Literacy Instruction, SES, and Word‐Reading Achievement in English‐Language Learners and Children with English as a First Language: A Longitudinal Study
Bibliographic record
Abstract
Socioeconomic gradients and growth‐mixture model trajectories of word‐reading achievement were examined from kindergarten to Grade 5 in all the children who entered kindergarten within a school district and started receiving literacy‐intensive instruction from that point on. In kindergarten, the relationship between socioeconomic status (SES) and word reading was significant in two of the three subgradients identified in English‐language learners (ELL), and in the only gradient identified in children with English as first language (L1). With more instruction, SES effects progressively disappeared and ELL and L1 gradients became identical. The trajectories showed that ELL and L1 children of middle‐SES level improved similarly as they progressed through Grade 5. However, at the lowest and highest end of the SES spectrum, the ELL children improved more than the L1 even though in kindergarten they were the most at risk for reading failure. The results suggest that the literacy‐intensive program may have reduced the negative influence of SES on word‐reading development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".