Again we find that individuals living in states that have statutorily removed jail sentences as penalties for possession of up to an ounce of marijuana are statistically less likely to report jail as the maximum penalty and more likely to report fines as the maximum penalty. However, again we see that the actual difference in knowledge across states is small. Interestingly, the “Don’t Know” rates in Table 3 correspond relatively closely to the “Don’t Know” rates in the 1976 and 1980 Monitoring the Future Survey data in Table 2 . There is no indication that citizens perceive themselves to be better informed in one period than in the other. Our study finds significant associations between the maximum penalty specified in state marijuana laws and people’s knowledge of those maximum penalties. But the associations are very small in magnitude. Citizens in decrim states are only about 27 % more likely to believe the maximum penalty for possessing an ounce of marijuana is a fine or probation . About a third of citizens in each type of state believes the maximum penalty is a jail sentence. The modest magnitude of these knowledge effects helps to clarify why decriminalization effects are fairly weak and inconsistent. The answer appears to be that people are not oblivious to their marijuana laws, but their awareness is pretty tenuous. It appears that people were more aware of their state penalties in 1980 than today . Why? One possibility is that it is the publicity surrounding a change in law, drying racks rather than the law’s actual implementation, that produces differences in citizen perceptions by state. In the 1970s, the initial decision to decriminalize marijuana was a matter of active public debate. MacCoun and Reuter report that in the 1970s, 22 out of 22 New York Times op-ed essay on drug legalization or drug decriminalization mentioned marijuana; only 15 out of 37 did so in the 1990s.
We believe that recent changes in these penalties have received far less publicity; only those interested in obtaining this information search it out. Another possibility, again not mutually exclusive, is that there has been erosion over time in knowledge of what may have been, in the 1970s, a real policy change. Indeed, research in other policy areas have shown that the impact of a policy is usually seen within a one to three year period following the policy’s adoption/effectiveness date . Given that many of the depenalization policies examined here occurred well before 2001, time may have decayed people’s knowledge or awareness of the laws. Thus the data we present here create a new puzzle for the decriminalization literature. Early studies failed to find an effect of decriminalization in an era in which citizens clearly recognized a difference in policies across states. But some recent studies have appeared to find a decriminalization effect in a more recent era, when citizens can just barely detect a difference in state laws. This is not how perceptual deterrence is supposed to operate. Either some studies are misestimating decriminalization effects , or we do not adequately understand the psychology of deterrence. South Africa has one of the highest rates of incarceration globally , most commonly among young men under the age of 35 years. Over 97% of SA’s prison population are men. Violence is pervasive with about half of SA men between the ages of 12 and 22 years old admitting to committing at least one criminal offence, and it is almost always a violent offense. Reports include assaults of others at school , in public places and at home , with 92.9% of the victims reporting that they knew the identity of the perpetrator. In addition, 30% of young men report committing physical or sexual violence against their partners. The current study complements previous research focusing on young men’s management of alcohol and drug behaviors as the primary source of criminal acts by considering both individual- and community-level factors associated with ever being arrested in SA.
Substance use is associated with higher rates of township violence and is linked to 75% of homicides, 67% of domestic violence, and 30% of hospital admissions. Gaining access to drugs often involves stealing, selling, or bartering goods and services–each acting as a pathway to engagement in criminal activity. Almost a third of young SA men report symptoms of alcohol dependency; half report recently using cannabis ; and a third recently used methamphetamine. The rates of substance dependence among SA offenders range from 10%–48% for males. In a SA study , 45% of arrestees tested positive for cannabis , methaqualone , opiates, cocaine, amphetamines, and/or benzodiazepines, with cannabis and methaqualone being the most prevalent. Those arrested for housebreaking and drug/alcohol offenses and those arrested at least once before are also more likely to test positive for drugs. Thus, substance use is hypothesized to be associated with ever being arrested among young men living in SA township neighborhoods. The high rates of substance use, violence, and incarceration in SA have been linked to unemployment, lower incomes, fewer years in school, younger age, being unmarried, and having mental health issues. More recently, attention has been focused on the mental health of individuals who come into contact with the criminal justice system. As with many other countries, SA experiences high rates of neuropsychiatric disorders in its prison system. Thus, we expect these individual factors and mental health risks to be associated with arrests. Research often focuses on youth’s background and risk behaviors to understand acts leading to arrests. Yet, globally it has been demonstrated that community disorder, poverty, and infrastructure are linked to rates of crime. Social disorganization theory suggests that where an individual lives has a substantial impact on their propensity to commit crimes or engage in criminal or delinquent behavior. Specifically, in contexts where there are few social bonds, crime and delinquency thrive. However, it is unknown whether these social processes operate in the same way across different disadvantaged neighborhoods. Shaw and McKay’s classic study in Chicago reports an ecological model of crime by mapping thousands of incidents of juvenile delinquency.
