scholarly journals The Spatial and Social Patterning of Property and Violent Crime in Toronto Neighbourhoods: A Spatial-Quantitative Approach

2019 ◽  
Vol 8 (1) ◽  
pp. 51 ◽  
Author(s):  
Lu Wang ◽  
Gabby Lee ◽  
Ian Williams
Keyword(s):  
Violent Crime ◽  
Property Crime ◽  
Criminal Activity ◽  
Ordinary Least Squares ◽  
Crime Rates ◽  
Individual Characteristics ◽  
Suitable Model ◽  
Similar Distribution ◽  
Wide Range ◽  
The City

Criminal activities are often unevenly distributed over space. The literature shows that the occurrence of crime is frequently concentrated in particular neighbourhoods and is related to a variety of socioeconomic and crime opportunity factors. This study explores the broad patterning of property and violent crime among different socio-economic stratums and across space by examining the neighbourhood socioeconomic conditions and individual characteristics of offenders associated with crime in the city of Toronto, which consists of 140 neighbourhoods. Despite being the largest urban centre in Canada, with a fast-growing population, Toronto is under-studied in crime analysis from a spatial perspective. In this study, both property and violent crime data sets from the years 2014 to 2016 and census-based Ontario-Marginalisation index are analysed using spatial and quantitative methods. Spatial techniques such as Local Moran’s I are applied to analyse the spatial distribution of criminal activity while accounting for spatial autocorrelation. Distance-to-crime is measured to explore the spatial behaviour of criminal activity. Ordinary Least Squares (OLS) linear regression is conducted to explore the ways in which individual and neighbourhood demographic characteristics relate to crime rates at the neighbourhood level. Geographically Weighted Regression (GWR) is used to further our understanding of the spatially varying relationships between crime and the independent variables included in the OLS model. Property and violent crime across the three years of the study show a similar distribution of significant crime hot spots in the core, northwest, and east end of the city. The OLS model indicates offender-related demographics (i.e., age, marital status) to be a significant predictor of both types of crime, but in different ways. Neighbourhood contextual variables are measured by the four dimensions of the Ontario-Marginalisation Index. They are significantly associated with violent and property crime in different ways. The GWR is a more suitable model to explain the variations in observed property crime rates across different neighbourhoods. It also identifies spatial non-stationarity in relationships. The study provides implications for crime prevention and security through an enhanced understanding of crime patterns and factors. It points to the need for safe neighbourhoods, to be built not only by the law enforcement sector but by a wide range of social and economic sectors and services.

scholarly journals INVESTIGATING THE INFLUENCE OF TREE COVERAGE ON PROPERTY CRIME: A CASE STUDY IN THE CITY OF VANCOUVER, BRITISH COLUMBIA, CANADA

2016 ◽  
Vol XLI-B2 ◽  
pp. 695-702 ◽  
Author(s):  
Yifei Chen ◽  
Yuenan Li ◽  
Jonathan Li
Keyword(s):  
Property Crime ◽  
Ordinary Least Squares ◽  
Crime Rates ◽  
Airborne Lidar ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Tree Coverage ◽  
Sectional Analysis ◽  
The Relationship ◽  
The City

With the development of Geographic Information Systems (GIS), crime mapping becomes an effective approach to investigate the spatial pattern of crime in a defined area. Understanding the relationship between crime and its surrounding environment can reveal possible strategies that can reduce crime in a neighbourhood. The relationship between vegetation density and crime has been under debate for a long time. This research is conducted to investigate the impacts of tree coverage on property crime in the City of Vancouver. High spatial resolution airborne LiDAR data collected in 2013 was used for the extraction of tree covered area for cross-sectional analysis. The independent variables were put into Ordinary Least-Squares (OLS) regression, Spatial Lag regression, and Geographically Weighted Regression (GWR) models to examine their influences on property crime rates. According to the results, the cross-sectional analysis demonstrated statistical evidences that property crime rates had negative correlations with tree coverage, with greater influences occurred around Downtown Vancouver.

scholarly journals INVESTIGATING THE INFLUENCE OF TREE COVERAGE ON PROPERTY CRIME: A CASE STUDY IN THE CITY OF VANCOUVER, BRITISH COLUMBIA, CANADA

2016 ◽  
Vol XLI-B2 ◽  
pp. 695-702
Author(s):  
Yifei Chen ◽  
Yuenan Li ◽  
Jonathan Li
Keyword(s):  
Property Crime ◽  
Ordinary Least Squares ◽  
Crime Rates ◽  
Airborne Lidar ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Tree Coverage ◽  
Sectional Analysis ◽  
The Relationship ◽  
The City

With the development of Geographic Information Systems (GIS), crime mapping becomes an effective approach to investigate the spatial pattern of crime in a defined area. Understanding the relationship between crime and its surrounding environment can reveal possible strategies that can reduce crime in a neighbourhood. The relationship between vegetation density and crime has been under debate for a long time. This research is conducted to investigate the impacts of tree coverage on property crime in the City of Vancouver. High spatial resolution airborne LiDAR data collected in 2013 was used for the extraction of tree covered area for cross-sectional analysis. The independent variables were put into Ordinary Least-Squares (OLS) regression, Spatial Lag regression, and Geographically Weighted Regression (GWR) models to examine their influences on property crime rates. According to the results, the cross-sectional analysis demonstrated statistical evidences that property crime rates had negative correlations with tree coverage, with greater influences occurred around Downtown Vancouver.

