گروه، باندهای، و بزهکاری: آیا سازمان اهمیت دارد؟
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|38579||2010||13 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Criminal Justice, Volume 38, Issue 5, September–October 2010, Pages 921–933
Abstract Purpose A consistent finding of research on delinquency has been that gang members show higher levels of delinquent behavior than non-gang members. However, research attempting to understand the mechanisms underlying this finding is lacking. The basic premise of the current article is that the level of organization found in delinquent groups and gangs matters in clarifying the relationship between membership and delinquency. Methods This article examined the association between organization and delinquency in a sample of 523 self-reported juvenile offenders from a high school survey conducted in the province of Quebec, Canada. Results The results showed that 1) there is clearly something special about membership in a gang that influences delinquency beyond the more general membership in a delinquent group; 2) the key to understanding finding lies, in part, in the level of organization found in gangs. Organization emerged as the most important factor associated with general delinquency, involvement in violence, and in drug supply offences, significantly (but not completely) reducing the effect of gang membership on delinquency. Conclusions Even if most delinquent associations show little signs of formal structure and organization, this study demonstrates the importance of organization as a key mechanism to understand the gang effect on delinquency.
نتیجه گیری انگلیسی
Results Table 1 compares involvement in delinquent activities and drug use among non-group members (N = 308), those who identified as belonging to a delinquent group (N = 171), and those who identified as gang members within the past 12 months (N = 44). This categorization allows for a direct comparison of offending along a continuum that not only examines the potential differences between gang and non-gang youth but also includes comparisons of non-group members and delinquent group members. As expected, there was an increase in offending from non-group to group members, and then to gang members. In fact, gang members reported higher prevalence and mean rates in all categories of delinquent activities. For example, we noticed a significant increase in the severity of offending from non-group to gangs with gang members reporting participation in almost five types of offenses (4.8), groups of delinquents reporting approximately two to three offenses (2.5), and non-group members reporting fewer than two offenses on average (1.8). Table 1. Comparison of non-group, group, and gang members on the participation in delinquent activities and drug use Non-Groupa (308) Group (171) Gang (44) Group vs. Non-Group Gang vs. Non-Gang Group vs. Gang Control Variables Age 15.6 15.5 15.6 n.s n.s n.s Gender % % % Male 59.1 72.5 81.8 ** * n.s Female 40.9 27.5 18.2 Low Income Neighborhood 21.1 24.6 36.4 n.s * n.s Drug Use Cannabis Use (0-5) 1.38 1.94 2.80 *** *** ** Hard Drug Use (0-1) 0.04 0.13 0.30 ** *** ** Offence Scales General Delinquency (1-10) 1.77 2.54 4.78 *** *** *** SD (1.25) (1.57) (2.66) Drug Supply (0-3) 0.50 0.85 1.50 *** *** *** SD (0.78) (1.03) (1.05) Violent Offenses (0-2) 0.12 0.20 0.89 n.s *** *** SD (0.33) (0.40) (0.87) Property Offenses (0-2) 0.30 0.30 0.77 n.s *** *** SD (0.46) (0.46) (0.86) Note. independent sample t-tests *p < 0.05, **p < 0.01, ***p < 0.001 (two-tailed). a. The non-group category refers to those offenders who are part of neither groups nor gangs. Table options The examination of drug use variables also revealed that the consumption of cannabis or hard drugs significantly increases as we go from non-group members to gang members. Thirty-percent of gang members, for example, reported consumption of hard drugs at least twice a week in this sample, compared to 13 percent and 4 percent for group and non-group members, respectively. Note that the differences between group and non-group members were not always important, or statistically significant. Of interest was the lack of significant differences between the groups for property and violent offenses shown in Table 1 between these two groups. Similarities were also found in the socio-demographic characteristics between groups. For instance, group and gang members appeared to be similar with respect to age, gender, and SES. But when gang and non-gang youth are compared, results show that gang members were more likely to be male and to come from a low income family than were non-gang members. In Table 1 it was found that gang members are more likely to be involved in