Mass Killings in the United States from 2006 to 2013: Social Contagion or Random Clusters?

Lankford, Adam; Tomek, Sara

doi:10.1111/sltb.12366

Cited by 26 publications

(30 citation statements)

References 23 publications

(38 reference statements)

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“…Consistent with the growing literature, we define a mass public shooting as an incident of targeted violence where an offender has killed or unequivocally attempted to kill four or more victims on a public stage (e.g., workplace, schools, parks, and businesses) in one or multiple closely related locations within a 24-h period (2)(3)(4)(5)(6)(7)(9)(10)(11)(12). Both familicides and felony-related mass shootings are excluded from this operationalization (12).…”

Section: Definitionsmentioning

confidence: 99%

“…Consistent with most studies on the subject (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(14)(15)(16)(17)(18)(19), we employed an open-source data collection strategy to identify and collect information on both failed and successful mass public shootings that occurred in the United States from 1966 to 2017. Open-source data are information that is open to the public (20).…”

Section: Data Collection Strategymentioning

confidence: 99%

See 1 more Smart Citation

Disaggregating Mass Public Shootings: A Comparative Analysis of Disgruntled Employee, School, Ideologically motivated, and Rampage Shooters

Capellan

Johnson

Porter

et al. 2018

Journal of Forensic Sciences

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This study compares the demographic, background, motivation, and pre‐event and event‐level behaviors across four types of mass public shooters: disgruntled employee, school, ideologically motivated, and rampage offenders. Using a database containing detailed information on 318 mass public shootings that occurred in the United States between 1966 and 2017, we find systematic differences in the characteristics, motivations, target selection, planning, and incident‐level behaviors among these offenders. The results show that ideologically motivated shooters to be the most patient, and methodical, and as a result the most lethal. Conversely, disgruntled employees, who are driven by revenge, tend to have little time to plan and consequently are the least lethal shooters. These, among other differences, underscore the need for prevention strategies and policies to be tailored to specific types of offenders. Furthermore, the results also highlight commonalities across offender type, suggesting that the social and psychological pathways to violence are universal across offenders.

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Section: Definitionsmentioning

confidence: 99%

Section: Data Collection Strategymentioning

confidence: 99%

Disaggregating Mass Public Shootings: A Comparative Analysis of Disgruntled Employee, School, Ideologically motivated, and Rampage Shooters

Capellan

Johnson

Porter

et al. 2018

Journal of Forensic Sciences

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“…For instance, Kissner () found that the occurrence of a mass public shooting significantly increased the hazard of experiencing another mass public shooting for 2 weeks. However, Lankford and Tomek () found no evidence of such a short‐term contagion effect. Capellan () did not find evidence of contagion; rather, he found that the occurrence of a mass public shooting has a deterrent effect on future ones.…”

Section: Discussionmentioning

confidence: 99%

Change and stability in offender, behaviours, and incident‐level characteristics of mass public shootings in the United States, 1984–2015

Capellan

Gomez

2017

Journal Invest Psychology

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For the last 40 years, the general profile of mass public shooters has enjoyed enduring consensus by experts, and as a result, it has remained static over this time. However, a recent string of mass public shootings perpetrated by “atypical” offenders bring into question the stability of the characteristics, motivations, and methods employed by these offenders. The goal of this study is to examine the stability and change of these characteristics and behaviors over the last 32 years (1984–2015). Using an open‐source database, this study compares mass public shootings in 2000–2015 time period to the attacks committed in 1984–1999. The results illustrate not only sharp increase in number of mass public shootings in the last 16 years but also a significant growth in the racial heterogeneity and background characteristics of these offenders, clearly marking a departure from the general accepted profile of mass public shooters and mass murderers. The results also point to key characteristics, and behaviors that have remained static during the analysis time. Additionally, this study explores the implications these changes and stability on crime prevention strategies, as well as strategies to mitigate the lethality of these attacks.

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“…As an example of the advantages of unbinned likelihood methods in increasing the statistical power of an analysis, here we compare and contrast two recent analyses of contagion in mass killings in America, both of which were based on exactly the same data, but used different methodology. One concluded that there was evidence of contagion in mass killings [ 6 ], while the later analysis contradicted this claim [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…Using the same data presented in Towers et al (2015), Lankford & Tomek (2017) published a subsequent analysis that claimed to find no significant evidence of contagion in mass killings [ 7 ]. They primarily based their conclusion on a simple analysis of how many events occurred within 14 days of a prior event, under the null hypothesis assumption that the data were randomly Uniformly distributed in time.…”

Section: Introductionmentioning

confidence: 99%

Detecting the contagion effect in mass killings; a constructive example of the statistical advantages of unbinned likelihood methods

2018

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BackgroundWhen attempting to statistically distinguish between a null and an alternative hypothesis, many researchers in the life and social sciences turn to binned statistical analysis methods, or methods that are simply based on the moments of a distribution (such as the mean, and variance). These methods have the advantage of simplicity of implementation, and simplicity of explanation.However, when null and alternative hypotheses manifest themselves in subtle differences in patterns in the data, binned analysis methods may be insensitive to these differences, and researchers may erroneously fail to reject the null hypothesis when in fact more sensitive statistical analysis methods might produce a different result when the null hypothesis is actually false.Here, with a focus on two recent conflicting studies of contagion in mass killings as instructive examples, we discuss how the use of unbinned likelihood methods makes optimal use of the information in the data; a fact that has been long known in statistical theory, but perhaps is not as widely appreciated amongst general researchers in the life and social sciences.MethodsIn 2015, Towers et al published a paper that quantified the long-suspected contagion effect in mass killings. However, in 2017, Lankford & Tomek subsequently published a paper, based upon the same data, that claimed to contradict the results of the earlier study. The former used unbinned likelihood methods, and the latter used binned methods, and comparison of distribution moments.Using these analyses, we also discuss how visualization of the data can aid in determination of the most appropriate statistical analysis methods to distinguish between a null and alternate hypothesis. We also discuss the importance of assessment of the robustness of analysis results to methodological assumptions made (for example, arbitrary choices of number of bins and bin widths when using binned methods); an issue that is widely overlooked in the literature, but is critical to analysis reproducibility and robustness.ConclusionsWhen an analysis cannot distinguish between a null and alternate hypothesis, care must be taken to ensure that the analysis methodology itself maximizes the use of information in the data that can distinguish between the two hypotheses.The use of binned methods by Lankford & Tomek (2017), that examined how many mass killings fell within a 14 day window from a previous mass killing, substantially reduced the sensitivity of their analysis to contagion effects. The unbinned likelihood methods used by Towers et al (2015) did not suffer from this problem.While a binned analysis might be favorable for simplicity and clarity of presentation, unbinned likelihood methods are preferable when effects might be somewhat subtle.

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Mass Killings in the United States from 2006 to 2013: Social Contagion or Random Clusters?

Cited by 26 publications

References 23 publications

Disaggregating Mass Public Shootings: A Comparative Analysis of Disgruntled Employee, School, Ideologically motivated, and Rampage Shooters

Disaggregating Mass Public Shootings: A Comparative Analysis of Disgruntled Employee, School, Ideologically motivated, and Rampage Shooters

Change and stability in offender, behaviours, and incident‐level characteristics of mass public shootings in the United States, 1984–2015

Detecting the contagion effect in mass killings; a constructive example of the statistical advantages of unbinned likelihood methods

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