Sign and Speech Share Partially Overlapping Conceptual Representations
Bibliographic record
Abstract
Conceptual knowledge is fundamental to human cognition. Yet, the extent to which it is influenced by language is unclear. Studies of semantic processing show that similar neural patterns are evoked by the same concepts presented in different modalities (e.g., spoken words and pictures or text) [1-3]. This suggests that conceptual representations are "modality independent." However, an alternative possibility is that the similarity reflects retrieval of common spoken language representations. Indeed, in hearing spoken language users, text and spoken language are co-dependent [4, 5], and pictures are encoded via visual and verbal routes [6]. A parallel approach investigating semantic cognition shows that bilinguals activate similar patterns for the same words in their different languages [7, 8]. This suggests that conceptual representations are "language independent." However, this has only been tested in spoken language bilinguals. If different languages evoke different conceptual representations, this should be most apparent comparing languages that differ greatly in structure. Hearing people with signing deaf parents are bilingual in sign and speech: languages conveyed in different modalities. Here, we test the influence of modality and bilingualism on conceptual representation by comparing semantic representations elicited by spoken British English and British Sign Language in hearing early, sign-speech bilinguals. We show that representations of semantic categories are shared for sign and speech, but not for individual spoken words and signs. This provides evidence for partially shared representations for sign and speech and shows that language acts as a subtle filter through which we understand and interact with the world.
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How this classification was reachedexpand
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) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".