The Intergenerational Transfer of Psychosocial Risk: Mediators of Vulnerability and Resilience
Bibliographic record
Abstract
The recurrence of social, behavioral, and health problems in successive generations of families is a prevalent theme in both the scientific and popular literatures. This review discusses recent conceptual models and findings from longitudinal studies concerning the intergenerational transfer of psychosocial risk, including intergenerational continuity, and the processes whereby a generation of parents may place their offspring at elevated risk for social, behavioral, and health problems. Key findings include the mediational effects of parenting and environmental factors in the transfer of risk. In both girls and boys, childhood aggression and antisocial behavior appear to predict long-term trajectories that place offspring at risk. Sequelae of childhood aggression that may threaten the well-being of offspring include school failure, adolescent risk-taking behavior, early and single parenthood, and family poverty. These childhood and adolescent behavioral styles also predict harsh, aggressive, neglectful, and unstimulating parenting behavior toward offspring. Buffering factors within at-risk families include maternal educational attainment and constructive parenting practices (e.g., emotional warmth, consistent disciplinary practices, and cognitive scaffolding). These findings highlight the potential application and relevance of intergenerational studies for social, educational, and health policy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".