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Record W4230423195 · doi:10.1017/s0008413100004114

The Modal Auxiliaries<i>have to</i>and<i>must</i>in the<i>Corpus of Early Ontario English</i>: Gradient Change and Colonial Lag

2006· article· en· W4230423195 on OpenAlexaffabout
Stefan Dollinger

Bibliographic record

VenueThe Canadian Journal of Linguistics / La revue canadienne de linguistique · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsModal verbDeontic logicRelation (database)LinguisticsColonialismModalHistoryAmerican EnglishCompetitor analysisVarieties of EnglishNorth American EnglishEarly Modern EnglishFunction (biology)SociologyPhilosophyVerbComputer scienceArchaeologyEconomics

Abstract

fetched live from OpenAlex

Abstract The notion ‘drift’ plays an important role in the development of the modals have to and must in early Canadian English in relation to British and American English during the late 18th and early 19th centuries. Have to is first found in texts that reflect informal usage, and for the period in question (1750–1849), have to is only attested with deontic readings; the data suggest that its rise was not exclusively conditioned by the defective paradigm of must. Must maintains its epistemic function in relation to its Late Modern English competitors. In early Canadian English, changes progress gradually, with individual variables following different directions. Canadian English epistemic must lags behind, while deontic have to has spread more quickly in North America, with Canadian English more progressive than British English varieties, but less so than American English. Within a more general drift towards have to , Canadian English shows independent development in successive periods.

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)0.005
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.249
Teacher spread0.229 · 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.

Study designNot applicable
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

Citations3
Published2006
Admission routes2
Has abstractyes

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