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Community Transitions and the Spatial Distribution of Crime Anna Stewart, James Ogilvie and Troy Allard.

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Presentation on theme: "Community Transitions and the Spatial Distribution of Crime Anna Stewart, James Ogilvie and Troy Allard."— Presentation transcript:

1 Community Transitions and the Spatial Distribution of Crime Anna Stewart, James Ogilvie and Troy Allard

2 Workshop presentation 11 July 2008 2 Background Queensland fastest growing state in Australia –Between 2001 and 2006 10% increase in population to just over 4 million people –Expected to double in next 40 years –Hospitals, water, roads and public transport –Increase in 25 to 30 year old couples Key growth factor is natural resources –Coal, gas, minerals (copper, lead, zinc, gold and silver), petroleum –China demand for commodities Government focus on infrastructure –1.6 million dollars every hour spent on infrastructure Little or no focus of the impact of growth on crime

3 Workshop presentation 11 July 2008 3 Research Questions What is the impact of this growth on crime? Data –ABS 2001 and 2006 census data by SLA –QPS 2001 and 2006 reported crime data by SLA

4 Workshop presentation 11 July 2008 4 Profile of the population growth 2001 and 2006 ABS census data Queensland divided into 479 Statistical Local Areas (SLA) 2006 mean population 8,495 (SD = 8,495) –Min population = 66 –Max population = 72,683 2001 to 2006 mean population growth 822.77 (SD = 1,497.9) –Min growth = - 856 –Max growth = 10,856 (increase of 69%)

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8 Workshop presentation 11 July 2008 8 Remoteness areas Major Cities (N = 256) –Highest population growth Inner Regional (N = 60) –Highest total population –High population growth Outer Regional (N = 77) Remote (N = 28) Very Remote (N = 57) –No growth Migratory (N = 2)

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10 Workshop presentation 11 July 2008 10 Change in population heterogeneity by SLA Percentage of population between 10-19 –Decrease, 14% to 13.4%, range 0 - 27% Percentage of population Indigenous –Increase, 8.9% to 9.3%, range 0 – 97% Percentage of population born overseas –Increase 15.5% to 16%, range 0 – 52% Short term Residential Stability: –Prop of families with different residential address one year ago –Increase in stability 26.4% to 23%, range 06 to 58% Long term residential stability –Prop of families with different residential address five years ago –Increase in stability drop from 54% to 51%, range 12% to 94%

11 Workshop presentation 11 July 2008 11 Social and economic change Proportion of households in poverty –No change, mean 22%, range 3% to 65% Proportion of households with a single parent –No change, mean 17%,range 0 to 56% Proportion public housing –Significant increase, 3% to 4%, range 0 to 90 Proportion unemployed –Significant drop, 7.5% to 4.5%, range 0 to 15% Proportion buying/owning own home –Significant drop, 59% to 58%, range 0 to 92% Median family income per week –Significant increase $921 to $1212, range $445 to $2512

12 Workshop presentation 11 July 2008 12 Police offending data QPS data for reported offences by SLA –2006 total of 420,454 reported offences personal (8%), property (54%) other (38%) Between 2001 and 2006, overall 6% drop in reported offences

13 Workshop presentation 11 July 2008 13 Crime by SLA Personal crime –No change between 2001 and 2006 –Average rate 1.2 offences per 100 population –Maximum 17.3 offences per 100 population Property crime –Decrease between 2001 and 2006 –9.3 offences per 100 population to 6.5 offences per 100 population Other crime –Increase between 2001 and 2006 –3.6 offences per 100 population to 5.0 offences per 100 population

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17 Workshop presentation 11 July 2008 17 Research Questions What is the impact of this growth on crime? How do crime increasing areas differ from crime decreasing areas? –Population growth and stability Total population 01 and 06 One year stability 01 and 06 –Housing affordability Prop in poverty 01 and 06 Prop owning/buying 01 and 06 Prop public housing 01 and 06

18 Workshop presentation 11 July 2008 18 Crime category Crime category SLAs for personal and property crime –Crime increasing SLA Property crime - 8.8% Personal crime – 12.4% –Crime decreasing SLA Property crime – 56.6% Personal crime – 14.9% –High crime stable SLA Property crime – 8.8% Personal crime - 10.1% –Low crime stable SLA Property crime – 27.7% Personal crime – 62.7%

19 Workshop presentation 11 July 2008 19 Property crime Interaction effect time*crime category –Poverty –Own/buy home Main effect –Population –Stability

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24 Workshop presentation 11 July 2008 24 Personal crime Significant interaction effect –Poverty –Public housing –Population –Stability Main effect –own

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30 Workshop presentation 11 July 2008 30 What does it all mean? Place is important Complex interactions among variables Factors that drive personal crime not necessarily the same as property crime I should not put up an abstract before I have done the analyses


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