Fast Mapping of Words and Story Recall by Individuals With Down Syndrome
Bibliographic record
Abstract
This study compared adolescents with Down syndrome to nonverbal mental-age matched controls in their ability to fast map new noun vocabulary in spoken story contexts. Context for novel words varied within subjects in the distance between mentions (close-distant) and the ease of inferring a real word for the referent (specificity). The 23 participants with Down syndrome (DS) were aged 12.8-20.3 years. The 24 typically developing (TD) children, matched on visual nonverbal mental age (MA), were 4.1 to 6.1 years old. Participants listened to 4 tape-recorded stories, each containing 3 mentions of 2 novel words in close or distant proximity and with clear or uncertain reference, and recalled each story after presentation. Fast-mapping production was measured by the occurrence of the novel word in story recall. Fast-mapping comprehension was measured by asking children to define the novel words. The DS group did not differ from the TD group in novel word production but seemed to have more difficulty with novel word definition. For both groups, novel word production was higher in the nonspecific than the specific referent condition, suggesting that availability of a real word label interfered with fast mapping. Recall of story propositions was poorer for the DS group. For both groups, story recall was better for text units not directly associated with novel words than for text units containing novel words, suggesting a trade-off effect in processing. Regression analyses indicated that syntax comprehension, rather than mean length of utterance, predicted novel word production in both groups; MA additionally contributed to predict DS story recall.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".