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date: 19 July 2019

(p. 931) Index

(p. 931) Index

activity node 23, 86, 91–93, 99, 243, 251, 254, 256, 265, 279, 314, 320, 324, 327, 430, 476, 477, 498, 500, 507, 510, 527, 548, 741, 743, 779, 781–782, 792, 889
activity space 16, 64, 86, 92, 99, 112, 223–224, 245–255, 265, 406, 425, 429–433, 476, 498, 507, 548, 693, 709, 741–743, 804, 842, 849, 896, 912
administrative data 281–283, 297, 354, 364–366, 600, 603, 607, 615, 620
agency, human 169
agent-based modeling 75–77, 313–336
aggregation 9, 14, 63, 177–179, 185–187, 246, 254, 265, 284, 353, 357, 371, 434, 446, 478, 481, 491, 579, 588, 653, 695, 698–701, 709, 746
aggregation bias 353, 698
airport 263, 618, 637, 804, 872–873, 876, 879
ambient population 213, 215, 216, 231, 247, 508, 510, 595, 912
aoristic analysis 696, 699, 706–707
architecture 11, 242, 323, 529, 884, 886
assault, sexual, violent 504–505, 584, 829
ATM 511
atomistic fallacy 179, 186, 196
attractiveness, target 278, 280, 283–284, 287, 433
authority constraints 733–734
behavioral setting 601, 638
big data 75, 185, 211, 215–216, 225, 239, 265, 306, 454, 465
bike theft 280
bioterrorism 798, 810–811
block, street, face 100, 35, 59–76, 153, 155–157, 162, 178, 184, 191–192, 248, 298, 305, 369, 381, 431, 433, 438, 479, 579, 581–589, 593–596, 601, 632, 678, 746
bounded rationality 86–87, 109
broken windows theory 12, 15, 22, 130, 226, 458, 459–460, 463–464, 607, 611–612, 615, 620, 722,
buffer zone 146, 693, 740
built environment 11, 22, 59, 62, 112, 114, 170, 242, 297, 379, 386, 475, 478, 481, 529, 562, 721, 732, 760, 839–840, 853–854, 868, 875
burglar 11, 72, 110, 155, 433, 602
bystanders 109, 111–112, 231, 609
(p. 932) capability constraints 733–734
capable guardians 16, 73, 89, 110, 114, 162, 168, 180, 277, 407, 426, 428–429, 431–432, 498, 500, 503, 506, 514, 595, 706, 716, 721–727, 734, 798, 842, 877, 892–893, 896, 912
CAPI (computer assisted personal interview) 277
car, vehicle, theft from 280, 587, 695, 744, 762, 783
car, vehicle, theft of 274, 282, 411, 519, 587–588, 592, 760–763
central business district 38, 126, 152, 192, 203–204, 348, 433, 499, 502, 519, 528, 535, 590, 841
characteristics of areas/area characteristics 17, 281–282, 296, 349, 351, 366, 401, 669, 783
Chicago School 4, 7, 10, 16, 36–38, 119–120, 126–127, 131, 133, 134, 136, 151, 160, 168, 190, 240, 281, 349–351, 361, 365, 417, 841, 847, 850
civil gang injunctions 853
cloud computing 246
clustering of crime 14, 201, 365, 401, 459, 591, 595
co-offender 25, 265, 616, 621, 693, 875–879
co-offending 265, 323, 709, 876, 877
code of the street 47–48
community attachment 39, 114
community Criminology 35, 37, 46–47, 50, 58–59, 63–66, 121, 169
competition models/Lotka-Volterra 843
computer science 246, 331
concentric zone model 10
conflict zone 830–831
convergent settings 634, 655
counterinsurgency (COIN) 797, 808, 810
counterterrorism 797, 798, 802–804, 808, 811
coupling constraints 734
crime concentration 14, 22, 86, 274, 280–281, 354, 360, 365, 424, 428, 431, 434, 491, 579–596, 628, 632–634, 640, 653, 657, 666, 679, 683, 691, 699, 785
crime displacement 96–98, 514, 770, 853
crime drop 277, 281, 459, 584, 672, 699–700
crime generator 68–69, 86, 91, 243, 254, 430, 433–434, 442, 445, 477, 492, 497–515, 548, 593, 643, 731, 741–744, 898,
crime harm index 462
crime involvement 634, 658
crime location choice 732–733, 739, 741, 743–747
crime opportunity 13, 36, 46, 50, 52, 86, 90, 123, 428, 433, 500, 503, 505, 514, 593, 653, 710, 717, 901
