2000115-Strengthening-Communities-with-Neighborhood-Data

Index 439
partner data holdings, 2013, 87–89
partner organizations, Feb. 2014, 25–26
partners as local data intermediaries,
23–24, 27
technical assistance and training by, 402
in Twin Cities, Minnesota, 58
National Preservation Database, 77
National Science Foundation, 104
national support system, 400–407, 408
access to national- and state-level
government and proprietary data,
401, 403–404
data transformation, visualization, and
local data use, 401, 404
educating for data-driven
decisionmaking, 401, 404–405
funding for local development and
innovation, 401, 406
informing civic leaders about effective
data environment, 401, 402
network for strengthening
neighborhood research, 401,
405–406
technical assistance and training, 401,
402
National Telecommunications and Information
Administration, 102, 407
National Vacant Properties Campaign, 33,
206, 207
national well-being, local-level governance
decisions and, 409
natural areas bond measure (Portland,
Oregon), 254–259, 262, 263
natural experiments, neighborhood
effects testing and, 355
“natural quasi-experiments,” overcoming
selection bias with, 354
Nature in Neighborhoods Capital Grants
Program (Portland, Oregon),
256–257, 259–262
Navarro, Mary Rose, 259, 260, 261
NCCS Core nonprofit database, 80
NCES Common Core of Data, 79
nearby attached movers, Making
Connections research on, 170–171
nearest neighbors criteria, 376
negative spatial autocorrelation, 373
negative spatial externalities, 374
Neighborhood and Family Initiative, 155,
190
neighborhood change, moving plans and,
352
Neighborhood Change Database, 91, 92
neighborhood context
dynamism of, 347
influences of, 345
neighborhood data. See also analytic
methods for neighborhood data,
advances in
for informing larger jurisdictions, need
for, 220–221
powerful role of, 243
putting to use, in cities and regions,
221–227
regional framework planning and
power of, 250
strategic use of, case studies, 227–242
usefulness of, advancing, 310–311
neighborhood data and community
change, 185–200
challenges and tensions related to,
188–190
community-university partnerships
and, 193–197
conclusions about, 200
neighborhood data and program
evaluation, 190–193
overview, 185–186
rationale and intent behind, 186–188
social action and, 197–199
neighborhood data case studies
improving children’s health in Travis
County, Texas, 227–233
improving health care systems in
Camden, New Jersey, 238–242
neighborhood disparities addressed in
Dallas, Texas, 233–238
neighborhood disadvantage effects,
mental health of young adults and,
347–348
neighborhood disparities in Dallas, Texas:
case study, 233–238