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Crime Pattern Theory Expanding our Understanding of Crime Using New Computational Strategies Part 3 Institute for Canadian Urban Research Studies


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Institute for Canadian Urban Research Studies


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Crime Generators • Channel large numbers of people past a set of criminal opportunities.

• Some potential offenders are mixed into groups of people passing the opportunities. • Crimes occur opportunistically.

Institute for Canadian Urban Research Studies


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Crime Attractors • Attract strongly motivated offenders intending to commit a crime. • Attraction is created by an ecological label. • Offenders may travel long distances to reach an attractor location. • Crimes often committed by area outsiders. • Offenders often follow a muti-step target search process once they reach the attractor neighbourhood.

Institute for Canadian Urban Research Studies


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BURNABY CRIMINAL CODE CALLS 1991

900 800 700 600 500 400 300 200 100 0

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1

900 800 700 600 500 400 300 200 100 0

3

40

30 35

25 30

20 25

15

20 10

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N

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5 0

0

Institute for Canadian Urban Research Studies


3D Visualization of major mall – 2001-2006 (ArcScene, Kernel Density Map(12,200m))

Institute for Canadian Urban Research Studies


Cross section of Crimes Across Kingsway in MT mall ( Kernel Density Map)

135000

Kingsway

Metrotown Mall Across Kingsway

115000 95000 75000 55000 35000 15000

1528 1465 1403 1340 1278 1215 1152 1090 1027 964 902 839 777 714 651 589 526 463 401 338 276 213 150 88 25 38 100 163 225 288 351 413 476 539 601 664 726 789 852 914 977

-5000

Justin Song

Institute for Canadian Urban Research Studies

10/3/2011


Cross section of Crimes Along Kingsway in MT mall ( Kernel Density Map) 155000

Metrotown Mall Along Kingsway 135000 115000

95000 75000 55000 35000 15000

1501 1449 1397 1345 1294 1237 1180 1124 1067 1010 953 896 840 783 726 669 613 556 499 442 385 329 272 215 158 102 45 12 69 126 182 239 296 353 409 466 523 580 637 693 750 807 864 920 977 1034 1091 1148 1204 1261

-5000

Institute for Canadian Urban Research Studies


Offenders' Home Location (City) (based on Metrotown Mall Centre crimes) offenders count 1400 1200 1000 800 600 400 200 0

VANCOUVER

BURNABY

SURREY

Institute for Canadian Urban Research Studies

PORT MOODY

COQUITLAM


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Institute for Canadian Urban Research Studies


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Networks • Networks of people can structure crime patterns by: ▫ Changing each other’s awareness and activity spaces ▫ Providing multiple starting points for criminal target searches

• Networks of interest should include: ▫ ▫ ▫ ▫

Criminal Associates and Co-Offenders Girlfriends or significant others Family Friends

• Networks can be analyzed to: ▫ Identify a spatially likely suspect for a set of crimes ▫ Identify a set of crimes that relate to a set of offenders ▫ Understand larger crime patterns

Institute for Canadian Urban Research Studies


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W2

W1

H1

S&E2

H2 S&E1

W3

H3

S&E3 Institute for Canadian Urban Research Studies


W3 Low Occurrence

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W1 W2

H2 High Occurrence

H1

H3 S&E Institute for Canadian Urban Research Studies


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FLINTS NETWORK NODES WITH INTELLIGENCE

Co-Defendant Link

IMS Link

Co-Defendant & IMS Link

Institute for Canadian Urban Research Studies


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Focus on Prolific Offender Networks • Analyze police and court data • Explore networks of frequent offenders • Identify prolific offenders who are also key to keeping the network of offenders active • Target investigations on offenders who are most important to offending capacity of the entire network • Shred network

Institute for Canadian Urban Research Studies


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Graffiti Vandal Network

Institute for Canadian Urban Research Studies


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Key Players Jailed: Network Disintegrates Vandals become less active Secondary players can be targeted

Institute for Canadian Urban Research Studies


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A Co-Offending network meeting the legal definition of an Organized Crime Group

Source: Brantingham, Brantingham, Glaesser & Tyebi (2012) AN ANALYSIS OF RCMP ``E`` DIVISION DATA TO ESTIMATE POSSIBLE CRIMINAL ORGANIZATIONS: FINAL DESCRIPTIVE REPORT. OTTAWA: PUBLIC SAFETY CANADA.

