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Record W4399546918 · doi:10.17721/2520-6397.2024.1.06

The Verb in the Linguistic and Conceptual Worldviews of English Language Speakers

2024· article· en· W4399546918 on OpenAlexaboutno aff
Iryna Dilai

Bibliographic record

VenueLinguistic and Conceptual Views of the World · 2024
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsVerbPsychologyPhilosophy

Abstract

fetched live from OpenAlex

The paper studies the peculiarities of mental representations of the verb in the conceptual worldview and their reflection in the linguistic worldview of English language native speakers. Special attention is paid to the etymology and meaning of the word “verb” in the English language. In particular, its connection with the meaning “word” in general, which is manifested in the corresponding derivatives, is clarified. A tendency to define the verb through its syntactic function in scientific literature has been revealed. The key role of the predicate-argument structure, which reflects the linguistic worldview of English language native speakers, has been established. At the same time, the conceptual structure of the verb meaning and its mental representations shed light on the place of the verb in the conceptual worldview of English language native speakers. In the naive worldview of the English speakers, a tendency to associate the verb with an action or an act can be observed. High productivity of verbification in present-day English, as well as the overall high saturation of verbs in the English language corpora, estimated at 10.86 per cent, testify to the significance of the verb in English. The corpus analysis has been conducted based on the Corpus of Contemporary American English (COCA), the British National Corpus (BNC), the Strathy Corpus of Canadian English, and iWeb Corpus of modern web communication. The total distribution of verbs across the aforementioned corpora does not reveal any substantial variation. Nonetheless, the corpus data provide illuminating insights into the worldview of the native speakers of English. The prospects of further research in this direction lie in the construction of a mental model of the English verb, which would integrate the approaches to verb semantics within different modern frameworks, employing both experimental findings and empirical corpus data.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.306
Teacher spread0.280 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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