2000115-Strengthening-Communities-with-Neighborhood-Data

Advances in Analytic Methods for Neighborhood Data 369
ture ideas” (National Research Council 2006, x). Spatial tools implement
methods for spatial data analysis, which is “the formal quantitative study
of phenomena that manifest themselves in space. This implies a focus on
location, area, distance and interaction” (Anselin 1990, 64). Spatial concepts
and methods are relevant in instances when the end of geography is
a less accurate description than Tobler’s (1970) first law of geography that
“everything is related to everything else, but near things are more related
than distant things.” And they can add insights when individuals are not
assumed to act as isolated economic agents but are influenced by social
interaction effects (Durlauf 2004) and neighborhood effects (Sampson
2012). What matters here is that traditional statistical and economic
assumptions of independence are replaced by an explicit focus on and
treatment of spatially constrained interdependence.
Spatial thinking, methods, and tools are congruent with place-based
efforts because, at a minimum, what these programs have in common
is a focus on a shared delineated location. More broadly, “placed-based
approaches are collaborative means to address complex social-economic
issues through interventions defined at a specific geographic scale” (Cantin,
cited in Bellefontaine and Wisener 2011, 7). Examples of place-based
approaches in the United States that particularly emphasize comprehensive
approaches and community building include comprehensive community
initiatives and other community change efforts (Kubisch et al. 2010).
Space becomes a platform for integration across academic disciplines,
such as computer science, economics, statistics, and geography, as illustrated
by the subfields of geo-computation, geo-statistics, and spatial
econometrics (Goodchild and Janelle 2004). It also becomes a platform for
coordinating and evaluating interventions across sectors and governmental
levels, domains, and departments such as employment, housing, education,
and crime. Space invites data integration across jurisdictions and
scales through GISs that layer data of multiple types and levels of aggregation.
The recent focus among funding agencies on collective impact illustrates
how funders who are investing in the same geographic areas can
commit to collaborate and jointly monitor programs in these areas (e.g., in
the 300-organization Strive Partnership to improve children’s educational
and employment outcomes in Cincinnati, Ohio). This approach contrasts
with silo practices in which each funder designs and evaluates its own
programs separately, even when programs pertain to the same area.
The assumption that different areas warrant different program designs
or expectations of how impacts work contrasts with one-size-fits-all,