The sound of round: Evaluating the sound-symbolic role of consonants in the classic Takete-Maluma phenomenon.
Bibliographic record
Abstract
Köhler (1929) famously reported a bias in people's matching of nonsense words to novel object shapes, pointing to possible naïve expectations about language structure. The bias has been attributed to synesthesia-like coactivation of motor or somatosensory areas involved in vowel articulation and visual areas involved in perceiving object shape (Ramachandran & Hubbard, 2001). We report two experiments testing an alternative that emphasizes consonants and natural semantic distinctions flowing from the auditory perceptual quality of salient acoustic differences among them. Our experiments replicated previous studies using similar word and image materials but included additional conditions swapping the consonant and vowel contents of words; using novel, randomly generated words and images; and presenting words either visually or aurally. In both experiments, subjects' image-matching responses showed evidence of tracking the consonant content of words. We discuss the possibility that vowels and consonants both play a role and consider some methodological factors that might influence their relative effects. (PsycINFO Database Record (c) 2011 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".