Becker (2021)

Abstract

  • This study investigates the impact of social control and social learning variables on involvement in violent vs. non-violent extremism.

  • Data sourced from the Profiles of Individual Radicalization in the United States (PIRUS) database with a sample of 1,757.

  • Key findings show that weaker social control and stronger social learning of violence correlate with violent behavior.

Introduction

  • Context of Violence: Notable incidents like the Pittsburgh Synagogue shooting raise questions on the causes of extremism.

  • Research Gap: Limited criminological research distinguishing between violent and non-violent extremists despite increasing occurrence.

  • Research Queries: What prompts individuals to resort to violence, and how can these actions be prevented?

Theoretical Framework

Social Control Theory

  • Explores forces that inhibit criminal and deviant behavior, emphasizing informal sanctions over formal deterrents.

  • Hirschi’s Bonds: Attachment, Involvement, Commitment, and Belief.

  • Importance of strong bonds to conventional society is reinforced; weak bonds may lead to antisocial behavior.

Social Learning Theory

  • Centers around individual interactions leading to learning behaviors.

  • Key Constructs include:

    • Differential Association: Associating with individuals who normalize violence increases likelihood of engagement in such behavior.

    • Imitation and Definitions: Exposing individuals to models of violence, and defining it as acceptable behavior influences their propensity to commit violent acts.

Methodology

  • Utilizes the PIRUS dataset accounting for various extremists across multiple ideologies accessed through public domain sources.

  • Inclusion criteria for individuals in the study based on criminal actions and ideological motivations.

  • Data collection involved coding demographic and behavior attributes, producing a final dataset of 1,757 individuals.

Results

Bivariate Analysis

  • Social Control Indicators Associated with Violence:

    • Married status, Work History, Unstructured Time, Aspirations, Radical Beliefs.

  • Social Learning Indicators Related to Violence:

    • Actively Recruited, Clique Radicalize, Gang Association, Behaviors Trajectory.

Multivariate Regression Analysis

  • Models confirmed relationships:

    • Stronger informal social control negatively related to violent extremism.

    • Social learning metrics, particularly gang affiliation and extremist group membership, positively correlated with violence involvement.

  • Mixed support for control and learning theories in predicting violent behavior amongst extremists.

Discussion

  • Findings suggest dual mechanisms of social control and social learning are both crucial in understanding pathways to violent extremism.

  • Importance of adult social bonds in reducing engagement in violence was emphasized, particularly in the context of marriage.

  • Presence of weaker belief structures leading to violent behavior aligns with existing literature on radicalization and significance quest.

Limitations

  • Acknowledges potential biases in data availability related to dramatic events overshadowing non-violent extremist actions.

  • The longitudinal application of social control and learning theories might not capture the evolving nature of radicalization.

Conclusion

  • This study enhances understanding of factors that differentiate violent and non-violent extremists and suggests the value of integrating criminological approaches to tackle radicalization.

  • Recommendations for future research include exploring additional criminological theories and methodologies to further dissect the complexities behind violent extremism.