Cumulative risk disparities in children's neurocognitive functioning: a developmental cascade model
Bibliographic record
Abstract
The current longitudinal study examined the role of cumulative social risk on children's theory of mind (ToM) and executive functioning (EF) across early development. Further, we also tested a cascade model of development in which children's social cognition at 18 months was hypothesized to predict ToM and EF at age 4.5 through intermediary language skills at age 3. We then examined whether this developmental mechanism varied as a function of social risk status. Participants were 501 children recruited when they were newborns, at which point eight psychosocial risk factors were assessed and combined into a metric of cumulative social disadvantage. Families were followed up at 18 months, at which point four social-cognitive skills were assessed using developmentally sensitive tasks: joint attention, empathy, cooperation, and self-recognition. Language was measured at age 3 using a standardized measure of receptive vocabulary. At age 3 and 4.5, EF and ToM were measured using previously validated tasks. Results showed that there were notable cumulative risk disparities in overall neurocognitive skill development, and these effects became more differentiated over time. Support was also found for a developmental mechanism wherein the effect of social cognition at 18 months on ToM and EF in the preschool period operated specifically through children's receptive language ability at age 3. This pathway functioned similarly for children with both low- and high-risk backgrounds. These results extend previous findings by documenting the role of cumulative social disadvantage on children's neurocognition and the pathways that link key neurocognitive abilities across early 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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".