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Record W1902358686 · doi:10.7202/1032664ar

At the Interface between Sociolinguistic and Grammatical Development: The Expression of Futurity in L2 French

2015· article· en· W1902358686 on OpenAlexvenueno aff
Martin Howard

Bibliographic record

VenueArborescences Revue d études françaises · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsVariation (astronomy)LinguisticsExpression (computer science)Variety (cybernetics)PsychologyIrishSecond-language acquisitionFirst languageSociolinguisticsSociologyComputer scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

As an example of socio-grammatical variation in target language French, the morphological variation at work in the expression of futurity constitutes an interesting area to intricately relate the L2 learner’s sociolinguistic and grammatical development. This conceptual entity is all the more interesting since previous studies of this variable in native speaker French point to a certain discrepancy between prescriptive and sociolinguistic norms in the speaker’s choice between the inflected and periphrastic forms as well as in the use of the present to mark futurity, whereby the prescriptively hypothesized semantic restrictions on the use of each form are not seen to be upheld in real language usage. This paper is concerned with the acquisition challenge that such a threefold choice poses to the L2 learner of French, based on a quantitative cross-sectional analysis of Irish instructed and study abroad learners of French. Reflecting previous studies of other variables (see, for example, Dewaele 2004; Mougeon et al. 2010), results suggest an important effect for naturalistic exposure on the acquisition of native speaker norms surrounding the expression of futurity, as well as for the actual target language variety to which the learners are exposed.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.051
GPT teacher head0.327
Teacher spread0.275 · 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.

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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueArborescences Revue d études françaisesSame topicLinguistic Variation and MorphologyFrench-language works237,207