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Record W3160366104 · doi:10.1017/s095439452100003x

<i>Be that as it may</i>: The Unremarkable Trajectory of the English Subjunctive in North American Speech

2021· article· en· W3160366104 on OpenAlexaff
Laura Kastronic, Shana Poplack

Bibliographic record

VenueLanguage Variation and Change · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of OttawaUniversity of Toronto
Fundersnot available
KeywordsAdverbialLinguisticsHistoryAmerican EnglishPerspective (graphical)PhilosophyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The English subjunctive has had a checkered history, ranging from extensive use in Old English to near extinction by Late Modern English. Since then, the mandative variant was reported to have revived, while the adverbial subjunctive continued to diminish. American English is heavily implicated in these developments; it is thought to be leading the revival of the former but lagging in the decline of the latter. Observing that most references to these changes are based on the written language, we examine the diachronic trajectory of the subjunctive in North American Englishspeech.Adopting a variationist perspective, we carried out systematic quantitative analyses of subjunctive use under hundreds of triggers. Results show that, despite the differences in their diachronic trajectories, today both types are not only extremely rare but heavily lexically constrained. We implicate violations of thePrinciple of Accountabilityin the disparities between the findings reported here and the consensus in the literature with respect to subjunctive use in North American English.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.291
Teacher spread0.258 · 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
Published2021
Admission routes1
Has abstractyes

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