delinquency compared to those respondents who do not belong to a gang, and even to those who belong to an identifiable delinquent group. What is unclear is whether differences in the level of organization between groups and gangs can help clarify this finding. This issue was examined further by comparing respondents on the types and number of organizational features of their group/gang (Table 2). Obvious from Table 2 is that groups scored much lower than gangs on the organizational scale (mean = 4.0 (sd. 3.3) vs. 1.3 (sd. 1.9). The relatively high standard deviation for both gangs and groups reveals important variation in both samples, as some groups both especially gangs are found at both extremes of the organization continuum. In addition, recall that a smaller proportion of group members reported organizational features (51 percent) compared to gangs (77 percent). Yet, the important point is that a majority of delinquent groups do show some features that are usually attributed to gangs only. The organizational features reported by delinquent group members varied widely. The most common feature was defense of honor/reputation (29.2 percent), followed by presence of a meeting location (22.8 percent), and rules and distinction signs (13.5 percent). The most frequently reported organizational feature for gang members was also defense of honor/reputation albeit at a much higher prevalence rate (61.4 percent). The next highest organizational feature reported by gang members was the protection of a specific territory (50.0 percent) or ‘turf’, a feature typical for gangs, especially those involved in dealing drugs. Very few delinquent group members reported protecting a specific territory (11.1 percent), or mentioned that their group had a hierarchical structure (11.7 percent), features we also expected to be more typical of gangs. Table 2. Comparison of gang and delinquent group members on various organizational properties Gang Members (N = 44) Group members (N = 171) Phi Organization Scale % % Group Name 40.9 9.4 0.35*** Group Leader 43.2 9.9 0.36*** Hierarchy 43.2 11.7 0.33*** Meeting Location 40.9 22.8 0.17* Distinctive Signs/Codes 38.6 13.5 0.26*** Rules 47.7 13.5 0.34*** Initiation 34.1 11.7 0.25*** Protect Territory 50.0 11.1 0.40*** Defend Honor/Reputation 61.4 29.2 0.27*** Organization Scale 0-9 0-9 Meana 4.0 1.3*** Median 4.0 1.0 SD 3.3 1.9 Note. *p < 0.05, **p < 0.01, ***p < 0.001 (two-tailed). a. Independent sample t-test. Table options Of interest in the current study is whether a higher score on the organization scale is associated to delinquency. To find out, the correlations between organization and delinquency among two sub-samples of gang or group respondents were considered (Table 3). First, the influence of organization on delinquency for gang members only was examined (N = 44). A moderate, positive correlation was observed for organization and general delinquency (0.39, p < 0.05) where higher levels of organization reflect an increase in delinquency. Examination of the types of crimes composing the general delinquency scale revealed some interesting differences. The correlation between violent offenses and organization was the only significant correlation (0.36, p < 0.05). No other correlation was found to be significant, including involvement in drug supply offenses. A similar moderate correlation between organization and general delinquency (0.31, p < 0.001) was found when we selected only respondents who reported being “group members” (N = 171). Again, this positive relationship did not hold for all types of crimes. The level of organization was not significantly related to involvement in violent or property offending, but was positively related to involvement in drug supply offenses (0.25, p < 0.01). Unlike the findings for gang members, the frequency of cannabis use and involvement in hard drug use was significantly and positively related to the level of group organization. Table 3. Spearman's rho correlations of organization with different types of crimes and drug use for gang members and group members Gang members (N = 44) Group members (N = 171) General Delinquency 0.39* 0.31*** Drug Supply Offenses 0.17 0.25** Violence Offenses 0.36* 0.05 Property Offenses 0.18 0.04 Cannabis Use -0.01 0.27*** Hard Drug Use 0.16 0.18* Note *p < 0.05, **p < 0.01, ***p < 0.001 (two-tailed). Table options Multivariate analyses The previous section suggested that 1) the qualitative distinction between gangs and groups is important to take into account, and that 2) the higher level of organization found in gangs might account for gang members' higher levels of delinquency. The multivariate analyses began by examining the general delinquency scale (1-10) using zero-truncated negative binomial regression (Table 4). The effect of organization and group/gang membership on delinquency was analyzed using two different sub-samples. First, non-group and group members only were selected (N = 479) to examine the effect of group membership on delinquency. Next, only delinquent group and gang members were selected (N = 215) and two different models were run. Model 1 examined the impact of gang membership when only group and gang members are considered. Model 2 added scores on the organization scale to the model in order to determine whether organization is associated to delinquency beyond the effect of gang membership. Table 4. Estimated parameters in zero-truncated negative binomial for general delinquency Group vs. Non-group/ganga (N = 479) Group vs. Gang (N = 215) Model 1 Group vs. Gang (N = 215) Model 2 Control Variables b(SE) z b(SE) z b(SE) z Age 0.063 (0.058) 1.09 0.030 (0.051) 0.59 0.000 (0.049) 0.00 Gender 0.369 (0.118) 3.12** 0.365 (0.133) 2.74** 0.372 (0.138) 2.69** Low SES 0.108 (0.113) 0.96 0.199 (0.117) 1.71† 0.239 (0.114) 2.10* Cannabis Use 0.302 (0.054) 5.62*** 0.254 (0.058) 4.34*** 0.246 (0.051) 4.82*** Hard Drug Use 0.416 (0.117) 3.56*** 0.338 (0.121) 2.79** 0.274 (0.097) 2.83** Group Membership 0.420 (0.104) 4.05*** -- Gang Membership -- 0.492 (0.123) 3.99*** 0.266 (0.123) 2.17* Organization Scale -- -- 0.079 (0.017) 4.74*** χ² 162.19 121.83 170.18 Log Likelihood -635.93 -361.45 -350.39 McFadden's Adjusted R² 0.05 0.09 0.12 Cox & Snell R² 0.117 0.35 0.41 Notes. *p < 0.05, ** p < 0.01, ***p < 0.001, † marginal p < 0.10; robust standard errors reported. a. The non-group category refers to those offenders who are part of neither groups nor gangs. Table options When gang members were excluded (left hand side of Table 4), we found that group membership is independently associated with delinquency involvement. The idea that “membership” is associated with increased delinquency levels also seems to apply to delinquent group members when gang members are not considered. The frequency of both cannabis and hard drug use were also significant, positive predictors. Of the socio-demographic variables, gender played a role in how many different offenses are committed by our respondents, where males (unsurprisingly) reported a larger number of offenses than did females. Selecting only gang and group members (N = 215), the right side of Table 4 examines the independent influence of organization beyond gang membership. Starting with model 1, results indicated again that gang membership is strongly associated with delinquency. Cannabis use, hard drug use, low SES and gender were also significant, positive predictors. The organizational scale was then added in model 2. Not only did organization matter, but it was found to be a stronger predictor of delinquency (z = 4.93, p < 0.001) than was gang membership (z = 2.23, p < 0.001). Adding organization to the model decreased the importance of gang membership by a factor of 2. In short, even though the qualitative effect of gang membership remains, the effect of organization may be most important in capturing increases in delinquency involvement. 14 What happens when the general delinquency scale is broken down to examine specific types of offenses? Variations in a count of drug supply offenses (0-3) was examined in Table 5 using standard Poisson regression. Following the same format as for the general delinquency scale, the left side of Table 5 compares group and non-group members (N = 479). Similar results were found: belonging to a delinquent group was a significant predictor of involvement in drug supply. An unexpected result was found, however, when only gang and delinquent group members were considered (N = 215, right side of Table 5). Model 1 shows that gang membership was not found to be a significant predictor of the number of drug supply offenses this subset of respondents was involved in. If “membership” per se does not matter for drug supply offenses, does the level of organization of the group or gang matter? Model 2 shows that organization does matter, as it was found to be a significant predictor of drug supply involvement. This suggests that it is not mere membership in a gang that matters for drug suppliers, but rather how organized the gang or the group is. Table 5. Estimated parameters in standard poisson regression for drug supply offenses Group vs. Non-group/ganga (N = 479) Gang vs. Group (N = 215) Model 1 Gang vs. Group (N = 215) Model 2 Control Variables b(SE) z b(SE) z b(SE) z Age 0.113 (0.059) 1.90† 0.010 (0.058) 0.18 -0.009 (0.057) -0.15 Gender 0.119 (0.120) 0.99 0.182 (0.152) 1.20 0.191 (0.155) 1.23 Low SES 0.289 (0.129) 2.24* 