Less imitation of arbitrary actions is a specific developmental precursor to callous–unemotional traits in early childhood
Bibliographic record
Abstract
OBJECTIVE: Callous-unemotional (CU) traits in early childhood explain heterogeneity within conduct problems and are associated with higher risk for later diagnoses of childhood disruptive behavior disorders and antisocial behavior in adulthood. Emerging research implicates impairments in affiliative processes in the etiology of CU traits. The current study tests whether the imitation of intentional actions with no functional significance -a behavior that supports the acquisition of social conventions and affiliative bonds, is a specific developmental precursor to CU traits in early childhood. METHODS: Data came from a longitudinal twin study of 628 children (Age 2: 47% females; Age 3: 44.9% females) with observations of arbitrary (i.e., nonfunctional actions) and instrumental (i.e., functional actions) imitation and parent reports of CU traits and oppositional defiant (ODD) behaviors at ages 2 and 3. RESULTS: Lower arbitrary imitation at age 2, but not instrumental imitation, was related to increases in CU traits from ages 2 to 3 (β = -.10, p = .02). CONCLUSIONS: These findings establish early social and affiliative processes in the etiology of CU traits, highlighting that novel personalized treatment and intervention strategies for CU traits may benefit from targeting these processes to help reduce CU traits and risk for persistent conduct problems in children.
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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 | 0.004 |
| 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 | 0.000 |
| 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".