Home literacy environment mediates the relationship between socioeconomic status and white matter structure in infants
Bibliographic record
Abstract
Abstract The home literacy environment (HLE) in infancy has been associated with subsequent pre-literacy skill development and HLE at pre-school age has been shown to correlate with white matter organization in tracts that subserve prereading and reading skills. Furthermore, childhood socioeconomic status (SES) has been linked with both HLE and white matter organization. It is also important to understand whether the relationships between environmental factors such as HLE and SES and white matter organization can be detected as early as infancy, as this period is characterized by rapid brain development that may make white matter pathways particularly susceptible to these early experiences. Here, we hypothesized (1) an association between HLE and white matter organization in pre-reading and reading-related tracts in infants, and (2) that this association mediates a link between SES and white matter organization. To test these hypotheses, infants (mean age: 9.2 ± 2.5 months, N = 18) underwent diffusion-weighted imaging MRI during natural sleep. Fractional anisotropy (FA) was estimated from the left superior longitudinal fasciculus (SLF) and left arcuate fasciculus using the automated fiber-tract quantification method. HLE was measured with the Reading subscale of the StimQ and SES was measured with years of maternal education. Self-reported maternal reading ability was also quantified and applied to all statistical models to control for confounding genetic effects. The Reading subscale of the StimQ positively related to FA in left SLF and mediated the association between maternal education and FA in the left SLF. Taken together, these findings underscore the importance of considering HLE from the start of life and may inform novel prevention and intervention strategies targeted at low-SES families to support developing infants during a period of heightened brain plasticity.
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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 | 0.000 | 0.002 |
| 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) | 0.003 | 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".