Children's own names influence their spelling
Bibliographic record
Abstract
We analyzed spellings that were produced by children in kindergarten ( N = 115), first grade ( N = 104), and second grade ( N = 77) in order to determine whether children's own names influence their spellings of other words. Kindergartners overused letters from their own first names (or commonly used nicknames) when spelling. Kindergartners with longer names, who had more own-name letters available for intrusions, tended to produce longer spellings than did children with shorter names. Moreover, the spellings of kindergartners with long names tended to contain a lower proportion of phonetically reasonable letters than did the spellings of children with short names. These effects appeared to be confined to children who read below the first grade level. The results support the view that children's own names play a special role in the acquisition of literacy. They further show that children choose letters in a way that reflects their experience with the letters.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".