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Record W4379053974 · doi:10.3765/amp.v10i0.5447

The Productive Status of Laurentian French Liaison: Variation across Words and Grammar

2023· article· en· W4379053974 on OpenAlexaffabout
Anne‐Michelle Tessier, Karen Jesney, Kaili Vesik, Roger S. Lo, Marie-Ève Bouchard

Bibliographic record

VenueProceedings of the Annual Meetings on Phonology · 2023
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsCarleton UniversityUniversity of British Columbia
Fundersnot available
KeywordsCryptographic nonceLinguisticsVariation (astronomy)Context (archaeology)MorphemeNounGrammarLexiconPopulationPhonologyPsychologyComputer scienceHistorySociologyPhilosophy

Abstract

fetched live from OpenAlex

There are competing views in contemporary phonological theory about how to best represent processes that are pervasive, frequent, and phonologically motivated, yet still lexically sensitive. To what extent can – or should – a process that applies idiosyncratically to different morphemes, words, and even phrases, be represented in a way that allows it to generalize to novel forms? We examine this question by looking at prenominal liaison as it is used in contemporary Laurentian French, spoken in Canada. We present the results of an online production study that compares application of liaison in real vs. nonce nouns, and that considers the effect of nonce nouns’ phonological properties and morphosyntactic context on the process. We interpret our results as evidence that liaison behaviour is driven jointly by lexical representations and an abstract grammar, with properties of the real-word lexicon affecting liaison rates in nonce words. We further show that there is considerable variation in the population in the extent to which speakers produce liaison with real h-aspiré words, but that all speakers nonetheless share an understanding of what types of words are more vs. less likely to undergo liaison.

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)0.001
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 score0.763
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.019
GPT teacher head0.321
Teacher spread0.302 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Annual Meetings on PhonologySame topicPhonetics and Phonology ResearchFrench-language works237,207