The source and magnitude of sound-symbolic biases in processing artificial word material and their implications for language learning and transmission
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.
Bibliographic record
Abstract
Abstract There exists a fundamental paradox in linguistic cognition. Experiments show consistent sound-symbolic biases in people's processing of artificial words, yet the biases are not manifest in the structure of real words. To address this paradox, we designed an experiment to test the magnitude and source of these biases. Participants were tasked with matching nonsense words to novel object forms. One group was implicitly taught a matching rule congruent with biases reported previously, while a second group was taught a rule incongruent with this bias. In test trials, participants in the congruent condition performed only modestly but significantly better than chance and better than participants in the incongruent condition who performed at chance. These outcomes indicate the processing bias is real but weak and reflects an inherent learning bias. We discuss implications for language learning and transmission, considering the functional value of non-arbitrariness in language structure and underlying neurocognitive mechanisms.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it