crime places 13, 37, 52, 92, 583, 594, 630, 634, 640–643, 653–656
crime prevalence 280, 506, 666
crime prevention through environmental design (CPTED) 58–59, 72–74, 157, 760–770, 853
(p. 933) crime science 160–162, 213
crime site 11, 96–97, 197, 243, 508, 634, 655, 717, 738, 740, 799, 801
criminal groups 98, 871
criminal motivation 12, 324, 499, 741, 888
criminal organizations 870–872
criminal propensity 51, 241, 360, 737, 821
cyber-banging 848
cyberspace 5, 246, 253, 664–666, 728, 883–902
cyberbullying 885, 891, 893, 895, 897
cyberterrorism 798, 810, 885, 901
daily routine activities, 16, 157, 213, 425, 701, 855
dangerous place 15, 727, 847
dark web 885, 898, 902
data, secondary 185, 228, 366, 395, 695–696, 794,
deep web 898
defensible space 11, 15, 58–59, 61, 72–73, 297, 361, 550, 640, 721–725, 760–761, 840, 900
defensible space theory 11, 550, 721–725, 840
delinquency areas 125, 154
demographics 323, 353, 402, 809
deterrence 608, 763, 924
deviant places 15
differential social organization 140–142
diffusion of benefits 96–98, 766
diffusion of violence 844–845
directionality 243–244, 254–258, 264, 740–741
disaggregation 63, 153, 284, 446, 494, 668
discrete choice 783
disorder, psychological 819
displacement 85, 88, 96–9, 166, 514, 766–770, 853–854, 921, 924
dispositional factors 16
dissemination areas 193–196, 200–201, 205
distribution of crime 2–13, 17, 37, 121, 190, 202, 239, 274, 280, 311, 349, 394, 424–426, 444, 457, 483–484, 493, 498, 579–583, 590, 630, 657, 664–670, 691, 696, 844
distribution of offenders 5, 351
distributed Denial of Service attacks 885, 902
dog fouling 227–229
domestic violence 95, 288, 335, 644–645, 669, 676–677, 707
drug markets 157, 459, 499–501, 548, 742, 846–848, 869, 874
drug trafficking 871, 875–876
drug use 364, 586, 695, 818
ecological disadvantage theory 15
ecological construct validation 63–70, 72, 74
ecological fallacy 63, 179, 186, 193, 196, 239, 367, 562, 809
ecology 3–7, 12, 35, 62, 74, 119, 371, 601, 733, 798, 801, 841, 843, 848
egohood 15, 22, 424–447
environmental backcloth 244–247, 254, 258–266, 590, 912, 914, 917
epidemic model 15
ethnographic research 41
evolution, Darwinian 3, 665
evolutionary adaptation 3–4
experience sampling method 212
experimental design 329–330, 659
experimental research 622
explanation, causal 14, 20, 38, 43–45, 58–76, 84, 135, 152, 167, 313, 331, 353, 358, 363, 366, 382, 533–534, 698, 746, 809, 845
exposure to risk 210, 213, 229
fast-food restaurant 68, 638, 640
field interviews 849
firearm 587, 807, 845
flow of people 16, 95, 251, 263, 723
foraging 15, 95, 681, 733
formal control 871
formal network 17, 572
gang member 41–42, 839–855
gang rivals 845
gang violence 839, 843–847, 853
gangs 23, 38, 98, 259, 839–855, 879, 918
gated communities 22, 401–421
geo-tagged 216
geographic Information Systems (GIS) 190, 555, 630
geographic profiling (geoprofiling) 23, 95, 797–812
geointelligence 797, 803, 811
geometry of crime 11, 254–256, 475–476, 734, 741
gestapo 808
global connectivity 25
global Positioning System (GPS) 14, 191, 217–221, 231–232, 361, 395, 623
GPS tracking 217, 232, 623
habitat 4–5, 681
harbors 872–879
hierarchical models 281, 284
hobbesian 127, 131, 136, 141
homicide 44–50, 95–96, 187, 242, 285, 463, 521, 524, 696, 701, 707, 758, 844, 853
hot flushes 22, 664, 668, 677–679, 681
hotspots policing 580, 591, 654
human territorial functioning 108
imprisonment 164–170
income inequality 345, 365, 372, 428, 434, 443–446, 917
independence of irrelevant alternatives 784
