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Prison and Violent Political Extremism in the United States

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Abstract

Objectives

In the current study we consider the link between imprisonment and post-prison participation in violent political extremism. We examine three research questions: (1) whether spending time in prison increases the post-release risk of engaging in violent acts; (2) whether political extremists who were radicalized in prison are more likely to commit violent acts than political extremists radicalized elsewhere; and (3) whether individuals who were in prison and radicalized there were more likely to engage in post-prison violent extremism compared to individuals who were in prison and did not radicalize there.

Methods

We perform a two-stage analysis where we first preprocess the data using a matching technique to approximate a fully blocked experimental design. Using the matched data, we then calculate the conditional odds ratio for engaging in violent extremism and estimate average treatment effects (ATE) of our outcomes of interest.

Results

Our results show that the effects of imprisonment and prison radicalization increases post-prison violent extremism by 78–187% for the logistic regression analysis, and 24.6–48.53% for the ATE analysis. Both analyses show that when radicalization occurs in the context of prison, the criminogenic effect of imprisonment is doubled.

Conclusions

In support of longstanding arguments that prison plays a major role in the identity and behavior of individuals after their release, we find consistent evidence that the post-prison use of politically motivated violence can be estimated in part by whether perpetrators spent time in prison and whether they were radicalized there.

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Notes

  1. We adopt the FBI (2017) definition of violent extremism as “encouraging, condoning, justifying, or supporting the commission of a violent act to achieve political, ideological, religious, social, or economic goals”.

  2. We adopt the FBI definition of radicalization as “the process by which individuals come to believe their engagement in or facilitation of nonstate violence to achieve social and political change is necessary and justified” (Hunter and Heinke 2011).

  3. A recent report in the New York Times claims that American prisons currently hold 443 convicted terrorists, but the reporters were unable to confirm the locations for two-thirds of the inmates identified (Fairfield and Wallace 2016).

  4. More generally, we know of no U.S. recidivism studies that follow people who have been radicalized in prison.

  5. Individuals could be coded as subscribing to more than one ideology. For a full description of the ideologies and coding rules, see PIRUS (2018, pp. 3–5).

  6. We acknowledge that the time period covered by the data is quite long—in part a feature of the fact that political extremism is a relatively rare event and gathering a large data set requires a long time frame. In general, 98.1% of the cases (662 cases) in the analysis occurred after 1970 and 91.9% (620 cases) after 2000. All cases were coded retrospectively in three waves between 2013 and 2015 using the same criteria for the entire period.

  7. A complete list of both groups is available on request.

  8. The most common reason for eliminating cases during the criteria coding stage was their failure to meet the inclusion requirement that they had radicalized in the United States. While every effort was made to ensure the representativeness of the data, given our reliance on open-sources, we cannot rule out the possibility that our sample is also influenced by news reporting trends. For more details on the data and the data coding process, see PIRUS (2018) and Jensen et al. (2015).

  9. Although the PIRUS team continually updates and revises the data as new information is discovered, to this point in time we have not had sufficient resources to double code the full data set.

  10. While there is still no generally accepted tool for measuring radicalization (cf., Borum 2011; Hamm 2008; Neumann 2013) our data seeks sources that indicate that while in prison the perpetrators demonstrated either through their attitudes or behavior a growing commitment to ideologically motivated illegal action.

  11. After performing coarsened exact matching, the sample size for H3 was even smaller: 36 out of 103 cases (35%) were pruned by the CEM algorithm, dropping the sample to 67 cases.

  12. For this analysis, we assumed that if there was no mention of mental illness in court documents or media accounts, then none existed—a decision supported by earlier research (LaFree et al. 2018).

  13. The regression-adjustment approach makes use of the potential outcome means to estimate the ATE; while the inverse probability weighting approach uses the propensity score.

  14. For the percentage change coefficient and standard error, we made use of the command “nlcom,” calculated with the delta method.

  15. We also performed an additional robustness check by using a multiple imputation method called Amelia II (Honaker et al. 2011) to ensure that the estimated likelihood of engaging in violent extremism is not being driven by our handling of missing data. We generated 5 complete data sets using Amelia II before running CEM. After establishing the validity of the 5 imputed data sets derived from Amelia II, we next used them to quantify the strength of association between violent extremism, imprisonment and radicalization. The results, available on request, were substantively identical to those reported here.

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  1. University of Maryland, College Park, USA

    Gary LaFree, Bo Jiang & Lauren C. Porter

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  1. Gary LaFree
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Correspondence to Gary LaFree.

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LaFree, G., Jiang, B. & Porter, L.C. Prison and Violent Political Extremism in the United States. J Quant Criminol 36, 473–498 (2020). https://doi.org/10.1007/s10940-019-09412-1

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