The Development of Numeracy: Fingers Count! - eScholarship
Bibliographic record
Abstract
The Development of Numeracy: Fingers Count! Marcie Penner-Wilger Franklin & Marshall College Lisa Fast Carleton University Jo-Anne LeFevre Carleton University Brenda L. Smith-Chant Trent University Sheri-Lynn Skwarchuk University of Winnipeg Deepthi Kamawar Carleton University Jeffrey Bisanz University of Alberta Abstract: Butterworth (1999) proposed that three component abilities support the development of numeracy: subitizing, finger gnosis, and finger agility. We assessed these abilities in children in Grade 1 (N = 144) and followed them to Grade 2 (n = 102). In Grade 1, subitizing and finger gnosis were related to children’s number system knowledge and all three component abilities were related to calculation skill. Using cluster analysis, we identified three groups of children based on skill profiles across subitizing, finger gnosis, and finger tapping. One group had strong subitizing, finger gnosis and finger agility – they also had good numeracy performance both concurrently in Grade 1 and longitudinally in Grade 2. Two other groups both performed worse than the highly-skilled group on numeracy measures in Grade 1 and Grade 2; these two less-skilled groups showed strikingly different patterns of performance on number comparison, a task designed to assess the representation of number.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".