From the Frustration–Aggression Hypothesis to Moral Reasoning and Action
Bibliographic record
Abstract
Gian Vittorio Caprara was born in Italy in 1944. He is Emeritus Professor in Psychology at the University of Rome and was also a fellow at the Netherlands Institute for Advanced Study and at the Swedish Collegium for Advanced Study. He founded the Interuniversity Center for the Study of Prosocial and Antisocial Motivation in Italy. He studied three major topics – personality, aggression, political preferences and participation – with an interactionist and social cognitive approach in which personality is considered a self-regulatory system while biological potential is mostly conditioned by culture. He initiated the Genzano Longitudinal Study, which followed 10-year-old children from elementary school through adolescence. The study focused on the development of aggression and prosocial behavior; stability and change in personality; the determinants of academic achievement and vocational choices; family and romantic relations; and civic and political behavior. The study investigated how different aspects of personality operate in concert. The aim was to clarify pathways that lead to maladjusted and risky behaviors. The findings led to the development of a theory that assigns to marginal deviations from normative behaviors a crucial role in the development of maladjusted behavior. The study also led to psychosocial interventions promoting and sustaining healthy 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".