Rural Data, People, And Policy

Information Systems For The 21st Century

Lis M. Maurer, Nancy Strang, James A Christenson

• Publisher: Routledge
• Year: 2019
• Print ISBN:
  9780367286262
• eBook ISBN:
  9781000310344
• Topic: Social Sciences
• Subtopic: Sociology
• Index: Social Sciences

This volume paints a critical view of the state of rural data systems in America with a collection of contributions leading scholars in the social sciences arena. It places an important wake-up call social scientists engaged in rural research, alerting them to the problems of existing data systems.

PART ONE
The Politics of Data

Because data drive policies, lack of information often results in nonresponsive or biased public policies. The first three chapters suggest that the methods we are using to gather and interpret data are insensitive to the diversity and needs of Americans living in our hinterlands. Data are political, perishable, and permanent. We suggest how federal and state agencies and public universities can work together to create a more appropriate information system for developing a policy agenda sensitive to rural needs and circumstances.

Rural policy often has been a matter of personal antidotes, political expediency, and institutional neglect. Without a rural information system to capture and highlight rural situations, antidotes and expediency will perpetuate past neglect.

Data drive policy, but people interpret what data are gathered, how they are processed, and whether they should be distributed. Information systems require data and interpretation. The philosophical discussion about and the theoretical needs for rural information systems provide the basis for the first three chapters of this book.

1
Rural Data Needs: The Comparative Advantage of University Research

James A. Christenson and Edwin H. Carpenter

This book is concerned with rural people and communities and how we gather and interpret information about them. Current methods of gathering and interpreting data are not sensitive to the diversity and needs of people living in America's hinterland. National data-gathering efforts have inherent biases that are rooted in the methods of data collection and analysis and the approaches to interpretation. As a result, the twentieth century has been marked by the failure of policies and programs directed at rural people and places.

Rural poverty is a good example of a national data system misrepresenting issues in rural areas. From census data we find that the average American household in poverty is headed by a single nonworking parent. However, data from rural America indicate that a household in poverty is made up of an intact family with both parents working (see Chapter 5). Data drive policy. Lack of data and the failure to develop an integrated information system based on available data can misdirect policy and undermine program intent. In the case of rural poverty, the gap in our knowledge about the characteristics of the rural poor and how they differ from the urban poor lead to public assistance programs that fail to address the needs of the rural working poor.

This book examines how the many players (federal and state agencies and public universities, especially land-grant universities) involved in data collection and the development of information systems can work together to create a more appropriate information base for developing a policy agenda for rural people and places sensitive to their particular needs and circumstances.

This book is guided by three themes. The first theme is complementarity. How can research and related activities in public universities complement, extend, and reinforce national data and information systems? Further, how can they reorganize, refocus, and restructure data and information as they pertain to rural people and places?

The second theme is cooperation. How can academicians involved in research and related activities be encouraged to collaborate in interdisciplinary, interuniversity, and interagency endeavors to provide data and information required to inform rural policy. This book attempts to answer the following questions: What is the role of public universities in providing data and information on rural needs? What kind of rural data will be needed in the years ahead? What do the national data sets reveal about rural America and what can't they reveal? In what areas do public universities need to provide information to complement, extend, and reinforce national research efforts? In what ways can the new microcomputer-based tools be used to collect data, turn data into information, store and update the information, make retrieval of the information as easy as asking a question, and display the information spatially using geographical information systems (GIS)?

The third theme of this book is responsiveness. American society is becoming more urbanized and less responsive to the needs of "uncounted" Americans. Rural Americans do not show up in most counts. Part of the problem is that information from national data systems is adequate for urban policy but of limited value for informing rural policy. For a particular rural place or area, data from national data sets are either too sparse to draw reliable conclusions or unavailable, except as part of a larger picture, to assure the anonymity of individuals from low-density population areas. This latter situation, known as "aggregation," is required by law to protect the privacy of individuals in the data set. The result of these inadequate data is a pronounced lack of responsiveness to the needs of rural Americans. If data are not available, then it is virtually impossible for anyone to mate a persuasive case that informs policy. Increased responsiveness, then, is highly dependent on data and information systems that can represent rural people, places, or areas. Such data can be provided by using increasingly automated primary-data collection and analysis technologies, which are fast and easy to use (see Chapters 9-11).

