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Record W2943800990 · doi:10.1017/s095439451900005x

Peaks and arrowheads of vernacular reorganization

2019· article· en· W2943800990 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLanguage Variation and Change · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVernacularHistoryScope (computer science)Language changeLinguisticsSociologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

Abstract A key component of Labov's (2001:411) socially motivated projection model of language change is the hypothesis that adolescents and preadolescents undergo a process of vernacular reorganization, which leads to a “seamless” progression of changes in progress. Between the ages of approximately five and 17, children and adolescents increase the “frequency, extent, scope, or specificity” of changes in progress along the community trajectory (Labov, 2007:346). Evidence of advancement via vernacular reorganization during this life stage has come from peaks in the apparent-time trajectory of a change around the age of 17 (e.g., Labov, 2001; Tagliamonte & D'Arcy, 2009). However, such peaks do not rule out the alternative explanations of retrograde change or age-grading. This paper presents both apparent time and real-time evidence for vernacular reorganization. We observe the arrowhead formation—a counterpart of the adolescent peak—for quotative be like in a trend study of adolescents and young adults in Toronto, Canada. Our results rule out the alternative explanations for previously observed adolescent peaks.

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 score0.944
Threshold uncertainty score0.640

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 head0.015
GPT teacher head0.278
Teacher spread0.262 · 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