Neighborhood associations and community development: Differences in needs and strategies

ABSTRACT

Neighborhood associations (NAs) help build social capital, enhance a sense of community, and elevate civic engagement. While urban researchers have studied NAs, there has been limited systematic observation of alliances of NAs. This research examines how neighborhood alliances (NALs) facilitate the creation and expansion of community capital that impact grassroots governance. We examine six NALs in Omaha, Nebraska that represent more than 120 active neighborhood associations. We find that participation in NALs is a good first step with respect to building social and political capital. Nevertheless, these NALs have yet to fully utilize this capital in the pursuit of resource sharing endeavors that cross multiple networks. More effort, therefore, is needed in the cultivation of the bridging and linking functions of community capital. For NALs to be construed as viable political actors, significant attention must be allotted to the development of generalized trust across NAL geographical boundaries.

KEYWORDS:

• Neighborhoods
• citizen participation
• capacity building
• community-based organizations
• social capital

Acknowledgments

The authors want to thank Mr. Jerome Deichert, the former director of the Center for Public Affairs Research at the University of Nebraska at Omaha, for his assistance in this research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. The Benson-Ames Neighborhood Alliance has since ceased to exist at the time of this writing.

2. No boundaries were specified for SWONA. Through the process of elimination, its area was determined as being south of NWONA and west of Midtown and SONA.

3. Had a different process been used, it would not have been possible to collect tract-level data for some alliances (e.g. Midtown and Benson-Ames).

4. An average calculation is not necessary for the city-level variables, as there is only a single estimate.

5. Because of excessive multicollinearity, a full model utilizing all of the significant predictor variables could not be calculated.