Infant mental health as we enter the third millennium: Can we prevent aggression?
Bibliographic record
Abstract
Abstract At the end of a murderous century, the author attempts to reflect on the origins of violence and finds that several authors working with murderers hear them talk about their childhood marked by abuse and violence. Research on early manifestations of violence shows that physical aggression present by age five is still the best predictor of physical aggression at adolescence, but also that it is present even before age five, and can be controlled early. Poverty is seen to be an important factor of aggression, particularly in association with family characteristics. Within attachment theory research, insecure attachment, specifically the disorganized‐disoriented (D) pattern, is closely tied up to aggressive behavior at ages five and seven. Development of self‐regulation and empathy in very young children is closely tied up to the empathic caregiving of the environment. Early intervention in disadvantaged areas is shown to lead to long‐term positive results in projects that were built on intensive family support and early education services mostly rendered in home visits. Recommendations are made for continuation of research and early intervention in its various forms, and for the importance of social policies that help all parents with infants and young children, but particularly parents from high‐risk populations. ©2003 Michigan Association for Infant Mental Health.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".