This book does not seek to criticize ongoing national data and information systems. Such systems have a role in charting and monitoring the state of the nation, which is predominantly urban. However, these national information systems, most of which emanate from the Bureau of the Census, are limited by the conceptual basis of their counting procedures—a conceptual basis that was conceived in fee 1930s for different people, places, and times. And they are mandated by a mission to provide information systems that monitor and project certain conditions for all of American society, rural and urban.

The federal agencies, with guidance from the Office of Management and Budget and other groups, appear to be performing roles within die constraints of their funding bases and missions. This is not to say, however, that all is well at the federal and state levels. Much of the information processed is not relevant to the evolving problems of today. And, federal agencies have been less than eager to create cooperative endeavors with state and university researchers in monitoring or studying unique conditions or changing situations.

What Kind of Rural Data Do We Have?

The data that serve as the basis for most decisions by federal and state governments are found in our national longitudinal data sets. These are the best, and virtually the only, information systems available. These systems include the National Longitudinal Surveys, Panel Study of Income Dynamics, Survey of Income and Program Participation, Census of Population, and many others (Chapter 4). However, these systems are limited in their applicability to rural areas and in their ability to provide geographical specificity. Likewise, while national longitudinal studies are able to provide valued information over time, they are not responsive to changing times. The lack of responsiveness stems from the fact that the studies are historically mandated counts of people that have not been altered to meet the evolution of the problems and concerns that afflict rural people and places.

State government data are unsystematic. A few slates, such as Wisconsin and Pennsylvania, have developed excellent information systems and some cities, like Phoenix and Cincinnati, have made major strides in information systems, especially GIS, but most states and cities do not have a system at all. In most states and cities, little liaison exists between universities and state agencies in developing information systems. In fact, most states and cities focus on gathering data for cities and are much less concerned with rural implications.

Public university data systems are an embarrassment. In colleges of agriculture and other mission-oriented sectors of the university, a lot of data are gathered. Some date are routinely transmitted to state and federal agencies, but this is clearly the exception rather than the rule. Academic research is, for the most part, individualistic and opportunistic. Data gathering is labor intensive and expensive. Most university professors do not want to spend the time nor do they have the financial resources to generate data. Instead, they use existing data or simulate model data, which tend to be disciplinary bound. We may be moving beyond this narrow base because the national funding agencies and foundations are encouraging interdisciplinary research and interdisciplinary programs. But only in time will we know how strong their commitment is to interdisciplinary efforts. Besides the five Rural Development Centers and a few regional research projects, little interstate or interuniversity research is performed. In short, we have the existing national longitudinal information systems, and we have a smorgasbord of state and university efforts. Specifically, there is no university-based rural information system that informs either the federal or state governments.

Problems with Existing Rural Data

Longitudinal data are desperately needed to monitor and interpret rapidly changing conditions in rural areas. Rural areas are heterogeneous, belying the aggregate comparison so often applied. Rural problems are complex, both spatially and contextually. We need to know more about the variety of activities (human, social, economic, and environmental) occurring in rural places. And, we know that rural places are very different from urban places. Contextually, rural areas offer a unique laboratory to assess what is going on, what is working, and what is not working in different parts of the country. These kinds of contextual studies are not possible in ongoing longitudinal national data efforts. In addition, many of the concepts central to ongoing national systems are questionable to the extent of the phenomena under study. We only have to ask what is a farm, a standard metropolitan area, a household, or poverty to launch a lively discussion.

Second, we lack primary data. Most university research efforts are shotgun projects with considerable variability in the quality of data, in the procedures utilized, and in the compatibility with any other ongoing efforts. The last three chapters discuss methodological, conceptual, and statistical standards to address such problems.

Third, we lack qualitative insight. At times, we become so accustomed to counting and using the computer that we forget the situation in rural society is changing. Our perception of rurality may be colored more by myths and assumptions than by what is really going on. We need to listen to people. We need to critically assess our assumptions and values in light of the words and actions of real people when interpreting data and formulating our agenda (see Chapter 8).

Finally, we lack panel data on individuals in a rural context (see Chapter 6). The Survey of Income and Program Participation (SIPP) and other information systems do have individual-level data, but without controls on rurality. We have similar problems in many ongoing data systems because of sample size, geographical specificity, or conceptual design.

