Ordinal processing differences between children with persistent dyscalculia and typically performing children.
Bibliographic record
Abstract
Ordinal number processing skills are important for adults and children. Recent work demonstrates that children have difficulty with judging the ordinality of sequences that are in-order but do not match the typical count-list (i.e., in-order non-adjacent sequences, such as 2-4-6). Limited evidence in the literature suggests that dyscalculic children show a similar pattern of behavior. In the present study, we sought to explicitly test the hypothesis that children with developmental dyscalculia struggle primarily with extending notions of ordinality to sequences outside of the count-list. We test this hypothesis using a sample of children with persistent developmental dyscalculia, and a comparison group of typically performing children. Both groups completed an ordinality judgment task, in which triplet sequences were judged as being in-order (e.g., 3-4-5; 2-4-6) or in mixed-order (e.g., 3-5-4; 2-6-4). In line with our prediction, results demonstrate that children with persistent developmental dyscalculia make more errors, compared to typically performing children, but only on the in-order non-adjacent trials (e.g., 2-4-6). Broadly, this finding suggests that ordinality processing abilities are impaired in children with developmental dyscalculia, and that this characteristic appears primarily in extending notions of ordinality beyond adjacent sequences. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".