Introduction
The social learning theory seeks to explain the development of antisocial behavior. Akers’ social learning theory is composed of four major concepts. They include differential association, reinforcement, imitation (modeling) and definitions. It postulates that people learn criminal or rather offensive behaviors in the same way they learn noncriminal/offensive behaviors. According to Akers’ theory, reinforcement learning involves getting rewards or punishments for criminal behaviors over time. As far as pro-criminal definitions are concerned, it posits that people who have definitions that favor crime or any other antisocial behavior have a high probability of getting involved in the crime(s) or antisocial behavior(s). The differential association aspect indicates that individuals who spend much of their time with peers that are involved in crime and other antisocial behaviors or peers whose definitions favor such crimes and behaviors are most likely to engage in such behaviors. The imitation component of the theory posits that an individual who witnesses any form of antisocial behavior is more likely to engage in such a behavior in future.
Review of articles
Article 1
The title of the article is Social Learning Theory and Self-control: Assessing the Moderating Potential of Criminal Propensity. The authors sought to expand people’s understanding about the applicability of social learning theory across individuals with varying levels of criminal propensity. It also seeks to establish whether differential association, differential reinforcement as well as pro-criminal definitions are moderated by self-control.
In the background information, the author reviews literature from scholars who support the four main elements of the social learning theory and its applicability to all types of individuals and crimes.-theoretically. Additionally, the author also acknowledges the works of some researchers who argue that the influence of antisocial peers on antisocial behavior may differ depending on other factors such as criminal propensity. It also explores models that seek to explain the development of antisocial behavior with bias on the life-course interdependent model.
Hypothesis 1 posits that that peers will significantly interact with self-control. Hypothesis 2 posits that procriminal definitions and differential enforcement will operate similarly across levels of self-control. If the hypotheses are confirmed, the study would favor SLT over the social amplification process, which is applied in the life-course interdependence model.
The researchers used a qualitative method in the study. They employed a cross-sectional study to examine crime and delinquency among middle and high school students. One of the measures was antisocial behavior, which was also the independent variable. It was measured using a 17-item scale. The second measure was the social learning theory focusing on three of its components namely definitions, peer associations and differential reinforcements. The last measure was self-control.
The results showed that self-control and each of the elements of the SLT had a significant relationship with the respondents’ self-reported antisocial behaviors. Self-control had a negative effect on the occurrence of antisocial behavior or rather the greater one’s self control, the less likely they were to indulge in antisocial behavior. The findings also showed that the effects of SLT constructs were not moderated by self-control (Yarbrough et al., 2011, p. 198). These findings offer more support for the SLT as a general theory of crime as opposed to the social amplification process of the interdependence model.
The authors noted that more empirical attention needs to be focused on the SLT to not only provide a more valid effect of peers to antisocial behavior but also to provide more information that will enhance a better understanding of whether criminal propensity moderates the effect of peers on any given antisocial behavior.
Article 2
The title of the article is Testing Social Learning Theory Using Reinforcements Residue: A Multilevel Analysis Of Self-Reported Theft And Marijuana Use In The National Youth Survey. Brauer seeks to establish a measurement strategy for analyzing two of the major aspects of the social learning theory: reinforcement and definition. He also examined whether the two components of the theory vary with time. The study also sought to derive theoretically valid indirect measures of reinforcement that improve on those that were typically employed in previous studies by using methods that can be easily replicated by future researchers as far as the social learning process is concerned.
The literature review entails some of the analyzing of the existing methods that have been used in studying the theory in both measurements and analyses. He notes that some researchers avoid using important statistical aspects by avoiding using measures of deviant peer associations as proxies for social mechanisms (Brauer, 2009, p. 933). In the study, he supports Krohn’s argument that learning mechanisms take place within associations but do not include a measure of associations in empirical examinations.
Hypothesis 1 posits a positive association between the estimated reinforcement and criminal offending. Hypothesis 2 predicts a positive association between definitions and criminal offending and posits that the definitions will mediate any reinforcement-crime associations.
The main variables of the study were the respondent’s self-report in theft and marijuana use. The main independent variables of the study are the indirect measures of the reinforcement learning process i.e. parent and friend estimated reinforcement of theft and marijuana use. The researcher employed an interval-level frequency variable that ranged from 0 to 100 for the self-report participation in theft. On the other hand, an ordinal-level variable that ranged from 0 to 8 was used for the self-report of marijuana use.
In testing the study’s hypotheses, a multilevel modeling (MLM) approach was used. It employs a maximum likelihood estimation technique that models fixed-effect coefficients and variance/covariance structures of random effects simultaneously (Brauer, 2009, p. 943). Its main advantage is that it allows researchers to assess all the available data across individuals and at multiple points in time using a person-period data format. It offers the benefits of both cross-sectional and longitudinal data analysis techniques. The models were estimated using HLM 6.02 and an over dispersed Poisson sampling distribution.
