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The purpose of this study was to contribute to the evidence base by analysing the characteristics and motives of homicides involving acts of dismemberment.

The current study explored offence, victim and offender characteristics and the motives for 71 homicides involving dismemberment using open source data. All cases included in this study were investigated in the UK between 1970 and 2016. A non-metric multi-dimensional scaling procedure smallest space analysis (SSA) was used to explore the characteristics and motives derived from a content analysis of homicide data sourced online.

A distinction between expressive and instrumental characteristics was observable with three thematic regions identified: instrumental – defensive, instrumental – predatory and expressive – affective. Support was found for previously identified motives for criminal dismemberment, with defensive being the most common motive identified in 63% (N = 45) of the cases.

The implications of the findings are discussed with suggestions made for future research. The findings have practical implications for assisting law enforcement and forensic and clinical practitioners in further understanding offenders who engage in homicidal dismemberment. This includes aiding homicide investigations, in terms of supporting investigators to draw upon offence, victim and offender characteristics and motives for homicides involving acts of dismemberment. Differentiation between cases of dismemberment and understanding of motives also has practical implications for the development of interventions and treatment pathways for homicide offenders who dismember victims.

This study aims to improve our understanding of violence, focusing on the analysis of the relation between socioeconomic factors and homicide rates from 2005 to 2019 in Brazilian capitals.

Multilevel Poisson models were used to estimate the homicide risk in men and women. The response variable was the homicide rate. Fixed effects were estimated for age group, year and gross domestic product (GDP).

The average homicide rate over the 2005–2019 period was 5.83/100,000 and 83.72/100,000 for women and men, respectively. In both sexes, the homicide rates increased over the period. The highest mortality rates were observed in North and Northeastern capitals. The peak homicide rates were 2010–2014, the risk of homicide decreased as age increased, and the capitals with GDP lower than US$5,000 showed a greater homicide rate.

Brazil remains among the countries with the highest risk of homicide, especially in the north and northeast regions, where socioeconomic conditions are more unfavorable. The improvement of socioeconomic conditions may contribute to changing this situation.

The purpose of this paper is to begin to explore whether and how the use of detection avoidance (DA) by offenders leads to a so called “dark figure” of unsolved homicides that have been mis/unclassified.

Australian Coronial data and inquest findings are used to examine how DA impacts on determining homicide, and cases remaining unsolved.

Results show DA behaviours perpetrated by offenders may be catalysed by other challenges, and may lead to homicides being mis/unclassified and unsolved. Findings indicate there is a small dark figure of mis/unclassified homicides which eventually become known and investigated as homicides in Australia. The number of unsolved homicides may be greater than official data reveals, due to some cases remaining mis/unclassified.

Results are likely to underestimate the prevalence of mis/unclassified homicides due to the invisibility of cases and the difficulty establishing rules to include suspected but unproven homicides. The variable nature and impact of DA behaviours also limits results, along with jurisdictional differences in Coronial data.

This discussion explains DA behaviours impact on determining and investigating homicide and the necessity of future research.

Mis/unclassified homicides as unsolved homicides have not been discussed previously. This discussion is the first to conceptualise mis/unclassified homicides as a dark figure of unsolved cases, and the first to attempt to gauge the problem.

The purpose of this article is to improve the use of evidence-based practice and research utilization in the offender profiling process. The use of offender profiling has been met with increasing resistance given its exaggerated accuracy. The “Investigative Journalist/Expert Field Micro Task Force” model, a collaborative method that incorporates offender profiling and is designed to address unresolved serial homicides, is introduced and evaluated alongside recommendations on attaining adherence.

The model was field tested in 17 instances. The measures used by the Federal Bureau of Investigation to gauge the usefulness of their case consultations, whether their input helped catch the offender, offer new leads, move the case forward, provide new avenues or give new ideas, were used to evaluate the model.