Is a Decentralized Police Organization a Better Option in a Modern Democratic Society? A Case Study From South Korea

2021 ◽  
pp. 109861112110420
Author(s):  
Sungil Han ◽  
Jennifer LaPrade ◽  
EuiGab Hwang
Keyword(s):  
South Korea ◽  
Violent Crime ◽  
Fear Of Crime ◽  
Police Department ◽  
Property Crime ◽  
Interrupted Time Series ◽  
Crime Rates ◽  
Interrupted Time Series Analysis ◽  
Clearance Rates ◽  
Crime Clearance

While western countries have had a decentralized policing model for many years, some countries, such as South Korea, still employ a centralized, national police department. Responding to calls for reform, South Korea launched a pilot program and implemented a more decentralized policing structure in Jeju Island in 2006. This study adds to the policing literature by offering the empirical comparison of a region before and after decentralization of a police department. This study will examine the intervention effects of police decentralization in Jeju, specifically related to crime rates, crime clearance rates, victimization, trust in police, and fear of crime. Using propensity score matching and interrupted time series analysis, this study found that the decentralized policing intervention significantly reduced total crime, violent crime rates, and property crime rates that lasted throughout the intervention period, while improving crime clearance rates for violent crime, as well as reduced fear of crime among residents.

scholarly journals Crime and individual and neighbourhood sociodemographic characteristics in the City of Toronto

2021 ◽  
Author(s):  
Gabby Lee
Keyword(s):  
Low Income ◽  
Demographic Characteristics ◽  
Individual Characteristics ◽  
Least Square ◽  
Geographical Information ◽  
Similar Distribution ◽  
Violent Crimes ◽  
Density Mapping ◽  
Qualitative Approaches ◽  
The City

The overall objective of this study is to determine what neighbourhood and offender-related demographic characteristics impact crime rates in the City of Toronto. By doing so, quantitative and qualitative approaches were implemented in this study. This study includes both property and violent crime datasets from 2014-2016 and census related information from the 2011 Canadian Census. The advancing techniques of Geographical Information System (GIS) has been explored and applied to achieve a thorough understanding of crime occurrences and patterns in the city. Hotspot and Kernel Density mapping were applied to analyze the spatial distribution of crime occurrences and account for spatial autocorrelation. Findings revealed that property and violent crimes across the three years of study showed similar distribution of significant hotspots in the core, Northwest, and East end of the city. An Ordinary Least Square (OLS) regression was conducted to examine the ways in which individual and neighbourhood demographic characteristics predict the effects of crime occurrences. The OLS model was a good predictor for offender-related demographics as opposed to neighbourhood level demographics at the 0.05 significant level. These findings revealed that social disadvantaged neighbourhood characteristics such as low income, unemployment, low education, female lone parent were poor predictors of property crimes but good predictors for violent crimes. However, individual characteristics were.

Club convergence of crime rates in the United States of America

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kolawole Ogundari
Keyword(s):  
Violent Crime ◽  
Property Crime ◽  
The United States ◽  
Crime Rates ◽  
Community Level ◽  
Club Convergence ◽  
Content Type ◽  
Level Data ◽  
Convergence Club ◽  
Over Time

Purpose The cyclical behavior of US crime rates reflects the dynamics of crime in the country. This paper aims to investigate the US's club convergence of crime rates to provide insights into whether the crime rates increased or decreased over time. The paper also analyzes the factors influencing the probability of states converging to a particular convergence club of crime. Design/methodology/approach The analysis is based on balanced panel data from all 50 states and the district of Columbia on violent and property crime rates covering 1976–2019. This yields a cross-state panel of 2,244 observations with 55 time periods and 51 groups. In addition, the author used a club clustering procedure to investigate the convergence hypothesis in the study. Findings The empirical results support population convergence of violent crime rates. However, the evidence that supports population convergence of property crime rates in the study is not found. Further analysis using the club clustering procedure shows that property crime rates converge into three clubs. The existence of club convergence in property crime rates means that the variation in the property crime rates tends to narrow among the states within each of the clubs identified in the study. Analysis based on an ordered probit model identifies economic, geographic and human capital factors that significantly drive the state's convergence club membership. Practical implications The central policy insight from these results is that crime rates grow slowly over time, as evident by the convergence of violent crime and club convergence of property crime in the study. Moreover, the existence of club convergence of property crime is an indication that policies to mitigate property crime might need to target states within each club. This includes the efforts to use state rather than national crime-fighting policies. Social implications As crimes are committed at the local level, this study's primary limitation is the lack of community-level data on crime and other factors considered. Analysis based on community-level data might provide a better representation of crime dynamics. However, the author hopes to consider this as less aggregated data are available to use in future research. Originality/value The paper provides new insights into the convergence of crime rates using the club convergence procedure in the USA. This is considered an improvement to the methods used in the previous studies.

