24 speakers in three age groups (3–5, 7–9 and 10–12 years of age). The distribution of the traditional - ont suffix with respect to social network is the same as that found among adults: as early as 3 to 5 years of age, children from families with closed networks use the traditional form almost exclusively while those from open network families use it infrequently, favouring the zero morpheme. However, among all children from closed network families, the frequency of use of the traditional variant is considerably higher than among adult speakers. Furthermore, unlike the pattern observed for adult speakers, there are no significant gender differences at any age level. With respect to the “transmission problem” the results show that the verb class constraint that is formulated by children is not identical with adults’ patterns, but it does resemble more closely the model of adult women speakers than that of adult male speakers. Interestingly, the process of re-structuring the internal constraint on the traditional – ont suffix variation begins relatively late (in the 10–12 year group) when compared with ages reported for the acquisition of constraints on phonological variation. The results of this study provide evidence for a complex picture of the acquisition of sociolinguistic competence; the acquisition of social and linguistic constraints on variation does not follow a clear linear order where social patterning is acquired before (or after) linguistic constraints.

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)0.020
metaresearch head score (Gemma)0.059
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.596
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.020
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.370
Teacher spread0.315 · 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 designTheoretical or conceptual
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

Citations21
Published2009
Admission routes2
Has abstractyes

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Same venueAmsterdam studies in the theory and history of linguistic science. Series 4, Current issues in linguistic theorySame topicLinguistic Variation and MorphologyFrench-language works237,207