Information and Spatial Technologies and the Inner City

Democratizing Information

DAPA's overriding goal is the democratization of information--providing a fact base to poor people, poor communities, and their collaborators who have been historically denied access to that vital information base, and helping to build the capacity of community residents. This is a revolutionary idea, and one that is sometimes controversial among traditional governmental agencies.1 Several trends in American society make the "democratization of information" almost a necessity. They are: devolution, the change in the locus of initiation for local programs, the change in the locus of computing power, and the need for a fact base for local program planning and management. No matter what the outcome of the forthcoming presidential elections, one thing is sure: there will be more bipartisan support for devolving social programs to the local level. In order to be able to handle these responsibilities, local actors will need an information base upon which to act. Targeting teen pregnancy programs is nearly impossible without first capturing and processing the data that give detail on the most at-risk populations, where they are located, what works to change behaviors, and how resources can be most effectively used at the local level. Second, the responsibility for local initiatives is moving to go way beyond simply relying on local governments. There are new collaborations between non-profits, community development corporations, neighborhood and metropolitan-wide community groups, business groups, and community foundations. The new theme has become "government participation in citizen initiatives," and collaboration among these groups, and between these groups and local governments. Third, the locus of computing power and data access is broadening. The use of information technology and spatial analysis is widespread. However, the level of skill required to turn raw data into information useful for policy analysis remains in the hands of a small, trained group of professionals. This remains true despite the fact that hardware and software have become so much cheaper and easy to use that the pool of potential policy analysts has grown dramatically. To democratize information fully, the locus of applications must move closer to the citizenry. Finally, local leaders of all types are recognizing the need for a much improved information base to help them in designing strategies and implementing them effectively and efficiently. The traditional measures of city or county well-being are being replaced by more localized, neighborhood measures because it is at that scale that problems get attacked. And information provided by single purpose agencies is deemed inadequate as problems are now viewed as multi-dimensional, and incapable of being understood from one dimension (e.g., police arrest data in the absence of school or social service data). Information resources, then, must collect data from dozens of governmental and non-governmental agencies. But this kind of data and information agency has never existed in metropolitan areas until quite recently. The Atlanta Project's Data and Policy Analysis, along with a handful of other organizations like it in other cities, has pioneered the way.

Goals and Objectives of DAPA

As stated above, DAPA's overriding goal is democratizing information to poor communities and their collaborators. More specifically our objectives include: providing information, spatial and non-spatial data, data interpretation, base maps, intelligent (analytical) maps, policy analyses and policy research to:

• TAP collaboration centers, their staffs, and their volunteers
• corporate sponsors
• other TAP team members
• non-profits working in poor area's in Atlanta
• university faculty who share TAP's mission
• governmental units needing local data and analysis
• media reporters
• other poverty research organizations, both local and national

We can roughly divide our activities into four categories: support for operations, support for planning and community development, policy analysis, and policy research. We will briefly describe the four: Support for operations. These tasks are usually small. Someone needs to know how many of this kind of person or household resides in a specific geographic area, or they need a data table or map. Support for planning and community development. We are moving as much analytical firepower into the hands of those doing neighborhood planning (including community development corporations) as is possible. DAPA staff have attached three electronic databases to digitized parcel maps for over 200,000 land parcels in the poorest part of the metro area. Each land parcel is described by over 100 fields. These include tax-delinquency, building condition, ownership, assessed value, frontage, land use, zoning, code violations, and much more. We are using the GIS tool with neighborhood and community development corporation leaders to query the database, make maps, and help plan for housing, development and community renewal. Policy analysis. DAPA is asked often to comment upon a proposed project or a piece of legislation under development. We use our inventory of databases and reports to inform those who raised the question. We also tap a national network of researchers and publications to bring the experiences of other organizations to bear on our situation. Policy research. Many problems in poverty or urban policy are complex, and differ from one geographic area to another. On some topics DAPA does leading-edge policy research, joining with other research organizations to understand the problems at a deeper level. An edited list of clients and projects is available from the author.

Microcomputer Technology at DAPA

DAPA possesses advanced data processing and geographic information systems capability as well as a vast library of relevant information we are able to offer clients. DAPA uses microcomputer technology which includes: tape and CD ROM readers, color printers and plotters, a large digitizing tablet, and a substantial collection of software, including a geographic information system. But, more importantly, we have a highly-qualified technical staff, composed mostly of graduate students, and a valuable collection of both geographic and attribute data. In addition to the land-parcel geographic information system described above, now worth well over $200,000, DAPA has in its library all of the U.S. Census data products from the 1990 census. Some additional examples of its other database holdings follow:

• over 1 million crime records
• birth and (linked) death records with detailed characteristics of mother
• juvenile justice system data
• data on 60,000 Atlanta Public School students
• addresses of all businesses by type
• locations of all social service providers

Proposed Research Activities That Could Enhance Inner-City Redevelopment

My approach will be to divide my proposals into two types. The first are ideas that could enhance, expand, and support the work of organizations like DAPA in the inner cities of the United States. These organizations are capable of bringing profound changes to the delivery of human services to disadvantaged populations, and aiding in the redevelopment of inner-city neighborhoods. Operational parcel-level GIS's can play an important role in the latter. The second set of proposals are more broad-ranging research ideas that focus on jobs and inner-city poverty and the role of new technologies in either aiding or exacerbating those problems.

