2000115-Strengthening-Communities-with-Neighborhood-Data

172 Strengthening Communities with Neighborhood Data
Budde (2014) examined the pattern of school attendance in the 10 cities. 23
Their findings confirm a shift that has been known to be under way for
some time as more and more school districts adopt school choice policies.
In every one of the Making Connections neighborhoods, large shares
of the elementary school students who live in the neighborhood attend
schools outside the neighborhood (and, presumably, the schools inside
the neighborhood serve many students who live elsewhere). This means,
for instance, that improvements in the academic proficiency scores of
neighborhood children may be explained as much by advances made by
actors outside the neighborhood as by the programmatic efforts within
the neighborhood. This research on schools reinforces awareness of a
reality that exists for many other services in community initiatives (e.g.,
financial counseling, job placement services)—namely, that it is challenging
to precisely align service populations and neighborhood boundaries.
In most communities, in-depth, longitudinal data on mobility and service
area differences are not available. 24 The lack of complete data, however,
does not mean that these issues cannot be thoughtfully considered in
assessment and decisionmaking in community development. When stakeholders
review trends in neighborhood outcomes, as pointed out above,
the influence of mobility is too important to be ignored, and it does not
have to be. National and administrative data sources, such as the American
Community Survey, can offer clues about residential movement, and
focus groups and interviews can reveal some understanding of its composition.
Even with such imperfect knowledge, fruitful discussions are possible
exploring the implications of what initiative leaders know from qualitative
and quantitative sources in relation to an initiative’s logic model.
Furthermore, there are prospects that richer data on neighborhood
change dynamics may become available at reasonable cost in the future,
not from surveys, but from more effective exploitation of administrative
datasets. There were hints of this in the TTM experience, and there are
more in the early implementation of the Promise Neighborhoods program,
which we review next.
Intensive Data Use in Program Planning and
Implementation: Promise Neighborhoods
As noted in chapter 2, Promise Neighborhoods is a US Department of
Education program modeled after the well-known Harlem Children’s
Zone [documented by Tough (2008)]. The founder of that effort,