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Record W2898267256 · doi:10.1177/0075424218805524

Constructions Waxing and Waning: A Brief History of the Zero-Secondary Predicate Construction

2018· article· en· W2898267256 on OpenAlexaboutno aff
Frauke D’hoedt, Hendrik De Smet, Hubert Cuyckens

Bibliographic record

VenueJournal of English Linguistics · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSyntax, Semantics, Linguistic Variation
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsPredicative expressionVerbNoun phrasePredicate (mathematical logic)HistorySchematicNounNominalizationPresent perfectVerb phraseComputer scienceLiteraturePhilosophyArtEngineering

Abstract

fetched live from OpenAlex

In the English Secondary Predicate Construction (SPC), a predicative relation between a noun phrase (NP) and a “secondary predicate” (XP) is established by a main verb ( He finds Verb her NP attractive XP ). While the syntactic nature of this construction has received ample attention from a synchronic perspective, this study aims to shed light on the diachronic developments of the SPC. First, using data from the York-Toronto-Helsinki Corpus of Old English Prose (YCOE) and the Penn corpora, a classification is proposed of the verbs occurring in the SPC. Based on this semantic classification, the development of the SPC is then traced from Old English to Late Modern English in terms of frequency and productivity. It is argued that, while the various classes of SPC-taking verbs often show opposite developments, these lower-level incongruities are resolved at a higher schematic level, as the SPC as a whole underwent a process of internalization. These findings underscore the importance of lower-level developments in the diachronic behavior of schematic constructions and consequently contribute to the literature on constructional change.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.011
Scholarly communication0.0040.007
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.214
Teacher spread0.195 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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Same venueJournal of English LinguisticsSame topicSyntax, Semantics, Linguistic VariationFrench-language works237,207