The results show that high rates of poverty and ethnic heterogeneity, combined with high levels of residential stability and single-parent households, are indicators of high criminality. Further, neighborhoods characterized by poverty and negative familial factors have been found to contribute to high arrest rates among youth in the U.S. and adolescent anti-social acts in Mexico. However, the applicability of social disorganization theory in SA is unclear. The applicability of Western criminological theories to urban SA has been previously demonstrated, but there are important differences in the ecological dynamics of violent crime across differing cultures. In SA, with the socio-political history of violence and oppression, the socioeconomic conditions of communities are likely to be important contributors to high criminality. However, there are limited data in post-apartheid SA. Research with individuals needs to take into account differences in the properties of the groups in which they belong.In some cases, neighborhood-level differences have been found to be significantly associated with outcomes, even when there is no significant variability between neighborhoods. These data suggest that assessing how individual and neighborhood effects are reciprocal and inherently related would lead to a better understanding of neighborhood effects on arrests. However, the relationship between arrests and individual- or community-level risk factors is far less studied in low and middle-income countries , such as SA. In township neighborhoods, infrastructure , limited opportunities for employment, gang activity, and the presence of small, informal and often illegal bars may function to exacerbate or dampen an individual’s risk of being arrested. The aim of this cross-sectional study is to examine arrest rates across low-resource township neighborhoods in Cape Town, SA. A community sample of young Black-African men was recruited from five areas within two Cape Town townships. Townships are peri-urban settlements that vary significantly in years since establishment, infrastructure,cannabis drying and access to services. In post-apartheid SA, townships experienced a major influx of migrants in search of work, which resulted in the rapid development of new informal township neighborhoods. Accordingly, the older township communities are more formalized with access to municipal roads, a police station, and community clinics.
However, the newly established communities are more informal, where the large majority of the residents are living in informal housing , with limited access to basic services. Thus, community-level factors such as less formal housing, fewer household sources of water , and food security, as well as greater number of bars and violence are hypothesized to be associated with having a history of arrests. This study examines: the individual- and community-level factors associated with a history of arrests among young men living in the townships of Cape Town, SA; and whether these factors are significant predictors of contact with the criminal justice system. The data used in this article are part of the baseline assessment for a larger longitudinal study investigating the impact of a public health intervention to improve the health of young men living in low-resource communities. Understanding the associations between individual factors, the community context, and having a history of arrests is important to plan interventions which seek to reduce the risk of arrests and re-arrests among young men in SA.Community clusters containing approximately 450–600 households, including roughly 50 young men per neighborhood, were identified in two Cape Town townships: Khayelitsha and Mfuleni. In each community, a random spot was selected, and recruitment proceeded house-to-house in concentric circles until a sample of 50 young men aged 18 to 29 was reached. If other household members reported that there was a male that slept there at least four nights a week, the interviewer returned repeatedly to solicit voluntary participation of the young man. Potential participants were only excluded if they were unable to understand the recruiter, appeared to be actively hallucinating, or lacked capacity to consent. Individuals who appeared to be under the influence of alcohol or drugs during the time of recruitment were enrolled in the study, but were only interviewed once they were no longer intoxicated. Assessments were conducted at a local research facility in the township, with transport provided. Of the 994 men approached, 5% declined to participate or were identified but could not be found later to complete the assessment . The final sample included 906 young men aged 18–29 years old .First, individual-level and community-level risk factors were compared based on the history of arrests across all neighborhoods. As a first step, chi-squared analyses were used to identify significant covariates between young men who have been arrested and those who have not. From these identified covariates, the most relevant variables were entered into a multiple predictor logistic regression to identify individual- and community- level risk factors associated with arrests. Odds ratios with 95% confidence intervals are presented. To identify communities with a high versus low number of arrests, we compared the proportion of men who have ever been arrested in each neighborhood. Since less than half of the young men reported ever being arrested, a reasonable split of 25% of the communities with the highest arrest rates was compared with 25% of the communities with the lowest arrest rates . We then compared measures of individual- and community-level risk factors between the communities with a high and low number of arrests using chi-squared analyses . This enabled analysis between neighborhoods by comparing aggregate measures of community-level risk factors. All analyses were conducted using SPSS Statistics 23.Substance use and gang involvement are the strongest predictors of ever being arrested. Substance use is consistently linked with high levels of violence and gang involvement. Most notably, young men using methamphetamine are three times more likely to be arrested than young men who abstained. Alcohol users are almost twice as likely to report ever being arrested compared to non-drinkers. This is consistent with previous studies in both HIC and LMIC –including SA –that link substance use with arrest history and incarcerations. This is one of the first studies to examine both individual and community characteristics linked to contact with the criminal justice systems among SA men. While poverty is widespread in these peri-urban settlements in Cape Town, this classification of resources may not be sufficient to explain the high rates of criminal activity among different SA communities, especially if more than half of young men report engaging in substance use or risky delinquent acts.