The results showed that the rates of theft and marijuana behavior increased significantly in the middle (theft) or late teens (marijuana use). The behavior then declined as the individuals approached their late adolescence and young adulthood. Whites, males and urbanites reported higher average rates of theft and marijuana use as opposed to the nonwhites, females and nonurban dwellers.
The findings did not support hypothesis 1. They indicated that the changes in friend and parent reinforcement are inconsequential to later changes in theft or marijuana use rates. Between-individual results offered support to hypothesis 1. The models showed that average friend reinforcement as well as average parent reinforcement are positively associated with average rates of theft and marijuana use (Brauer, 2009, p.948). Youths with more favorable definitions of marijuana use and theft reported higher average rates of their indulgence in the two antisocial behaviors as opposed to their counterparts-youths that hold definitions that are less favorable.
The author asserts that the lack of significant within-individual associations between reinforcement and crime does not necessarily mean that the social learning theory cannot predict within-individual changes in offending behaviors. He recommends that future studies of the theory should factor in additional sources of reinforcement since individuals are subject to a variety of sources of reinforcement. In addition, future research should attempt to replicate the findings of this study using other longitudinal data sets.
Article 3
The title of Morris and Higgins’ article is Criminological Theory in the Digital Age: The Case of Social Learning Theory and Digital Piracy. It seeks to find out if the social learning theory can be applied in crimes that involve the use of digital technology such as digital piracy. It provides important information as far as the use of general theories in such crimes is concerned.
The literature review involved a detailed exploration of the major concepts that Akers incorporated in the theory. One of the concepts that the authors uses is differential association. Additionally, the authors explore Akers’ social structure and social learning (SSSL) model of criminal behavior. The article holds that Differential association is the most important component of SLT. From the literature review, the authors use the link between differential association and participation to determine the application of the SLT in digital piracy. The variables were gender, region, age and race.
Hypothesis 1 posits that being a general theory of crime, social learning theory should account for a substantial amount of variation in explaining digital piracy. Hypothesis 2 postulates that the correlates of digital piracy such as age, gender, race and geographic region should be mediated by the learning process.
Data was collected using self-administered questionnaires that were filled by university students. A random sample longitudinal data and properly time-ordered self-report measures were employed. The necessary measures of the study comprised of multiple indicators of digital piracy, neutralization, individual level demographics, social learning theory measure and the geographic region. A five-point Likert Scale was used to ones association with digital pirating peers. The authors used structural equation modeling for data analysis. It allows the specification of the direction of hypothesized casual relationships. It also allows one to explore the direct and indirect relationships between variables and constructs. Additionally, it allows one to test an entire theoretical model as opposed to coefficients alone.
The results of the study suggested that one’s differential location in the social structure might be an important part of understanding digital piracy, which may lend itself to formally extending social learning theory to the digital environment. They also suggested that SLT might account for a substantial amount of variation in the likelihood to engage in digital piracy. The results have shown that individuals are likely to follow the social learning process that will lead them to digital piracy. The results were modestly supportive of the social learning theory. However, the data did not allow for a complete test of SLT and the SSSL. The results also indicated support for the view that the correlates of digital piracy are substantially mediated by social learning theory.
In the conclusion, the authors assert that scholars can be able to shed light on the existing theories by exploring crimes that occur in the digital world. Although general theories can be used to explain almost all the crimes, scholars need to come up with theories that seek to explain crimes that involve the use of digital technology e.g. piracy. The authors asserts that much research is required to enhance a better understanding of the impact of learning process in explaining digital crimes. The social learning theory explains a great deal of the variation in the probability of an individual to be get involved in piracy. The authors also note that the social learning theory requires substantial improvements through the modification of its components. This will enable it to address all virtual groups that may influence one’s behavior.
Conclusion
The three articles provide essential information as far as the social learning theory is concerned. They have demonstrated the interaction between the various components of the theory as used to explain antisocial behaviors. Additionally, the researchers have identified areas, which can be studied in the future as far as determining the applicability of the theory is concerned.
References
Brauer, J. R. (2009). Testing Social Learning Theory Using Reinforcements Residue: A
Multilevel Analysis Of Self-Reported Theft And Marijuana Use In The National Youth Survey. American Society of Criminology, 47(3), 929-971.
Morris, R. G., & Higgins, G. E. (2010). Criminological Theory in the Digital Age: The Case of
Social Learning Theory and Digital Piracy. Journal of Criminal Justice, 38, 470-480.
Yarbrough, A., Jones, S., Sullivan, C., Sellers, C., & Cochran, J. (2011). Social Learning Theory
and Self-control: Assessing the Moderating Potential of Criminal Propensity. International Journal of Offender Therapy and Comparative Criminology 56(2), 191-204.
