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JournalISSN: 2193-7680

Crime Science 

Springer Nature
About: Crime Science is an academic journal published by Springer Nature. The journal publishes majorly in the area(s): Crime prevention & Poison control. It has an ISSN identifier of 2193-7680. It is also open access. Over the lifetime, 211 publications have been published receiving 4484 citations.


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Journal ArticleDOI
TL;DR: How the frequency of common types of crime changed in 16 large cities across the United States in the early months of 2020 is used to make suggestions for future research into the relationships between the coronavirus pandemic and different crimes.
Abstract: The COVID-19 pandemic led to substantial changes in the daily activities of millions of Americans, with many businesses and schools closed, public events cancelled and states introducing stay-at-home orders. This article used police-recorded open crime data to understand how the frequency of common types of crime changed in 16 large cities across the United States in the early months of 2020. Seasonal auto-regressive integrated moving average (SARIMA) models of crime in previous years were used to forecast the expected frequency of crime in 2020 in the absence of the pandemic. The forecasts from these models were then compared to the actual frequency of crime during the early months of the pandemic. There were no significant changes in the frequency of serious assaults in public or (contrary to the concerns of policy makers) any change to the frequency of serious assaults in residences. In some cities, there were reductions in residential burglary but little change in non-residential burglary. Thefts of motor vehicles decreased in some cities while there were diverging patterns of thefts from motor vehicles. These results are used to make suggestions for future research into the relationships between the coronavirus pandemic and different crimes.

184 citations

Journal ArticleDOI
TL;DR: In this paper, a crime script approach is used to understand what kind of criminal opportunities the Internet offers for conducting wildlife trafficking and how these opportunities affect the organization of this transit crime, as concerns both the carrying out of the criminal activity and the patterns of relations in and among criminal networks.
Abstract: There is a broad consensus that the Internet has greatly expanded possibilities for traditional transit crimes such as wildlife trafficking. However, the extent to which the Internet is exploited by criminals to carry out these types of activities and the way in which it has changed how these crimes are carried out remains under-investigated. Based on interviews and investigative cases, this paper shows the possibilities offered by a crime script approach for understanding what kind of criminal opportunities the Internet offers for conducting wildlife trafficking and how these opportunities affect the organization of this transit crime, as concerns both the carrying out of the criminal activity and the patterns of relations in and among criminal networks. It highlights how Internet-mediated wildlife trafficking is a hybrid market that combines the traditional social and economic opportunity structure with that provided by the Internet.

158 citations

Journal ArticleDOI
TL;DR: It is important that analysts use the most accurate methods for temporal distribution approximation to ensure any resource decisions made on the basis of peak times are reliable.
Abstract: To test the accuracy of various methods previously proposed (and one new method) to estimate offence times where the actual time of the event is not known. For 303 thefts of pedal cycles from railway stations, the actual offence time was determined from closed-circuit television and the resulting temporal distribution compared against commonly-used estimated distributions using circular statistics and analysis of residuals. Aoristic analysis and allocation of a random time to each offence allow accurate estimation of peak offence times. Commonly-used deterministic methods were found to be inaccurate and to produce misleading results. It is important that analysts use the most accurate methods for temporal distribution approximation to ensure any resource decisions made on the basis of peak times are reliable.

114 citations

Journal ArticleDOI
TL;DR: It is theorised that crime rate changes were primarily caused by those in mobility, suggesting a mobility theory of crime change in the pandemic.
Abstract: Governments around the world restricted movement of people, using social distancing and lockdowns, to help stem the global coronavirus (COVID-19) pandemic. We examine crime effects for one UK police force area in comparison to 5-year averages. There is variation in the onset of change by crime type, some declining from the WHO ‘global pandemic’ announcement of 11 March, others later. By 1 week after the 23 March lockdown, all recorded crime had declined 41%, with variation: shoplifting (− 62%), theft (− 52%), domestic abuse (− 45%), theft from vehicle (− 43%), assault (− 36%), burglary dwelling (− 25%) and burglary non-dwelling (− 25%). We use Google Covid-19 Community Mobility Reports to calculate the mobility elasticity of crime for four crime types, finding shoplifting and other theft inelastic but responsive to reduced retail sector mobility (MEC = 0.84, 0.71 respectively), burglary dwelling elastic to increases in residential area mobility (− 1), with assault inelastic but responsive to reduced workplace mobility (0.56). We theorise that crime rate changes were primarily caused by those in mobility, suggesting a mobility theory of crime change in the pandemic. We identify implications for crime theory, policy and future research.

112 citations

Journal ArticleDOI
TL;DR: In this paper, the authors make use of crowd-sourced data to estimate the population at risk for mobile crimes such as street robbery, which can be used to estimate crime rate significance in both space and time.
Abstract: It is well known that, due to that inherent differences in their underlying causal mechanisms, different types of crime will have variable impacts on different groups of people. Furthermore, the locations of vulnerable groups of people are highly temporally dynamic. Hence an accurate estimate of the true population at risk in a given place and time is vital for reliable crime rate calculation and hotspot generation. However, the choice of denominator is fraught with difficulty because data describing popular movements, rather than simply residential location, are limited. This research will make use of new ‘crowd-sourced’ data in an attempt to create more accurate estimates of the population at risk for mobile crimes such as street robbery. Importantly, these data are both spatially and temporally referenced and can therefore be used to estimate crime rate significance in both space and time. Spatio-temporal cluster hunting techniques will be used to identify crime hotspots that are significant given the size of the ambient population in the area at the time.

98 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202313
202223
202127
202026
201914
201820