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Record W4205321551 · doi:10.1111/josl.12544

Participation in (non)salient linguistic change over the lifespan: An examination of panel speakers’ life stories

2022· article· en· W4205321551 on OpenAlexaffabout
Raymond Mougeon, Katherine Rehner, Françoise Mougeon

Bibliographic record

VenueJournal of Sociolinguistics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsLinguisticsSalientVariation (astronomy)SociologyLinguistic changeGrading (engineering)HistoryPsychology

Abstract

fetched live from OpenAlex

Abstract This paper addresses linguistic change over the lifespan by examining two cases of variation in the speech of the minority Francophone community of Welland, Ontario: (i) consequence markersso, fait que, alors, anddonc(“therefore”) and (ii) markers of restrictionjuste,seulement que, (r)ien que, and (ne…)que(“only”). Using two sociolinguistic corpora collected 40 years apart, this paper first examines the impact of social factors on both cases at the community level, revealing thatsoandjusteare rising at the expense of their competitors, and documenting differences in the speed of each rise and in the social marking of the rising variant. Second, it examines whether 12 speakers recorded in both corpora are participating in each rise, revealing important interindividual differences, including, for some, patterns of age‐grading that go against the community trends. Explanations for these patterns are linked to the 12 speakers’ sociolinguistic life stories.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.114
GPT teacher head0.379
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2022
Admission routes2
Has abstractyes

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