Cicchetti’s organizational-developmental perspective of Down syndrome: Contributions to the emergence of developmental psychopathology and the study of persons with neurodevelopmental conditions
Bibliographic record
Abstract
Dante Cicchetti's earliest work, his studies of social-emotional development in infants and children with Down syndrome, set the stage for the emergence of the larger field of developmental psychopathology. By applying basic developmental principles, methodologies, and questions to the study of persons with Down syndrome, Dante took on the challenge of searching for patterns in atypical development. In doing so, he extended traditional developmental theory and introduced a more "liberal" approach that both continues to guide developmentally based research with persons with neurodevelopmental conditions (NDCs), including Down syndrome. We highlight five themes from Dante's work: (1) appreciating the importance of developmental level; (2) prioritizing the organization of development; (3) examining whether developmental factors work similarly in those with known genetic conditions; (4) rethinking narratives about ways of being; and (5) examining the influence of multiple levels of the environment on the individual's functioning. We highlight ways that these essential lessons anticipated present-day research with persons with a variety of NDCs, including Down syndrome, other genetic syndromes associated with intellectual disability, and autism. We conclude with visions to the future for research with these populations as well as for the field of developmental psychopathology more generally.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.037 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| 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".