informal control 17, 37, 67–74, 346, 367–370, 456, 602–607, 613, 870, 901
information overload 797, 802–803, 808–812
injury 704
insurgency 797–798, 808
intelligence 23, 215, 466, 591, 797–812, 908, 915
investigation, police 23, 95, 655–656, 797, 801–812
journey to crime 85, 93–96, 99, 197–199, 218, 243, 329, 573, 733–747, 799, 808, 872, 877
(p. 935) kernel density estimation 192, 197
lifestyle theory 277, 608
lifestyles 72, 168–169
local drug markets 846, 874
location choice 22, 333, 429, 732–748
looting 791
mafia 847, 869–880
malware 885–902
map, cognitive 86, 255, 314, 321. See also mental map
map, mental 90, 91, 112, 324, 804. See also cognitive map
map, point 10, 239, 258
Marxian 127–141
Mexican American/Chicano gangs 850
micro places 499, 585
microlocations 120, 668
mobile phone 21, 218–219, 223, 229, 232, 288, 595, 604–606, 700, 735, 848
mobile phone applications 223, 229, 232, 515
mobility, offender 15, 85, 86–88, 96, 732–747
mobility patterns 86–92, 250, 405, 699, 704–708
mobility, residential 17, 39–40, 49, 354–365, 378, 384–397, 607, 612, 724, 846–848
model implementation (ABM) 326
model validation (ABM) 327
modifiable areal unit problem (MAUP) 180, 186, 193–200, 389
morality 4, 7, 241, 350, 360, 737
multiple spatial units of analysis 195
natural surveillance 11, 162, 573, 721, 759, 762, 895–901
near repeat victimization/near-repeat 87, 93, 99, 207, 265, 666, 677, 681, 745
nearest-neighbor distance 807
neighborhood dynamics 22, 346
neighborhood watch 406, 419, 762
nested data 569
nodes, logistical 872–873, 879
norms 4, 17, 36, 47, 106–113, 127, 131, 136, 141, 370, 406, 581, 612, 694, 709, 717, 831, 850
occupancy 278, 333, 705, 718, 725, 899
offender convergence settings 868, 877–879
offender perceptions 86, 314, 463
opportunity makes the thief 13, 817
opportunity theory 15, 46, 51, 119, 122, 171, 758, 822
organized crime 23, 868–882
pareto principle 221, 591, 594, 666–667
participant observation 128, 293
perceived risk 13, 59, 720
physical characteristics 403, 595, 635
piracy (maritime) 23, 315, 907–925
place management theory 15, 629–659
playgroups 841–842
plunder 23, 908, 925
police recorded 128, 215, 361, 364, 379, 395, 519, 706, 786, 823
pooled places 633–634, 653–656
(p. 936) population density 8–9, 231, 298, 349, 350–365, 381, 385, 436, 445, 525, 529, 603, 607, 612–615, 803, 843
predatory crime 164, 582, 734, 798, 875–877
premeditation 738–739, 743, 747, 821
private space 404–405, 431, 603, 609, 848, 854–855
privatized space 404–405
problem-oriented policing (POP) 680, 853
proprietary places 629–659
prostitution 12, 89, 91, 128–135, 499–501, 742–743, 880
proximal places 632–634, 641
proxy measures 383, 396, 546, 572, 718–719, 728, 743
psychological characteristics 821
psychology 23, 62, 212, 242, 331, 346, 244, 798–799, 831
punishment 111, 830, 840
qualitative inquiry 229, 293
racketeering 868–879
railway stations 499, 790–791
random utility framework 794
random utility maximization 744
randomized experiments 651, 654
rational choice perspective/theory 13–20, 85–113, 119, 163, 315–336, 498, 692, 733–734, 758–770, 779–780, 783, 790, 798–800, 822, 911
rationality, bounded 86–87, 109
real estate (value) 10–11, 22, 351–421, 518–540, 607
reciprocity 17, 44, 846
repeat crimes/victimization 87, 93, 99, 319, 329, 501, 637, 642, 662–683, 745, 899
replication 206, 224, 281, 295, 595
resident population 43, 282, 299, 665
residential mobility/stability 17, 39–44, 49, 105, 354–366, 378, 384–396, 411–419, 607, 612, 724, 846–848
