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Testing a promising homicide reduction strategy: re-assessing the impact of the Indianapolis “pulling levers” intervention

Journal of Experimental Criminology volume 5, pages 63–82 (2009)Cite this article

Abstract

Since the publication of analyses suggesting the significant impact on youth homicide of the Boston “pulling levers” intervention, a series of studies of similar strategies have indicated promise in reducing homicide and gun assaults. One of these studies was an assessment of a pulling levers strategy in Indianapolis, where trend analyses indicated a significant reduction in homicide following the intervention, while six other similar Midwestern cities did not experience a significant decline in homicide. We re-assess the results of the Indianapolis study by disaggregating the offenses into gang- and non-gang homicides. Given that the pulling levers program focused on influencing gangs and networks of chronic offenders, the impact of the intervention should be more apparent for gang homicides than for non-gang homicides. Alternatively, should the impact be similar for non-gang homicides, then it is more likely that the downward trend would be caused by unmeasured external forces. Coefficient-difference tests relying on estimates obtained from autoregressive integrated moving average (ARIMA) time–series models indicate that gang homicides declined significantly more than did non-gang homicides following the Indianapolis intervention. These findings suggest ‘something happened’ to gang homicides that did not happen to non-gang homicides, which adds further support that the pulling levers initiative was the driving force behind the overall reduction in homicide in Indianapolis.

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Fig. 1

Notes

  1. Also included in the assessment by Rosenfeld et al. (2005) was the New York Compstat program (see Kelling and Sousa 2001 for a discussion) and the Project Exile program in Virginia (see Raphael and Ludwig 2003 for a discussion)

  2. It should also be noted that Berk (2005) raises a number of methodological and statistical limitations in the Rosenfeld et al. (2005) manuscript.

  3. The pulling levers element of the Chicago strategy was rooted among several other violence prevention approaches (see Papachristos et al. 2007)

  4. It is important to note that the first major study that examined the neighborhood–gang homicide relationship was conducted by Curry and Spergel (1988). They found that gang homicides were more likely than non-gang homicides to occur in socially disorganized areas. However, their study was limited to data in Chicago between 1978 and 1985 (i.e., prior to the gang homicide epidemic). In addition, their focal point of ‘disorganization’ mostly involved the percent of Hispanics living in a community (i.e., ethnic heterogeneity). More recent studies have failed to find a substantive relationship between structural measures and gang homicide when compared with non-gang homicide.

  5. While this finding supports the ‘awareness’ of offenders in the IVRP, Chermak (2007) found in a later evaluation that implemented an experimental design in Indianapolis that offenders’ in the two treatment groups (law enforcement and community probationers) as well as the control group had similar recidivism patterns.

  6. The research team observed the incident reviews and coded a variety of dimensions of the incidents. Some details, such as whether the incident was gang motivated or drug motivated, could not be reliably coded due to a lack of information. However, two-person independent coding revealed congruence of over 90% on whether the incident was gang-involved, drug-involved, the type of weapon, and for other variables described herein.

  7. Chermak (2007) later found that, in subsequent years, it became difficult for the IVRP task force to maintain the tight connection between the incident reviews and the groups targeted for pulling levers.

  8. In order to assess the face validity of the gang/non-gang homicide classification in Indianapolis, we compared gang homicide rates in other cities. Since this study relied on the Los Angeles definition of gang homicide, it was important to compare the proportion of gang homicides observed in Indianapolis with that in Los Angeles. Nearly 45% of all homicides in Los Angeles were gang related between 1994 and 1995 (Maxson 1999). In Newark, NJ, homicides were gang related in 40% of the cases between 1999 and 2004 (Pizarro and McGloin 2006). Thus, the proportion of gang related homicides in Indianapolis (51.9%) was consistent with that in prior gang research.

  9. Between October 1998 and May 1999 a total of 17 pulling levers meetings were held. Eight occurred prior to the Brightwood arrests and nine subsequently thereafter. Approximately 320 individuals attended these meetings (McGarrell and Chermak 2003a).

  10. The original race categories were white, African American, Hispanic, and other. The use of non-white as a dummy variable serves both theoretical and empirical purposes. First, prior gang research has shown that African American communities (Kubrin and Wadsworth 2003) and Hispanic communities (Curry and Spergel 1988) are at greater risk for gang activity. Second, Hispanics made up a very small percentage of both victims and suspects in Indianapolis homicides. Specifically, where the race of the actor was known, Hispanics made up fewer than 2.9% (29 of the 1,027 known victims and suspects combined) of the cases. Thus, for theoretical and empirical clarity, Hispanics and African American actors were collapsed into a non-white category.

  11. The joint distribution of inclusion concerning the victim’s demographic information was 95.2% (536/563). Comparatively, 36% (203/563) of the suspects’ demographic data were coded as missing due to a high number of unknown suspects. Where there were multiple suspects per homicide incident (122 incidents in total, or roughly 17.9%), the average age, proportion of non-white, and proportion of male individuals per incident were used where the demographic information of the suspect was known.

  12. There were 563 total homicides between January 1997 and June 2001. Some homicides were not included in the distribution of the situational measures due to missing or incomplete data on the incident. These incomplete data varied by measure. Thus, missing data were excluded from the situational distribution seen in Table 3. There were complete data for 98.2% (553/563) of the firearm-related offenses, 86.8% of the drug-motivated offenses (489/563), and 98.5% (555/563) of the homicides that involved multiple suspects.

  13. The augmented Dickey–Fuller unit root test indicated that the transformed series were stationary, meaning that the variance in the series was sufficiently stable over time to meet the assumptions of the subsequent ARIMA models (McCleary and Hay 1980).

  14. In order to calculate the percentage change, we used the multiplicative inverse of the natural logarithm, which means we used exponentiation on the raw coefficients and subtracted 1.0. Thus, gang homicides declined by 38.1% (0.681−1.0 = −0.381) and non-gang homicides declined by 8.6% (0.913−1.0 = −0.086) following the IVRP intervention.

  15. Again, the use of a one-tailed distribution when assessing the differences between ARIMA coefficients had been performed in prior research (Simpson et al. 2006).

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Authors and Affiliations

  1. Center for the Study of Crime, Delinquency, and Corrections, Southern Illinois University, 1000 Faner Drive, MC 4504, Carbondale, IL, 62901, USA

    Nicholas Corsaro

  2. Michigan State University, East Lansing, MI, USA

    Edmund F. McGarrell

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  1. Nicholas Corsaro
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  2. Edmund F. McGarrell
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Correspondence to Nicholas Corsaro.

Appendix A

Appendix A

Fig. 2
figure 2

Natural logarithm of the transformed series of gang and non-gang homicides in Indianapolis

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Corsaro, N., McGarrell, E.F. Testing a promising homicide reduction strategy: re-assessing the impact of the Indianapolis “pulling levers” intervention. J Exp Criminol 5, 63–82 (2009). https://doi.org/10.1007/s11292-008-9065-1

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Keywords

  • Autoregressive integrated moving average (ARIMA) time–series analysis
  • Pulling levers
  • Quasi-experimental design
  • Threats to validity

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