Support For Enhancing Local Spatial Data and Policy Analysis

We should begin by noting that The Urban Institute has completed the first (planning) phase of its "National Neighborhood Indicators Project." The Institute is currently developing a number of proposals for funding various activities subsumed under the NNIP umbrella.2 The emphasis of the Institute's effort is, however, on indicators, not necessarily on helping to support ongoing activities of DAPA-like organizations. Clearly, we need some dialog with the NNIP project leaders. That said, to enhance the ongoing local efforts, we need to do the following:

• Analyze the efforts of the (say four) most successful community-based spatial and policy analysis organizations, and develop a model for self-sustainability. This is difficult since their avowed mission statement is analysis in support of poor communities.
• Develop an incentive system which encourages community groups and their analytical arms to post electronically (locally and nationally) success stories which highlight their work with spatial and information technologies. "Success" in this context means effective implementation after analysis, that helps to make people's lives better. Collected cases might, in fact, lead to a book.
• Develop an issue-based index to data. For example, a community worried about crime might search the index and be pointed toward cases where police call data were manipulated to help make improvements in neighborhood security.
• Work towards the development of a prototype neighborhood database which uses administrative data along with independent survey research to supplement the decennial census, which is the only rich data source available for small geographic areas. Without intercensal small-area data it is difficult to judge change and to develop intercensal rates because a timely estimate of the denominator is missing (e.g., how many teenage girls were at-risk to becoming pregnant given there were 150 teenage births in this neighborhood?).

From my perspective, three issues stand out in the discussions about inner-city poverty and its relationship to space. They are:

• There are too few employment possibilities at a reasonable location, wage, and skill level, to permit the urban poor and near-poor to lift themselves out of poverty. The urban poor are concentrated in the nation's central cities. Without income, the places where these poor reside sink into disrepair.
• The concentration of poverty is in itself a problem, especially for children. Locked in schools with peers of similar circumstances, in families often without education and resources, and in neighborhoods without successful role models, children at very young ages become attached to unconventional and unproductive life styles.
• There is a growing consensus among urban scholars that almost forty years of failed urban policy prove that the ghetto cannot be improved comprehensively. Policies and practices, as well as "natural" market forces, that concentrate the poor in spatially separate neighborhoods within metropolitan areas must be challenged.3

• The mismatch between appropriate jobs and unemployed and not-in-the-labor-force (NILF) people is somewhat overrated as a cause of joblessness. There are other important factors, most more difficult to measure than physical accessibility.
• Information technology in the hands of undereducated people not placed in a rich learning environment is not worth much. The topic of haves and have-nots on the information superhighway is overplayed. Most importantly, the poor are have-nots in wealth, health, and education; secondarily, they may not have access to the superhighway.

• Poor minorities do not generally participate in a rich job information network. Artificial networks must be substituted. Analyze and offer ways to improve electronic job networks and ways to improve poor people's access to those networks.
• Up to date, geographically-specific as well as SIC- and SOC-specific employment data and information seldom exists for metropolitan areas. The smallest reporting unit is the county. White4 and a few others have used the state labor department's ES202 unemployment insurance dataset very creatively for monitoring changes in the patterns of job growth and decline in a metro area. We need to build upon his success and help clone it in other metropolitan areas. It sounds easy, but there are many roadblocks, both technical and political.
• Scholars disagree on whether immigrants harm the chances of U.S. citizens for employment and higher wages. Frey has shown that metros with large immigrations experience high out-migrations of their less-educated.5 Sawicki and Moody have shown that high in-migration to Atlanta has created a very competitive job market for native (not moving in the last five years) less-educated black males, who do very poorly in the job market.6 We hope to extend this research to other metropolitan areas including those with high out-migration, immigration, and in-migration.
• In the Atlanta case (above), we observed that less-educated in-migrants to Atlanta chose residential locations that were much closer to new entry-level jobs than did Atlanta natives. We hope to extend this research to other metropolitan areas including those with high out-migration, immigration, and in-migration.
• New logistics technologies (e.g., ubiquitous bar-code readers and inventory software) are changing the way goods and services are produced and delivered. This results in shorter product life cycles, smaller order quantities, more agile manufacturing, less face-to-face interaction, more telecommuting, and just-in-time production. Logistics systems must move, store, and control more materials and information than ever before. These changes have serious implications for the locations of manufacturing and service producers, and for the types of people they employ. Central cities could suffer as historic sites for transfer terminals and personal interaction are made outmoded by modern technology. Research on the interface between changing logistics technology, changing processes of production and its location, and their impact on employment and jobs seems essential.7
• Michael Porter has been espousing the idea that the United States could be made more competitive if we recognized clusters of industrial activity as has been done in some successful examples in Italy, Germany, and Japan.8 The intent is to exploit the positive externalities, consumption interdependencies and economies of scale, to link together different firms in a cluster that becomes more competitive than if the individual firms were spread out. There are two major obstacles to operationalizing what appears to be a good idea. First, Porter has not offered much concrete advice on how to identify and define these clusters. Second, the roles of space and scale are undefined: do we mean located adjacent to one another, or within 50 miles? Changes in logistics technologies as described above could play a big role in delineating "clusters of the future." This promising area deserves attention.

