2000115-Strengthening-Communities-with-Neighborhood-Data

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Index 451 Vacants 2 Value (V2V), 45 valid classifications, 285 validity, of multi-indicator indexes, 293 van Ham, M., 352 variables, Dynamic Neighborhood Taxonomy project and, 323, 325–326, 339n.12 Vartanian, T. P., 348 Vasquez, Susan, 167 Verbitsky-Savitz, N., 380 Verde (Portland, Oregon), 261, 262 victimization, distressed, disinvested neighborhoods and, 6 video-conferencing technology, 49 villages, 6, 154 violent crime, 195 Virginia Garcia Memorial Health Clinic (Portland, Oregon), 261 Virtua Health System, Camden, New Jersey, 238 virtualization, cloud computing and, 126 virtual servers, 49 visualization libraries, customizing, 379 visualization tools, 392 Visualizing Neighborhoods (Twin Cities), 69 voting records, NNIP partner data holdings, 2013, 89 W. T. Grant Foundation, 303 walkability measures, 94–95, 96 Walker, C., 381 Walker, Darren, 10n.4 Walker, Karen E., 144 Walker Buck, P., 348 walking school buses, 277 Walk Score, 95 Wascalus, Jacob, 57, 398, 399 Washington, DC, foreclosure crisis in, response to, 225 Weave, 103, 379 web-based interactive mapping, 407 “Web Services Manifesto” (Windley), 121 websites, 49 web surveys, 47 Web 2.0, 49 weighted displacement quotients, 384n.14 weights, for indexes of well-being, 293–294 Weisburd, D., 371 Weissbourd, R, 371 welfare usage, neighborhood effect hypothesis and, 346 Wells Fargo, NEO CANDO data in lawsuit filed against, 212 Wheaton, B., 347 white avoidance theory, 350, 359n.5 white flight theory, 348, 350, 352, 359n.5 Wholeness Index (Dallas, Texas), 223, 234, 235, 238 wholesale information markets, 120–123 Wiewel, Wim, 194 Wilder Research (Twin Cities), light-rail transit line and, 67–68 Williams, Don, 233 Wilson, W. J., 341, 346 Windley, Phil, 121, 122 Winston, F., 381 wireless/cellular networks, 126 within-cluster heterogeneity, cluster randomized trials and, 303 World Bank, 106 World Wide Web consortium, 133 youth mapping projects, 187 youth unemployment distressed, disinvested neighborhoods and, 6 spatial effects and, 370 Zabel, J. E., 355 Zerbe, Richard O., 43 Zillow, 95 Zip Business Patterns, 74, 78, 104 Zip Codes, 91, 103, 189, 199, 288, 371 zone-design programs, automated, 290
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Efforts to address the problems of
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ABOUT THE URBAN INSTITUTE The nonpr
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iv 4 A 5 Using 6 Using 7 Advances C
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Acknowledgments We would like first
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1 Introduction to the Field The Inc
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Introduction to the Field 3 into an
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Introduction to the Field 5 to set
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Introduction to the Field 7 in chap
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Introduction to the Field 9 improve
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Introduction to the Field 11 Streng
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14 Strengthening Communities with N
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Table 2.1. (Continued) City/Metro N
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ESSAY From Tornadoes to Transit How
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Institutional Context 59 profession
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Institutional Context 61 graphic, h
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Institutional Context 63 department
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Institutional Context 65 This infor
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Institutional Context 67 By identif
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Institutional Context 69 embedded i
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Institutional Context 71 8. For mor
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100 Strengthening Communities with
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4 A Framework for Indicators and De
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A Framework for Indicators and Deci
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5 Using Data for Neighborhood Impro
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Using Data for Neighborhood Improve
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New Insights on Neighborhood Change
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ESSAY Neighborhood Data and Locally
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ESSAY Cutting through the Fog Helpi
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6 Using Data for City and Regional
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Using Data for City and Regional St
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ESSAY Creating and Using Neighborho
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The Regional Equity Atlas Using Dat
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The Bond Measure Is Approved Using
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ESSAY A Solvable Problem Hidden in
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7 Advances in Analytic Methods for
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ESSAY The Dynamic Neighborhood Taxo
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Sample Output Advances in Analytic
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Page 409 and 410: 400 Strengthening Communities with
Page 421 and 422: 412 About the Authors served as dir
Page 424 and 425: About the Essayists Riccardo Bodini
Page 426 and 427: About the Essayists 417 community a
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Page 431 and 432: 422 Index alternative scenarios, fo
Page 433 and 434: 424 Index Center on Urban Poverty a
Page 435 and 436: 426 Index Community Development Blo
Page 437 and 438: 428 Index data (continued) oversigh
Page 439 and 440: 430 Index early warning systems, no
Page 441 and 442: 432 Index funders, data-driven deci
Page 443 and 444: 434 Index homeless students, chroni
Page 445 and 446: 436 Index Koschinsky, Julia, 307, 3
Page 447 and 448: 438 Index Minneapolis Inspections o
Page 449 and 450: 440 Index Neighborhood Early Warnin
Page 451 and 452: 442 Index OnTheMap, 81, 104 open da
Page 453 and 454: 444 Index privacy concerns (continu
Page 455 and 456: 446 Index Sawicki, David, 10n.2 sca
Page 457 and 458: 448 Index strategic investment init
Page 459: 450 Index Twin Cities (Minnesota) d
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