Children remember words from ignorant speakers but do not attach meaning: evidence from event‐related potentials
Bibliographic record
Abstract
Although we know much about the conditions under which children demonstrate selective social learning, we have a limited understanding of the cognitive mechanisms by which children's selectivity manifests. Here, we report findings from a brain electrophysiological (ERP) study designed to determine the extent to which words presented by ignorant speakers were later both familiar to children and associated with semantic meaning. Forty-eight children (mean age = 6.5 years) first experienced novel word training from either a knowledgeable or an ignorant speaker. Children's ERPs were subsequently recorded as they heard a recording of the speaker using the novel word, followed by a picture of either the object the word was paired with during training (congruent) or a distractor object that was also present during training (incongruent). Children trained by a knowledgeable speaker showed both N200 and N400 effects to the incongruent word-referent pairings, thereby suggesting that the novel words were both familiar and bore a semantic association. In contrast, children trained by an ignorant speaker demonstrated only the N200 effect, thereby suggesting that the word-referent links were familiar, but not associated with semantic meaning. These findings provide evidence that selective word learning involves the disruption of processes specifically associated with semantic consolidation of word learning events.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".