MétaCan
Menu
Back to cohort
Record W2068142647 · doi:10.1068/i0535

Early Sound Symbolism for Vowel Sounds

2013· article· en· W2068142647 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuei-Perception · 2013
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSound (geography)VowelSound symbolismSound changeLinguisticsAcousticsHistoryPhilosophyPhysics

Abstract

fetched live from OpenAlex

Children and adults consistently match some words (e.g., kiki) to jagged shapes and other words (e.g., bouba) to rounded shapes, providing evidence for non-arbitrary sound-shape mapping. In this study, we investigated the influence of vowels on sound-shape matching in toddlers, using four contrasting pairs of nonsense words differing in vowel sound (/i/ as in feet vs. /o/ as in boat) and four rounded-jagged shape pairs. Crucially, we used reduplicated syllables (e.g., kiki vs. koko) rather than confounding vowel sound with consonant context and syllable variability (e.g., kiki vs. bouba). Toddlers consistently matched words with /o/ to rounded shapes and words with /i/ to jagged shapes (p < 0.01). The results suggest that there may be naturally biased correspondences between vowel sound and shape.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.010

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 head0.043
GPT teacher head0.360
Teacher spread0.317 · 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