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Record W4403036142 · doi:10.1163/23526416-bja10059

Open-class-ness, Aspect, Iconicity, and Other Characteristics of Japanese Ideophones Viewed through the Lens of Closed-class Semantics

2024· article· en· W4403036142 on OpenAlexaff
Kiyoko Toratani

Bibliographic record

VenueCognitive Semantics · 2024
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsYork University
Fundersnot available
KeywordsIconicityClass (philosophy)Semantics (computer science)LinguisticsComputer scienceArtificial intelligenceProgramming languagePhilosophy

Abstract

fetched live from OpenAlex

Abstract This paper adopts closed-class semantics (Talmy, 2000) to examine the semantics and morphophonology of Japanese ideophones. First, it considers the class category status of ideophones, arguing that the membership expansion of ideophones as open-class forms is impeded by iconicity, or the sound-symbolism of a phoneme. Next, it explores the relevance of three grammatical concepts expressed by closed-class forms (aspect, force dynamics, and perspective) to the meaning of ideophones, arguing that: (i) the forms of ideophones are iconic representations of (un)boundedness; (ii) ideophones can elaborate on the force enacted by the antagonist or agonist; and (iii) a proximal perspective underlies commonly used descriptions, such as dramaturgicness. The discussion touches on cross-linguistically common characteristics of ideophones, including use of a closed-class means such as reduplication to create aspect-informed forms. The paper shows that the class category status is an important measure to seize characteristics of ideophones, corroborating Dingemanse (2019, 2023).

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.005
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0000.001
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 head0.041
GPT teacher head0.331
Teacher spread0.291 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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