A Developmental Cascade Model of Neurocognitive Functioning: Risk, Resilience, and Implications for Children's Mental Health
Bibliographic record
Abstract
Theory of Mind (ToM) and executive functioning (EF) are two neurocognitive abilities that develop rapidly over the preschool period. ToM and EF are highly interrelated, both behaviourally and neurologically, and are predictive of a host of psychosocial outcomes across the lifespan. This dissertation delineates a developmental cascade model of ToM and EF in which key social-cognitive skills in the second year of life are examined as precursors to ToM and EF through their impact on children's nascent language skills. Further, both cumulative social disadvantage and biomedical risk are investigated as risk factors that increase vulnerability to cognitive morbidity over the early years. Finally, it is suggested that these social and biomedical risks are non-deterministic, and that positive postnatal socialization experiences with caregivers may protect children against their deleterious influence. The implications for prevention and intervention will be discussed with the overarching suggestion that early programming may help to mitigate the negative cascading effects of poor early adaptation on later psychosocial health and development.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".