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Record W3011686062 · doi:10.1075/scl.96.10bri

The development and pragmatic function of a non-inference marker

2020· book-chapter· en· W3011686062 on OpenAlexaff
Laurel J. Brinton

Bibliographic record

VenueStudies in corpus linguistics · 2020
Typebook-chapter
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGrammaticalizationInferenceLinguisticsDivergence (linguistics)Function (biology)Reading (process)Context (archaeology)DramaHistoryLiteraturePhilosophyArtEpistemology

Abstract

fetched live from OpenAlex

Abstract That is not to say (that) is an introductory clause refuting an inference that could be drawn from the previous discourse; it often occurs in a negative context (with a positive reading) and is characteristic of written genres, with lowest frequency in fiction. The earliest examples date from the 16th century but the next examples found date from the mid- to late-19th century. The gap in the corpus data may be explained by the predominantly fiction/drama make-up of available corpora. The development of that is not to say (that) is not an entirely prototypical case of grammaticalization as certain parameters (loss of that , contracted forms) are inconclusive and there are no ‘lexical’ uses of the form and hence no ‘divergence’.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0040.008
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0120.003

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 head0.051
GPT teacher head0.330
Teacher spread0.278 · 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 designQualitative
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
Published2020
Admission routes1
Has abstractyes

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