In my role as technical advisor to The Atlanta Project I have witnessed the positive contribution that a data shop well-supplied with GIS technology could provide to local groups trying to make improvements to the lives of those in poverty. Thus my approach was to sketch what we do and recommend that we join others in trying to get as many of these organizations established as we can around the country. On the other hand, these attempts are mostly in the vain of "guilding the ghetto," whereas most now agree that to make meaningful change we must integrate the entire metropolitan area. I believe this is a political problem, important to, but removed from the NCGIA research agenda. What is important to that agenda is the creation of new jobs, their locations, their skill requirements, and their accessibility to those currently not employed or underemployed. Thus my second set of ideas relate to research on spatial technologies and jobs for the next century.

Notes

1. Three articles describe the work of organizations like DAPA in more detail. See David S. Sawicki and Will Craig, "The Democratization of Data: Bridging the Gap for Community Groups." Forthcoming in the Journal of the American Planning Association; David S. Sawicki and Patrice Flynn,"Neighborhood Indicators: A Review of the Literature and An Assessment of Conceptual and Methodological Issues." Journal of the American Planning Association, Spring, 1996, Volume 62 # 2, 165-183; and Ruth Knack, "Empowerment to The People." Planning, Volume 59, No.2, 1993.

2. See The Urban Institute's "Democratizing Information: First Year Report of the National Neighborhood Indicators Project," Washington, D.C.: The Urban Institute, March 1996.

3. See, for example, David Rusk's latest book, Baltimore Unbound: A Strategy for Regional Renewal. Baltimore: Abell Foundation, 1996. Rusk, like others, recommends a special purpose regional government. Among other duties it would be empowered to oversee a plan of regional housing integration. The governing board would be elected from pie-shaped districts, centered on the city's core. Rusk is among a cadre of the best urban policy scholars in America who have given up on ghetto-enrichment as a stand-alone strategy for solving the problems of urban poverty and its attendant side effects. See also Anthony Downs, New Visions for Metropolitan America, Washington, D.C.: The Brookings Institution, 1994.

4. Sammis B. White et al. "ES 202: The Data Base for Local Employment Analysis." Economic Development Quarterly, August 1990, Volume 4, No. 3, 240-253.

5. See, for example, William H. Frey, "The New Geography of U.S. Population Shifts: Trends Toward Balkanization," In State of the Union: America in the 1990's edited by Reynolds Farley, New York: Russell Sage Foundation, 1995, 271-355.

6.David S. Sawicki and Mitchell Moody, "The Effects of Intermetropolitan Migration on the Labor Force Participation of Disadvantaged Black Men in Atlanta." Forthcoming in Economic Development Quarterly.

7.This topic is contained in a recent proposal to the National Science Foundation I helped develop. The principal investigator is Professor Donald Ratliff. The senior author of the "Urban Logistics" section was Professor Amy Helling.

8.David S. Sawicki, "Deja-Vu All Over Again: Porter's Model of Inner-City Redevelopment," with Mitch Moody. Forthcoming in The Review of Black Political Economy.

Draft Version 5/13/96 David S. Sawicki

Biography

David Sawicki, a Georgia Tech Professor of Planning and Public Policy was named Senior Advisor for Data and Policy Analysis (DAPA) of The Atlanta Project (TAP) in the summer of 1992. First alone, and then with a small student staff, he established DAPA as a prime source of spatial data and policy-relevant information for those working with poor communities within The Atlanta Project area of 500,000 in Atlanta. Over time, the staff has grown as has its list of responsibilities and clients. DAPA is now part of a national seven-city consortium, housed at The Urban Institute. The project title is the "National Neighborhood Indicators Project." The Institute will try to clone DAPA-like organizations in other poor communities in the United States. Dr. Sawicki is the lead person for the Atlanta (TAP) NNIP site, and a consultant to The Institute on their national NNIP activities. In this brief research note he will attempt to accomplish two things. First, he will reflect on his recent experience at DAPA and propose how modern spatial and information technologies could be used to aid inner-city redevelopment. Second, based on his experience in poor communities, he will propose several research agendas centered on changing technologies and their impact on poor communities.

David Sawicki
Professor
Georgia Tech
City Planning and Public Policy
770-436-7283 (h); 404-894-0569 (o); 404-894-1628 (fax)
DAVID.SAWICKI@ARCH.GATECH.EDU

Senior Advisor
The Atlanta Project Data and Policy Analysis Group
404-881-3400 ext 342; 881-3477 (fax)