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Criminal Trajectory Clustering×Life-Course Criminology Analysis×
CampoCriminologyCriminology
FamigliaRegression modelProcess / pipeline
Anno di origine20101993
IdeatoreDaniel S. Nagin; Christophe Genolini & Bruno Falissard (KmL)Robert J. Sampson & John H. Laub
TipoAlgorithmic clustering of longitudinal offending trajectoriesTheoretical framework and longitudinal analytic strategy for offending over the life course
Fonte seminaleNagin, D. S. (2005). Group-Based Modeling of Development. Harvard University Press. ISBN: 9780674016866Sampson, R. J., & Laub, J. H. (1993). Crime in the Making: Pathways and Turning Points Through Life. Harvard University Press. ISBN: 9780674176058
AliasOffending Trajectory Clustering, Longitudinal Offending Cluster Analysis, Trajectory Shape Clustering, Crime-Curve ClusteringAge-Graded Theory of Informal Social Control, Sampson-Laub Life-Course Theory, Developmental Life-Course Criminology, Life-Course Theory of Crime
Correlati45
SintesiCriminal trajectory clustering is the broad family of methods that group individuals by the shape of their longitudinal offending curves. Rather than committing to a single statistical model, it spans algorithmic approaches — k-means for longitudinal data, distance-based clustering of trajectory shapes, and likelihood-based latent class growth — and treats the choice of clustering method itself as a modeling decision validated by fit and stability criteria.Life-course criminology analyzes both continuity and change in offending across the entire life span, anchored in Sampson and Laub's age-graded theory of informal social control. The core claim is that social bonds that emerge at different ages — strong marriages, stable employment, military service — function as informal social control that can redirect criminal trajectories, so that change is possible at any age and is not fully determined by childhood propensity.
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ScholarGateConfronta i metodi: Criminal Trajectory Clustering · Life-Course Criminology Analysis. Consultato il 2026-06-25 da https://scholargate.app/it/compare