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Record W4206557902 · doi:10.1177/17470218221078299

Is a boat bigger than a ship? Null results in the investigation of vowel sound symbolism on size judgements in real language

2022· article· en· W4206557902 on OpenAlexafffund
David M. Sidhu, Penny M. Pexman

Bibliographic record

VenueQuarterly Journal of Experimental Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Health Solutions
KeywordsVowelSound symbolismPerceptionLinguisticsAssociation (psychology)PsychologyMid vowelCongruence (geometry)JudgementComputer scienceSpeech recognitionSocial psychology

Abstract

fetched live from OpenAlex

Sound symbolism is the phenomenon by which certain kinds of phonemes are associated with perceptual and/or semantic properties. In this article, we explored size sound symbolism (i.e., the mil/mal effect) in which high-front vowels (e.g., /i/) show an association with smallness, while low-back vowels (e.g., /ɑ/) show an association with largeness. This has previously been demonstrated with nonwords, but its impact on the processing of real language is unknown. We investigated this using a size judgement task, in which participants classified words for small or large objects, containing a small- or large-associated vowel, based on their size. Words were presented auditorily in Experiment 1 and visually in Experiment 2. We did not observe an effect of vowel congruence (i.e., between object size and the size association of its vowel) in either of the experiments. This suggests that there are limits to the impact of sound symbolism on the processing of real language.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.075
GPT teacher head0.414
Teacher spread0.339 · 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 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

Citations7
Published2022
Admission routes2
Has abstractyes

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