The model established likely patterns of serial murder activity among strangulations of women in Chicago, Cleveland, and Panama and resulted in convictions of suspects in Louisiana and Kansas City. This model is valuable when used to parse modern-day offenders from those who committed unresolved homicides as the latter display different behaviors that can make investigations difficult endeavors. Results from the field tests mirror those from the literature in that profiling alone did not result in the capture of serial killers. Instead, profiling was used in conjunction with other efforts and mainly as a means to keep the investigation moving forward.

Unresolved homicides are at a point of crisis and represent a significant but largely unaddressed societal problem. The success of this model may compel law enforcement to restore faith in offender profiling.

The study aims to examine the effect of detective experience on the likelihood of clearing a homicide, while controlling for additional extralegal and case/investigative characteristics.

This study uses homicide and policing data collected from case files in a mid-sized US city. Detective experience is measured in multiple ways. Analytical models include extralegal variables, case characteristics, and proxies of investigative quality as controls. The study uses logistic regression with a dichotomous clearance outcome.

The results suggest a robust and significant inverse relationship between the years spent as a homicide detective and the likelihood of case closure. However, years of experience with the department overall has a significant and positive relationship to clearance. Investigation-related variables and case characteristics contribute more to model explanatory power than extralegal factors.

The potential role of experience has not been fully explored, with contradictory findings over time. This work builds on previous research to highlight the potential role of experience in clearing cases, while questioning previous assumptions tied to the belief that more experience improves investigative outcomes.

Crime linkage analysis (CLA) can be applied in the police investigation-phase to sift through a database to find behaviorally similar cases to the one under investigation and in the trial-phase to try to prove that the perpetrator of two or more offences is the same, by showing similarity and distinctiveness in the offences. Lately, research has moved toward more naturalistic settings, analyzing data sets that are as similar to actual crime databases as possible. One such step has been to include one-off offences in the data sets, but this has not yet been done with homicide. The purpose of this paper is to investigate how linking accuracy of serial homicide is affected as a function of added hard-to-solve one-off offences.

A sample (N = 117–1160) of Italian serial homicides (n = 116) and hard-to-solve one-off homicides (n = 1–1044, simulated from 45 cases) was analyzed using a Bayesian approach to identify series membership, and a case by case comparison of similarity using Jaccard’s coefficient. Linking accuracy was evaluated using receiver operating characteristics and by examining the sensitivity and specificity of the model.

After an initial dip in linking accuracy (as measured by the AUC), the accuracy increased as more one-offs were added to the data. While adding one-offs made it easier to identify correct series (increased sensitivity), there was an increase in false positives (decreased specificity) in the linkage decisions. When rank ordering cases according to similarity, linkage accuracy was affected negatively as a function of added non-serial cases.

While using a more natural data set, in terms of adding a significant portion of non-serial homicides into the mix, does introduce error into the linkage decision, the authors conclude that taken overall, the findings still support the validity of CLA in practice.

This is the first crime linkage study on homicide to investigate how linking accuracy is affected as a function of non-serial cases being introduced into the data.

In England and Wales, on average one child every week is a victim of homicide. The purpose of this paper is to explore whether different victim-risk profiles and suspect variables can be differentiated for specific victim ages.

This paper presents a preliminary analysis of more than 1,000 child homicides committed in England and Wales between 1996 and 2013, from data provided through the Homicide Index. Statistical techniques such as cluster analysis were used to identify specific victim-risk profiles and to analyse suspect variables according to the age of victim.

The findings present a clearer picture of the risk-age relationship in child homicide, whereby several specific risk profiles are identified for specific child ages, comprised of crime variables including; likely victim and suspect demographics, the most likely circumstances of the homicide and methods of killing. Using similar techniques, a number of tentative clusters of suspects implicated in child homicide are also described and analysed, with suggestions of further analysis that might prove of value.

The practical implications cannot be understated. For those professionals working in the fields of child protection and criminal investigation the identification of risk profiles promises to provide a back-cloth with which to practice when confronted with complex and distressing child homicide scenarios. This research promises most to those currently training in related professions.