Problems in Obtaining New Data

Costs, standards, technology, political constraints, and lack of appreciation inhibit efforts to generate rural data systems. At the national level, costs are clearly a major deterrent to broadening existing information systems to include rural information needs. Likewise, at the state level, it is difficult to generate new funds for information systems that are sensitive to rural areas if such systems are not already in place. Since most states have little existing data on rural areas, new information systems are often pipe dreams. Once an information system is in place, the likelihood that it will be maintained over a long period is very low. Information systems are often among the first programs to get the budget axe when economic times are difficult.

For many in the university research community, standards and coordination seem to be an irrelevant concept. People receive so many surveys from so many different sources, sometimes from different disciplines within the same university, that they cannot reasonably respond to all of them. There have been more than a dozen farm polls conducted simultaneously in the United Sates, each using a completely original set of questions and response categories. Mail surveys of the public vary greatly in their response rates, from as low as 35 percent to as high as 75 percent. Lack of coordination is clearly evident in university studies. We need university-wide or interuniversity standards on sampling, survey response elicitation techniques, questionnaire design, measurement scales, and background information questions. But, more important, we need standards that address comparability and compatibility among research projects and programs, without which we cannot build cumulative information systems (see Chapter 10). For example, questions on household income or the amount of education completed should have comparable response categories across surveys.

Technology provides increasingly better ways to gather information effectively. The social science research process can be likened to the physical science research process of years ago. For example, a few decades ago gas chromatography was accomplished by a laboratory full of technicians and equipment—very similar to the social science research process of today. However, the physical sciences bow have a black box, known as the "gas chromatograph," that takes the place of the lab full of technicians and equipment. Simply stated, to determine the chemical mate-up of a substance, one merely has to insert a sample in the gas chromatograph and wait for the result. The social science research process eventually may be automated in a similar way.

Today, many steps in the social science research process can be computerized (like computer-assisted interviewing) and linked so that it takes only a few minutes from the time of the last interview to when the findings are presented. However, knowledge of new procedures to gather and process information is lacking across social science disciplines. We tend to conduct research the way we were taught in graduate school. The lack of common methodological and statistical standards in gathering and analyzing rural data continues to plague academic research. Transferring social science technology to those who could make the most use of it is slow. The third section of this book addresses these issues.

Little support exists for building information systems, We seem to be driven by the need for data rather than the need for information. Data are raw information that need a conceptual basis before they can be treated as information (see Chapter 2). There appear to be few systematic efforts within disciplines, across disciplines, or between levels of government and universities. Each researcher wants to do his or her own thing, precluding the possibility of building data into an ongoing information system. Insensitivity to this issue frustrates efforts to build a rural information system; however, the situation may be changing.

One of the impediments to forming and maintaining information systems has been the cost of the hardware, software, and personnel to mate such a system work. Inexpensive microcomputers, easy-to-use software (such as search and retrieval systems), and inexpensive massive storage capability in the form of read/write optical disks, compact disks with read-only memories (CD-ROMs), and gigabyte hard drives provide new opportunities for the development of information systems, including those that will inform rural policy. The most difficult part is providing fee information that will go into the system, updating the system, and providing easy access to the contents of the system. For example, Internet, which links university computers around the world, is a possible starting point for providing access to an information system that resides on a microcomputer at a university site.

This new technology opens the way to systematically analyze and evaluate text-based information that relates to policy in rural America. Such a capability opens the systematic inquiry and tracking of government documents, legal opinions, research reports, and any other text items that have been prepared over the years. If these new information-archiving procedures are activated to analyze historical and contemporary textual information relative to rural policy, then we can forge ahead with new insights from a historically grounded context.

How to Improve the Rural Information System

First, to improve the rural information system, we must make existing national information systems more accessible, more flexible, and more sensitive to the heterogeneity of rural areas. Clearly, concepts such as "rural" and "form" need both conceptual and methodological clarification. Disaggregation of information systems for geographical specificity is crucial.

Second, primary information is needed to expand and build national information systems so they can be responsive to rural needs. Likewise, new data generated in state studies should be de...

Table of contents

• Cover
• Half Title
• Series Page
• Title
• Copyright
• Dedication
• Contents
• Foreword
• Acknowledgments
• PART ONE The Politics of Data
• PART TWO Data for Rural Information Systems
• PART THREE Technologies for Rural Information Systems
• Epilogue
• About the Editors and Contributors
• Name Index
• Subject Index