Exploring Spatial Patterns of Property Crime Risks in Changchun, China

2013 ◽  
Vol 4 (3) ◽  
pp. 80-100 ◽  
Author(s):  
Wei Song ◽  
Daqian Liu
Keyword(s):  
Spatial Patterns ◽  
Hot Spots ◽  
Property Crime ◽  
Ordinary Least Squares ◽  
Neighborhood Characteristics ◽  
Risk Areas ◽  
Gwr Model ◽  
The Relationship ◽  
The City ◽  
Crime Risks

Urban crime has increasingly become a major issue for Chinese cities. Using crime data collected at police precincts in 2008, the main aim of this research is to examine the spatial distribution of property crime which accounted for almost 82% of all crimes in the city of Changchun, and analyze the relationship between the spatial patterns of property crime and neighborhood characteristics. Standardized property crime rates (SCR) were applied to assess the relative risk of property crime across the city. Statistically significant clusters of high-risk areas or hot-spots were detected. A global ordinary least squares (OLS) regression model and a geographically weighted regression (GWR) model were calibrated to explore the risk of property crime as a function of contextual neighborhood characteristics. The analytical results show that significant local variations exist in the relationship between the risk of property crime and several neighborhood socioeconomic variables.

The Politics of Refuge: Sanctuary Cities, Crime, and Undocumented Immigration

2017 ◽  
Vol 55 (1) ◽  
pp. 3-40 ◽  
Author(s):  
Benjamin Gonzalez O’Brien ◽  
Loren Collingwood ◽  
Stephen Omar El-Khatib
Keyword(s):  
Property Crime ◽  
Crime Rates ◽  
Undocumented Immigration ◽  
Police Departments ◽  
Potential Benefits ◽  
Key Variables ◽  
Matching Strategy ◽  
Post Hoc ◽  
The City ◽  
Discernible Difference

This article assesses the claim that sanctuary cities—defined as cities that expressly forbid city officials or police departments from inquiring into an individual’s immigration status—are associated with post hoc increases in crime. We employ a causal inference matching strategy to compare similarly situated cities where key variables are the same across the cities except the sanctuary status of the city. We find no statistically discernible difference in violent crime, rape, or property crime rates across the cities. Our findings provide evidence that sanctuary policies have no effect on crime rates, despite narratives to the contrary. The potential benefits of sanctuary cities, such as better incorporation of the undocumented community and cooperation with police, thus have little cost for the cities in question in terms of crime.

Dogs and Crime

2018 ◽  
Vol 26 (1) ◽  
pp. 34-53
Author(s):  
Wes Grooms ◽  
DJ Biddle
Keyword(s):  
Spatial Analysis ◽  
Property Crime ◽  
Comprehensive Analysis ◽  
Crime Rates ◽  
Deterrent Effect ◽  
Academic Press ◽  
Percentage Points ◽  
Analysis Methods ◽  
The City

AbstractPrevious attempts to quantify the role that dogs play in mitigating household property crime rates have produced mixed results.gisand spatial analysis methods to conduct such an investigation are not well-represented in the anthrozoological academic press for an entire city. This study seeks to address these gaps using agis-based case study of dog license locations and reported property crime locations for land parcel data in the City of Milwaukee,wi, for 2011. We found that parcels with reported licensed dogs experienced property crime at rates of between 1.40 and 1.71 percentage points lower than the property crime rates for parcels that were zoned the same and did not have licensed dogs. This association between the presence of dogs and reduced property crime rates suggests dogs have a deterrent effect on property crime; more comprehensive analysis is encouraged to draw more concrete conclusions.

Official Crime Rates and Residents’ Sense of Security Across Neighborhoods in Tokyo, Japan

2016 ◽  
Vol 54 (1) ◽  
pp. 165-189 ◽  
Author(s):  
Kimihiro Hino ◽  
Masaya Uesugi ◽  
Yasushi Asami
Keyword(s):  
Social Capital ◽  
Violent Crime ◽  
Crime Rate ◽  
Property Crime ◽  
The Elderly ◽  
Crime Rates ◽  
Sense Of Security ◽  
Violent Crime Rate ◽  
Using Data ◽  
Official Crime

The aim of this study was to investigate, in consideration of individual attributes and neighborhood-level social capital, the association between official crime rates and sense of neighborhood security among residents in the 23 wards of Tokyo, Japan, using data obtained from a national questionnaire survey and police statistics on crime for 511 neighborhoods. We found that crime rates affected residents’ sense of security differently according to the type of crime committed and the spatial scale. Regarding individual attributes, sense of security among men and those aged 35 to 49 years was in line with the actual property crime rate, whereas that among women and the elderly was in line with the actual violent crime rate. In addition, even when controlling for social capital, which had a strong positive effect on residents’ sense of security, and individual attributes, all crime rates except that for violent crime were significantly related to residents’ sense of security in their neighborhood.

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