2000115-Strengthening-Communities-with-Neighborhood-Data

Advances in Analytic Methods for Neighborhood Data 289
that residents’ views do not map neatly onto census tracts and that there
may be disagreement among residents as to neighborhood definitions
(Campbell et al. 2009; Coulton et al. 2001; Foster and Hipp 2011). However,
community mapping exercises and GIS tools hold promise as a way
to link perceptions to geographic boundaries in a useful way.
An illustration of how GIS tools can be used to uncover resident-defined
neighborhood units comes from the Making Connections program of the
Annie E. Casey Foundation (Coulton, Chan, and Mikelbank 2011). Making
Connections, described in more detail in chapter 5, was a community
change initiative directed toward strengthening neighborhoods for families
and children in low-income communities. Representative samples of
households in each community were asked to draw the boundaries of their
neighborhoods as they viewed them onto cartographic maps. The residents
were grouped according to their self-reported neighborhood names, and
their digitized maps were overlaid to find areas of consensus. The blocks
marked in a plurality of resident maps were considered to be core parts of
the neighborhood for the purposes of community identity. Local stakeholders
reviewed the resulting neighborhood units and provided some
evidence of face validity based on their understanding of the local context.
The resident-defined neighborhoods were then used in specifying the units
for the aggregation of survey and census data. This process allowed the
calculation of neighborhood indicators for the areal units that residents
collectively defined as consistent with their sense of neighborhood identity.
Another approach to neighborhood boundary definition is to use
aspects of the built environment that structure social processes and everyday
life. T-communities are neighborhood units defined by the network
of streets that pedestrians can traverse without crossing main streets
(Grannis 2005). The boundaries of T-communities are demarcated
using street data from the Census Bureau’s TIGER line files so that tertiary
street networks fall within the area that is bounded by main streets
or other physical barriers. GIS tools are used to identify the blocks that
fall within these networks of pedestrian streets. The resulting areal units
(T-communities) demonstrate predictive validity with respect to various
hypotheses about racial segregation and interaction (Grannis 2005).
Moreover, T-communities identified through GIS can be combined with
local knowledge to further refine this street-based definition of neighborhood
units (Foster and Hipp 2011).
An additional option is to use person-centric neighborhoods (sometimes
referred to as ego-centric or sliding neighborhoods) that use GIS