Young Children Show Little Sensitivity to the Iconicity in Number Gestures
Bibliographic record
Abstract
These studies tested two questions about the developmental origins of children’s sensitivity to iconicity with regard to number gestures: (1) whether children initially learn number gestures with sensitivity to the one-to-one correspondence between fingers and quantities or whether they learn them as unanalyzed symbols; and (2) whether sensitivity to iconicity increases with general cognitive development (as indexed by age) or with experience using fingers for counting. We carried out three experimental studies testing if children generalized the one-to-one correspondence in conventional number gestures to unconventional gestures. In Study 1, children between two and five years of age showed little sensitivity to iconicity, tending to be more accurate with conventional than unconventional gestures. In Study 2, we randomly assigned children to count on their fingers or to count only with words. Children with finger-counting experience did not improve in interpreting unconventional number gestures. In Study 3, we compared age-matched samples of children in school (in France) and children in daycare (in Canada). We found that schooling had little impact on children’s interpretation of unconventional gestures. These results suggest that young children initially learn number gestures as unanalyzed Gestalts and only later develop sensitivity to the iconicity available in number gestures.
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.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".