“I'll Show You How to Write My Name”: The Contribution of Naturalistic Sibling Teaching to the Home Literacy Environment
Bibliographic record
Abstract
Abstract Research on the home literacy environment has typically involved parents as teachers with little attention given to siblings’ roles in teaching each other. This study examines naturalistic language and literacy teaching by 39 sibling dyads, at two timepoints, when children were ages 2 and 4 (time 1; T1) and again at ages 4 and 6 (time 2; T2). Each family was observed for a total of six 90‐minute sessions at both timepoints. First, all sibling‐directed teaching sequences were identified, including instances of formal and informal teaching. Second, sequences were coded for evidence of language (i.e., vocabulary, book concepts, songs, phonological awareness) and literacy concepts (i.e., alphabetic principle, reading, writing, spelling). Over 40% of the T1 and T2 teaching sequences involved language and literacy concepts. Older siblings taught the majority of the time at T1 and T2; however, the number of sequences taught by younger siblings increased proportionally over time. Because siblings taught vocabulary concepts significantly most often at both T1 and T2, further analyses were conducted on vocabulary subcategories (i.e., expansion, discussing pictures, relaying word meaning, checking for listener understanding, second‐language instruction). Significantly more teaching sequences involved expansion than other vocabulary subcategories at both timepoints. Finally, at T2, literacy concepts (i.e., writing, spelling) were taught significantly more than at T1. Our findings demonstrate that siblings are interested in teaching each other a variety of language and literacy concepts during naturalistic interactions in the home, indicating that siblings contribute to the richness of the home literacy environment.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".