Bibliographic record
Abstract
Abstract The Bouba/Kiki (BK) effect is observed when a linguistic sound is associated with a shape. People usually associate the nonword bouba with a round shape, and kiki with a sharp shape ( Ramachandran & Hubbard, 2001 ). In 2011, Nielsen and Rendall found that certain English letters (/k/, /p/, and /t/) and (/b/, /l/, /m/, and /n/) were associated with sharp and round shapes respectively. The BK effect was investigated in depth for the first time in Arabic in 2022 (Nassereddine) using Arabic Analogs to the English letters. Arabic participants’ performance was not consistent with previous research ( Nielsen & Rendall, 2011 ). The goal of the present study was to determine the roundest and sharpest Arabic letters by presenting all letters both visually and auditorily to Arabic speakers and have them say whether a letter shape or sound best maps on to the standard bouba and kiki shapes. The results revealed that Arabic does have both round and sharp letters, and that there is a strong influence of phonological features on this BK effect.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.003 |
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".