Institute for Canadian Urban Research Studies


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Road Network Analysis • Ease of Movement ▫ Formal road network analysis  beta scores – ease of flow measurement  Tells us likelihood of offender or target from Point A to Point B on the network  Tells us most likely path

• Directionality ▫ Establishes resistance to movement ▫ Calibrates weights of competing nodes

Institute for Canadian Urban Research Studies


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The road network, land use and zoning as key determinants of the crime pattern Research by Rob Tillyer and Patricia Brantingham

Institute for Canadian Urban Research Studies


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Residential B&E's in Burnaby, BC #

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Sum m ed residential b reak and en ter.sh p 1 # 2 -3 # 4 -7 8 - 11 # # 12 - 16 Mainand skytrain.sh p #

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Commercial Zoning #

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Sum m ed residential b reak and en ter.sh p 1 2-3 # 4-7 # 8 - 11 # # 12 - 16 Mainand skytrain.sh p King scom b ufm erg e.shp Hastin gsbu ff.shp Bu ffer 1 of Lou gh eed co m .shp #

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Sum m ed residential b reak and en ter.sh p 1 2-3 # 4-7 # 8 - 11 # # 12 - 16 Ea dw elling .shp 0 - 2472.1 2472.1 - 4387.1 4387.1 - 9275.8 9275.8 - 224305.6 #

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Institute for Canadian Urban Research Studies


29

Land Use analysis • Criminality of land use mixtures

▫ Is a pub near a high school more problem than a pub near a hospital? ▫ Is a school near a parking lot more problem than a school near a bank? ▫ Is a convenience store more problem next to a school or a bar or a hospital?

• Crime fields of nodal uses

▫ How far will a thief travel to reach a convenience store, a super market, a shopping centre? ▫ How far will a customer travel to reach a drug market or a prostitution stroll?

• Housing mix

▫ What blend of different housing forms maximizes or minimizes criminal event volumes? Institute for Canadian Urban Research Studies


A Conceptual Model for Anticipating Crime Displacement Patricia L. Brantingham and Paul J Brantingham ICURS Simon Fraser University Institute for Canadian Urban Research Studies


Brantinghams’ Displacement Model (1984) The Burglar’s Choice Displacement Type Geographic

Temporal

Other NonConfrontation Crimes

Other Confrontation Crimes

Non-Criminal Activity

Full-time Burglars Specific Goods Oriented Non-Specific Goods Oriented Part-time Burglars

High

High

High

High

Low

High

High

High

Low

Low

Adults with High Commitment

Moderate

Low

Moderate

Low

Low

Adults with Low Commitment

Low

Low

Low

Low

Moderate

Juveniles with High Commitment Adults with High Commitment

Low

Moderate

Moderate

Low

Low

Low

Low

Low

Low

Moderate

Institute for Canadian Urban Research Studies


Spatial Displacement • Most criminal events do not displace when some intervention eliminates the opportunity

• The relatively small proportion of criminal events that displace do so in predictable ways.

Institute for Canadian Urban Research Studies


Journey to Crime  Most crimes are committed opportunistically as a result of the offender discovering the opportunity in the course of routine, non-criminal activities  Crime trips are short, and occur in the offender’s home neighborhood or some adjacent area.

 Crime trips that leave an offender’s home neighbourhood travel to other similar neighourhoods or to some wider activity node – some crime attractor or crime generator.  Crime trips by offenders living in the same neighbourhood tend to be vectored in the same direction.  Crime trip distances vary with the type of crime in question.  Crime trip distances vary with the age of the offender, increasing as the offender ages.  Crime trip distances vary with social class, increasing as social class increases. Institute for Canadian Urban Research Studies


Aggregate Directionality Offenders Metro Vancouver

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Displacement Implications Journey to Crime • Criminal activity will displace the shortest possible distance within the neighbourhood. • Criminal activity that displaces from the immediate neighbourhood will displace to the next neighbourhood offering a similar setting and adequate supply of opportunities. • Criminal activity will displace outside the neighbourhood in the direction of a major activity node, often the CBD. • The social and demographic characteristics of the neighbourhood in general will set limits on the distance criminal activity will displace from the original neighbourhood to other neighbourhoods. • Criminal activity is unlikely to displace outside the neighbourhood to areas of substantially different character except to crime generator and crime attractor nodes. Institute for Canadian Urban Research Studies


Paths and Barriers • Road networks and transit systems channel activity in general and criminal activity in particular into specific, narrow lines of movement. • Destination points create crime generators by channelling large numbers of people into some neighbourhoods and not others. • The permeability of a neighbourhood defined in terms of its path connectivity sets limits on the likelihood that an outside offender will enter the neighbourhood to search for targets. • Topographical and built features of the environment form barriers that prevent movement between adjacent areas. • Social differences create barriers to penetration of neighbourhoods by outsiders.

