Phonological Processing Skills of Children Adopted Internationally
Bibliographic record
Abstract
PURPOSE: In recent years, large numbers of children have been adopted from abroad into the United States. This has prompted an interest in understanding and improving the developmental outcomes for these children. Although a growing number of studies have investigated the early language development of children who have been adopted internationally, few have focused specifically on the phonological processing development of this group of children, even though it is widely acknowledged that phonological processing skills are important in language and literacy acquisition. The purpose of this study was to examine the phonological processing skills of a group of children who had been adopted from China into the United States. METHOD: The participants were 45 children who had been adopted from China ( M age at adoption = 13.09 months). The children were assessed between the ages of 6;10 (years;months) and 9;4. Their phonological processing skills, spoken language skills, and reading comprehension skills were assessed using norm-referenced measures. RESULTS: Overall, the majority of children scored at or above the average ranges across measures of phonological awareness, phonological memory, and rapid naming. The children's reading comprehension scores were moderately to highly correlated with their phonological processing scores, but age at the time of adoption was not highly correlated with phonological processing or reading comprehension. CONCLUSION: The findings of the current study provide a basis for an optimistic view regarding the later language and literacy development of school-age children who were internationally adopted by the age of 2 years.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".