Although the statistical level of risk has been linked with the age of a child (with younger children being most vulnerable to killing by a parent or step-parent and older children most vulnerable to killing by acquaintances and strangers), extant research is yet to progress beyond the identification of broad age-risk categories. The paper concludes with a discussion of the likely implications for those charged with reducing and investigating child homicide and outlines the possibility of future research.

Clearance rates for nonfatal shootings, especially cases involving gang- and drug-related violence, are disturbingly low in many US cities. Using data from a previously completed project in Boston, we explore the prospects for improving gang/drug nonfatal shooting cases by investing the same investigative effort found in similar gang/drug gun murder cases.

Our analyses primarily focus on a sample of 231 nonfatal shootings that occurred in Boston from 2010 to 2014. Logistic regressions are first used to analyze differences in the likelihood of case clearance for gang/drug nonfatal shooting cases relative to other nonfatal shooting cases. Independent samples t-tests are then used to compare the investigative characteristics of these two different kinds of nonfatal shootings. Next, independent samples t-tests are used to compare the investigation of gang/drug gun assaults relative to the investigation of very similar gang/drug gun homicides.

Results demonstrate that the odds of clearing gang/drug nonfatal shootings are 77.2% less likely relative to the odds of clearing nonfatal shootings resulting from other circumstances. This stark difference in clearance rates is not driven by diminished investigative effort, but investigative effort does matter. Relative to gang/drug gun assaults, gang/drug gun homicides have much higher clearance rates that are the result of greater investigative resources and effort that produces significantly more witnesses and evidence, and generate more forensic tests and follow-up investigative actions.

Gang- and drug-related violence generates a bulk of urban nonfatal shootings. Low clearance rates for nonfatal shootings undermine police efforts to hold offenders accountable, disrupt cycles of gun violence, and provide justice to victims. Police should make investments to improve investigative effort such as handling these cases with the same vigor as homicide cases.

The purpose of this paper is to investigate the relationship between rates of firearm homicide in New York State (NYS) and indicators of access to and quality of healthcare from 2011 to 2017.

Utilizing data from the NYS Division of Criminal Justice Services Uniform Crime Reporting Supplemental Homicide Reports and Robert Wood Johnson Foundation County Health Rankings Program, a county-level ecologic study was conducted, descriptive statistics provided and multivariable analyses conducted to determine the associations between critical indicators of county health and firearm homicide.

The majority of firearm homicide victims (n=2,619) were young, Black, men and the highest rates of firearm homicide were situated in urban centers. Subgroup analyses excluding large urban centers and controlling for key demographics illustrated that those counties with lower rates of clinicians were significantly associated with higher rates of firearm homicide.

Despite challenges integrating two large data sets, the present findings were able to illustrate the critical relationship between access to healthcare and prevalence of firearm homicide.

The results of this study reinforce the importance of access to primary healthcare services and its relationship to critical health outcomes.

In urban settings, firearm homicides disproportionately impact young Black men, who are among the least likely to have access to healthcare. In more rural areas, access to healthcare is related directly to improved health outcomes, including reduced rates of firearm homicides.

This is the first study to explore and subsequently establish the relationship between indicators of community health and firearm homicide in NYS.

Cohen (1998) describes a study showing that, in the US, regionally distributed culture controls the direction of the relationship between social disorganization and homicide rates. In the South and West, where, according to the Nisbett‐Cohen theory, there is a “culture of honor”, strong community and family bonds increase argumentrelated homicides. Conversely, in the North, where cultural beliefs do not support violence in response to insults, strong social bonds decrease argument‐related homicides. A reanalysis shows that Cohen’s results are due to a few counties with atypical values that heavily influence the slope estimates. The data do not provide support for the Nisbett‐Cohen thesis that regional patterns in US homicide can be attributed to a culture of honor.