restaurant 68, 214, 348, 507, 515, 618, 638–640, 657, 782–787
riots 23, 214, 779–794
risk heterogeneity 87, 810
risky facilities 428, 431–432, 494, 506, 678, 779–794
rural areas 5, 251–253, 347, 371, 385, 595, 657, 806
sanction severity 733
selection/Selectivity, bias 65, 786
self-selection 230, 357
sensitivity analysis 195
sensors 217, 219, 233, 925
serial crimes 797
set space 841–855
sex offenders 520–522, 727, 818–832
sexual abuse 23, 88, 727, 817–832
sexual assault 504–505, 584, 829
shoplifting 251, 295–296, 636, 706, 761–762
shopping center (mall) 70, 243, 247, 252–257, 263, 359, 477, 488–494, 497–507, 603, 610–611, 621, 634, 645, 648, 742, 826, 874
signal crimes perspective 226, 453–469
simulation, computer 21, 75–76, 247, 265–266, 311–336
situational action theory 75, 303, 358, 361, 601, 615
situational characteristics 600–603, 615–618, 724
(p. 937) situational crime prevention 13, 23, 73, 88, 90–92, 171, 242, 311, 407, 514, 622, 637, 656, 720, 724–729, 757–770, 853, 868, 873, 885, 901, 908
situational dynamics 23, 832
smartphone 219, 245, 306, 623, 747, 885
social capital 17, 45, 105, 282–283, 361–366
social cohesion 12, 17, 36, 43, 107, 151, 299, 323, 350, 356–360, 368–374, 384–385, 431–432, 527, 723, 781
social disorganization theories 113, 120, 633, 781, 794
social ecology 5, 35, 371
social embeddedness 23
social environment 1, 5, 20–21, 109, 112–114, 161–163, 240, 359, 424, 460–461, 579, 653, 693, 710, 724, 797–798, 876
social media 21, 216, 245, 454, 465–469, 700, 728, 781, 848
social network 23, 41, 50, 132, 169, 384, 432, 434, 446, 467, 800, 845–848, 871–878, 885–897, 901
social opportunity structure 868, 872, 877, 880
social simulation 314
social trust 18, 346, 353, 356, 365–370, 602, 613
space-time budget 294, 301–307, 359–361, 370, 601–623, 696, 736–747
spatial autocorrelation 199–207, 301, 367, 393, 410, 425, 527, 534, 679, 790
spatial scales/scaling 21, 50, 58, 62–63, 299–300, 491, 781, 803
spatial statistics 21, 200–205
spatial unit of analysis 193, 196, 732, 746
spatiotemporal patterns 99, 665, 693, 696, 709–710
stadiums 22, 497–515, 645
street corner 630, 840–847, 854–855,
subculture 5, 39, 131–143
subway 92, 502, 513, 526, 529, 582, 653, 804
suicide 7, 141
surfer gangs 849
suspect prioritization 800
symbiosis 4
systematic observation 22, 295, 459
systemic theory 107, 114
target search 242, 738
target selection 15, 86, 90–92, 319, 324, 327–329, 555, 573, 738, 804, 811
temporal constraints 704
temporal crime patterns 692–710
temporal scaling 63–76
territoriality 11, 112, 404, 431, 550, 552, 607, 722, 839–855
terrorism 23, 95, 797–812, 901
The onion router (Tor) 895–898
time geography 733–734, 747
transit crime 868, 871–879
transit station 22, 497–515, 742–743
transport network 91, 213, 311, 513, 555, 913, 922
underground stations 503, 782, 793
unemployment 47, 201–202, 365, 382, 570–571, 612, 829, 852
universal Logit 784–793
unstructured socializing 601–623, 737
(p. 938) vacant properties 282, 352, 842–843
victim perceptions 86, 90
victimization risk 168–169, 279, 283, 289, 602, 667, 677, 699, 706, 891
victimization survey 211, 216, 273–289, 386–395, 409, 595, 602, 669–676, 695, 706, 823, 827, 915,
vietnamese gangs 850
virus (computer) 890–899
visualization 21, 192, 197, 238–266, 699
volunteered geographic information (VGI) 213–215
war zone 828–831
weapon 603, 606, 727, 733, 736, 797–806, 920
weapon carrying 603, 606, 616–621, 727, 733, 736
white-collar crime 655, 767–770
zonation effect 180
zone in transition 37–38