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Crime clustering on arterial and collector roads

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Displacement Implications Paths and Barriers • Crime will displace toward and along traffic arterials. • Crime will displace along traffic arterials in the direction of some major activity node. • Crime will only displace off a traffic arterial into neighbourhoods that have permeable, predictable and highly connected internal path networks. • Major traffic barriers also constitute barriers to crime displacement.

• Crime displacement along a rapid transit system is confined to areas close to the transit stations. • Crime will not displace into neighbourhoods that are substantially different in character from the offender’s home neighbourhood.

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Crime Generators • Crime generators produce crime by channelling large numbers of people past a set of criminal opportunities. • Some potential offenders are mixed into the people gathered at generator locations. • Crimes occur opportunistically.

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Displacement Implications Crime Generators • Criminal activity associated with a crime generator is unlikely to displace. • Potential offenders will be deflected into noncriminal activity.

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Crime Attractors • Crime attractors are places to which strongly motivated, intending criminal offenders are attracted because of opportunities for crime. • The attraction is created by an ecological label, often supplemented by the intending offender’s personal past history, establishing that particular location as a known place to go for some specific kind of crime. • Strongly motivated offenders will travel relatively long distances in search of a target. • Crimes in such locations are often committed by area outsiders. • Offenders engaging in crime at crime attractor locations are likely to engage in a staged target search process in the vicinity of the crime attractor.

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Crime Attractor

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Crime Attractors Displacement Implications • Criminal activity at crime attractors is likely to be displaced, in the first instance, into the neighbourhood surrounding the attractor.

• Criminal activity is likely to be displaced back into the offender’s home neighbourhood rather than to nearby similar neighbourhoods. • Criminal activity is likely to be displaced to other important attractor nodes.

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A process for predicting displacement locations Analogous to Hot Spot prediction

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Analyze the character of the intervention site.  Is it a crime attractor, a crime generator or crime neutral?  If a pure crime generator, little displacement is likely.  If a crime attractor, a crime neutral site or a mixed attractor-generator site some displacement is possible.

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Analyze intervention neighborhood  Analyse the social, characteristics of the neighbourhood.

cultural, economic intervention target’s

 Social area analysis  Topological neighbourhood analysis

 Identify other neighbourhoods with similar characteristics. Map the similar neighbourhoods.

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Analyse characteristics of the probable displaced offenders.  Utilise information from planning and movement geography literatures to estimate a likely maximum range of movement for the displaced offender group.  Identify neighbourhoods from the ‘similar neighbourhoods’ map that fall within this activity range.  If site is a crime attractor, identify probable neighbourhoods of displaced offenders. Utilise:

home

 police information on home neighbourhoods of arrested offenders,  planning department information on home location of site users in general.

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Analyse land uses. • Identify major activity nodes. • Weight the activity nodes utilising some combined volume and distance measures. ▫ Gravity potential ▫ Hierarchical diffusion

• Rank activity nodes in terms of weighted importance.

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Analyse the street network.  Identify arterial roads flowing most directly from the police intervention location toward the major activity nodes using some measure such as the beta statistic.

 Identify neighbourhoods from the “similar neighbourhood” map that are characterised by high entry permeability. ▫ White (1990) is likely approach. ▫ Johnson and associates are developing additional permeability measurements – watch for new technical publications

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Analyse transportation network. • Identify major entry and exit points. • Identify search ranges around each entry and exit point. ▫ There is a crime risk zone around rapid transit stations in North America that start ~50 meters out from the station and may extend for additional 200 meters (Chicago, Vancouver studies)

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Combine Analyses and Take Action • Combine these analyses to identify specific potential displacement sites. • Rank order on basis of combined likelihood score • Provide intelligence on known offenders who might be displaced to police units responsible for most highly ranked displacement sites • Provide crime prevention advice to residents of displacement areas. Institute for Canadian Urban Research Studies


Paul Brantingham