By Rick Dierenfeldt, Grant Drawve, Joshua May, Ellee Jackson

A growing body of literature has explored the ‘life course’ of crime guns, with a particular focus on the time between the initial point of sale of firearms and their eventual recovery by police following a crime. We contend that this examination is incomplete, with limited consideration given to the period between a firearm's first known use in a criminal offense and its recovery by police—which we refer to as time in crime. Increased understanding of this time frame is important given that crime guns are frequently recirculated among criminally involved groups and the recent finding that time in circulation following first known use in a crime is a significant predictor of multiple uses of crime guns. We add to the literature through the application of negative binomial regression to a sample of 310 crime guns used in offenses in a city in the Southeastern United States to examine how neighborhood context and initial incident characteristics influence the number of days that firearms remain in circulation after their first known use in a crime. We found that increased levels of concentrated disadvantage and gang involvement during the original incident correspond with significant increases in time in crime, while increased levels of residential stability and the ability of police to identify suspects are linked with more rapid recovery of crime guns. Notably, these findings hold even after the inclusion of popular time-to-crime covariates, including firearm quality, caliber, and status as a stolen gun. 

Journal of Criminal Justice Volume: 49 Dated: July 2024 Pages: 723-744

By Armita Adily, George Karystianis and Tony Butler

Police attend numerous family and domestic violence (FDV) related events each year and record details of these events as both structured data and unstructured free-text narratives. These descriptive narratives include information about the types of abuse (eg physical, emotional, financial) and the injuries sustained by victims. However, this information is not used in research. In this paper we demonstrate the application of an automated text mining method to identify abuse types and victim injuries in a large corpus of NSW Police Force FDV event narratives (492,393) recorded between January 2005 and December 2016. Specific types of abuse and victim injuries were identified in 71.3 percent and 35.9 percent of FDV event narratives respectively. The most commonly identified abuse types mentioned in the narratives were non-physical (55.4%). Our study supports the application of text mining for use in FDV research and monitoring.

Trends & issues in crime and criminal justice no. 630. Canberra: Australian Institute of Criminology. 2021. 12p.

By Armita Adily, George Karystianis and Tony Butler

In this paper, we describe the feasibility of using a text-mining method to generate new insights relating to family and domestic violence (FDV) from free-text police event narratives. Despite the rich descriptive content of the event narratives regarding the context and individuals involved in FDV events, the police narratives are untapped as a source of data to generate research evidence. We used text mining to automatically identify mentions of mental disorders for both persons of interest (POIs) and victims of FDV in 492,393 police event narratives created between January 2005 and December 2016. Mentions of mental disorders for both POIs and victims were identified in nearly 15.8 percent (77,995) of all FDV events. Of all events with mentions of mental disorder, 76.9 percent (60,032) and 16.4 percent (12,852) were related to either POIs or victims, respectively. The next step will be to use actual diagnoses from NSW Health records to determine concordance between the two data sources. We will also use text mining to extract information about the context of FDV events among key at-risk groups.

Trends & issues in crime and criminal justice no. 629. Canberra: Australian Institute of Criminology. 2021. 16p.

By Ben Grunwald and Jeffrey Fagan

In 2000, the Supreme Court held in Illinois v. Wardlow that a suspect’s presence in a “high-crime area” is relevant in determining whether an officer has reasonable suspicion to conduct an investigative stop. Despite the importance of the decision, the Court provided no guidance about what that standard means, and over fifteen years later, we still have no idea how police officers understand and apply it in practice. This Article conducts the first empirical analysis of Wardlow by examining data on over two million investigative stops conducted by the New York Police Department from 2007 to 2012. Our results suggest that Wardlow may have been wrongly decided. Specifically, we find evidence that officers often assess whether areas are high crime using a very broad geographic lens; that they call almost every block in the city high crime; that their assessments of whether an area is high crime are nearly uncorrelated with actual crime rates; that the suspect’s race predicts whether an officer calls an area high crime as well as the actual crime rate; that the racial composition of the area and the identity of the officer are stronger predictors of whether an officer calls an area high crime than the crime rate itself; and that stops are less or as likely to result in the detection of contraband when an officer invokes high-crime area as a basis of a stop. We conclude with several policy proposals for courts, police departments, and scholars to help address these problems in the doctrine.

California Law Review 345-404 (2019

By Peter Leasure and Hunter M. Boehme

Efforts such as evidence-based policing and data-driven policing have argued for the use of research and data analysis in the decision-making process for law enforcement agencies. The current study sought to examine the importance of data collection and data analysis across Ohio law enforcement agencies and whether Ohio law enforcement agencies are interested in improving their data collection and data analysis procedures. The results showed that the majority of respondents strongly agreed or somewhat agreed that data collection and data analysis are key components of their decision-making process, and that their agency could benefit from improved data collection and data analysis procedures. However, a nontrivial number of respondents strongly disagreed or somewhat disagreed that data collection and data analysis are key components of their decision-making process, and that their agency could benefit from improved data collection and data analysis procedures. Recommendations informed by these results are discussed in detail.

Drug Enforcement and Policy Center. July 2023, 8pg

By Peter Leasure and Hunter M. Boehme

This study examined whether public perceptions of police traffic stops and searches varied when participants were randomly assigned to receive various traffic stop and search statistics derived from research. We utilized an experimental information provision survey sent to head of households in South Carolina with an associated email address. Respondents were randomly assigned to one of three conditions: 1) a condition where respondents were presented statistics on contraband hit rates (i.e., rate at which contraband is found during a stop), 2) a condition where respondents were presented statistics on racial disparities in traffic stops, or 3) the control condition. Results from roughly 4,600 respondents indicated that research on traffic stops and searches could impact public opinion regarding whether the police should conduct more stops and searches. Statistically significant differences were found with the contraband versus the racial disparity conditions and with the racial disparity versus control conditions. Looking at the overall probabilities (without regard to the p-values for the differences), respondents who received the racial disparity condition were the least likely to agree that police should conduct more traffic stops and searches, while respondents who received the contraband condition were most likely to agree that police should conduct more traffic stops and searches. However, it should be noted that probabilities for all conditions ranged from approximately 32% to 38%, meaning that most respondents did not agree that more traffic stops and searches should be conducted.

Drug Enforcement and Policy Center. February 2024, 20pg