0.200 (0.157) 1.27 0.241 (0.158) 1.53 Cannabis Use 0.648 (0.063) 10.25*** 0.615 (0.069) 8.90*** 0.602 (0.066) 9.17*** Hard Drug Use 0.384 (0.163) 2.35* 0.304 (0.145) 2.10* 0.292 (0.139) 2.10* Group Membership 0.276 (0.115) 2.39* -- -- Gang Membership -- 0.096 (0.121) 0.79 -0.038 (0.129) -0.30 Organization Scale -- 0.056 (0.021) 2.61** χ² 259.43*** 180.42*** 186.84*** Log Likelihood -436.89 -236.38 -234.30 McFadden's Adjusted R2 0.16 0.16 0.17 Cox and Snell R2 0.31 0.39 0.41 Notes. *p < 0.05, ** p < 0.01, ***p < 0.001, † marginal p < 0.10; robust standard errors reported. a. The non-group category refers to those offenders who are part of neither groups nor gangs. Table options Next, logistic regression was used to examine involvement in violent offenses. Comparing non-group and group members (N = 479, left side of Table 6), results revealed a now familiar pattern: group membership was a significant indicator of involvement in violent offenses. Age was a significant factor as well, with older offenders having a greater likelihood of committing violent offenses. Moving to the selected sample of gang and group members only (model 1, right hand side of Table 6), gang membership was also found to be strongly associated with involvement in violence. But does the level of gang/group organization matter? Model 2 suggests that it does: the higher the level of organization, the higher the likelihood of involvement in violent offending. The addition of organization decreased the importance of gang membership from model 1, but this variable still remained a significant predictor. Both gang membership and organization are important factors to take into account when considering involvement in violence. Table 6. Estimated parameters in logistic regression for violent offenses Group vs. Non-group/ganga (N = 479) Group vs. Gang (N = 215) Model 1 Group vs. Gang (N = 215) Model 2 Control Variables b(SE) z b(SE) z b(SE) z Age 0.342 (0.147) 2.33* 0.414 (0.191) 2.16* 0.377 (0.205) 1.84† Gender 0.563 (0.300) 1.88† 1.03 (0.461) 2.23* 1.032 (0.480) 2.15* Low SES 0.020 (0.299) 0.07 0.637 (0.363) 1.75† 0.717 (0.373) 1.92† Cannabis Use -0.141 (0.144) -0.98 0.158 (0.174) 0.91 0.143 (0.177) 0.80 Hard Drug Use 0.359 (0.458) 0.78 0.245 (0.444) 0.55 0.108 (0.442) 0.24 Group Membership 0.613 (0.260) 2.36* -- Gang Membership -- 1.43 (0.389) 3.69*** 1.020 (0.435) 2.34* Organization Scale -- -- 0.179 (0.068) 2.64** Χ2 15.71* 33.80*** 44.17*** Log Likelihood -194.07 -109.00 -106.543 McFadden's Adjusted R2 0.01 0.09 0.11 Cox and Snell R2 0.04 0.16 0.18 Notes. *p < 0.05, ** p < 0.01, ***p < 0.001, † marginal p < 0.10; robust standard errors reported. a. The non-group category refers to those offenders who are part of neither groups nor gangs. Table options The last series of logistic regression models examined involvement in property offenses (Table 7). As can be seen, trying to predict involvement in property offenses was more difficult with the set of variables used in this study. When group members were compared to non-group members (N = 479, left side of Table 7) there was not a single predictor associated with involvement in property offenses. Similarly, gang membership was not a significant predictor of property offenses when group members and gang members were examined separately (N = 215, right side of Table 7). The addition of organization (model 2, right hand side of Table 7) did not help either, suggesting that neither membership nor organization is associated to involvement in property crime. What matters however, is the intensity of drug use: both cannabis (0.27, p < 0.10) and hard drug use (0.88, p < 0.05) were found to be positive predictors of property crime. Table 7. Estimated parameters in logistic regression for property offenses Group vs. Non-group/ganga (N = 479) Group vs. Gang (N = 215) Model 1 Group vs. Gang (N = 215) Model 2 Control Variables b(SE) z b(SE) z b(SE) z Age -0.043 (0.109) -0.40 0.056 (0.170) 0.33 0.040 (0.171) 0.24 Gender -0.225 (0.211) -1.07 -0.093 (0.360) -0.26 -0.090 (0.362) -0.25 Low SES 0.192 (0.237) 0.81 0.350 (0.350) 1.00 0.374 (0.353) 1.06 Cannabis Use 0.158 (0.113) 1.40 0.264 (0.162) 1.63 0.256 (0.162) 1.58 Hard Drug Use 0.403 (0.387) 1.04 0.967 (0.426) 2.27* 0.933 (0.425) 2.19* Group Membership -0.058 (0.214) -0.27 -- -- Gang Membership -- 0.581 (0.379) 1.53 0.423 (0.422) 1.02 Organization Scale -- -- 0.062 (0.068) 0.90 Χ2 6.28 15.60* 16.32* Log Likelihood -288.03 -128.00 -127.57 McFadden's Adjusted R2 -0.01 0.02 0.02 Cox and Snell R2 0.01 0.09 0.09 Notes. *p < 0.05, ** p < 0.01, ***p < 0.001, † marginal p < 0.10; robust standard errors reported. a. The non-group category refers to those offenders who are part of neither groups nor gangs.