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Sharing Research Data in the Social Sciences Jerome M. Clubb, Enk W. Austin, Carolyn L. Geda, and Michael W. Traugott Dunng the past two decades an extensive literature has appeared exploring issues related to access to basic computer-readable data for empirical social science research. In the main, the authors of this literature emphasize the scientific, public policy, and pedagogical values and advantages of data shar- ~ng, and they often advocate a policy of open access to data in maximally us- able form. Obstacles to data sharing are discussed, specific categories of data are noted as exceptions to the general sharing Nile, arguments against com- plete open access to research data are sometimes offered, and the precise na- ture of obligations to share data are debated, but few if any of the authors cate- Jerome M. Clubb, Erik W. Austin, Carolyn L. Geda, and Michael W. Traugott are at the Inter-university Consortium for Political and Social Research, Center for Political Studies, Institute for Social Research, University of Michigan. An earlier draft of this paper was discussed at length by Stephen Fienberg, Clifford Hildreth, Margaret Martin, Miron Straf, Joe Cecil, and Terry Hedrick. Although we were unable to meet all of their many comments and suggestions, this paper has benefitted greatly from their efforts. We alone, however, are responsible for its shortcomings. 39
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40 Jerome M. Clubb et al. goncally oppose data sharing or some form of open access. These same two decades have been marked by movement among social scientists toward implementation of the general principle of open access to ba- sic research data. Institutional mechanisms have appeared to facilitate access to data, and venous agencies that fund research in the social sciences have stressed that the resultant data collections should be made available to other researchers. One consequence of these developments is that abundant, if somewhat unsystematic, concrete evidence of the value of open access to ba- sic research data is now available. At the same time, however, discussion and disagreement continue, and ac- ceptance and implementation of the general principle of data sharing are far from complete. Social scientists are still often refused access to data, or if ac- cess is granted, copies of data are sometimes received in technically unusable form. In some cases data are shared, but only after prolonged delay. In oth- er cases data are shared only within relatively limited networks of researchers, often within a single discipline or subdiscipline. Access to data by people outside such networks is either difficult or precluded. Difficulties in gaining access to data are not simply the product of unwillingness of researchers and research groups to share, but also result because mechanisms to provide infor- mation about the availability of data, and particularly mechanisms that oper- ate across disciplinary boundaries, are not yet well developed. It is only in very recent years, for example, that concerted efforts to develop bibliographic control over computer-readable data collections have begun, and there is as yet no centralized reference service for computer-readable social science data. Failure to move more rapidly toward acceptance and implementation of the principle of open access to basic data is sometimes asserted to be a reflection of the supposed transitional nature of the social sciences—from essentially lit- erary values, with their emphasis upon private and unique individual creativi- ty, to the scientific values of public and cooperative pursuit of cumulative knowledge. In our view such an explanation is neither particularly useful nor accurate. If it were accurate, other areas of inquiry would also have to be seen as transitional in nature, since difficulties and disagreements concerning access to data and to data collection facilities are also encountered in other sciences. In our reading much more obvious and, in some respects, more useful explanations are also available. First, there are serious concrete tech- nical obstacles to effective data sharing, although at least some of them could be readily overcome. Second, there are reasonable arguments against a gen- eralized norm of data shanug and against complete open access to research da- ta, arguments that reflect conflicting values and goals as well as the reward structure characteristic of science. These issues constitute the most serious obstacles to data sharing. In this paper we examine the issues confronted in sharing basic social
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Sharing Data in the Social Sciences 41 science data. The initial section summarizes scientific and other values and advantages gained through open access to data. The second section provides an indication of the magnitude of data sharing that now occurs. The third sec- tion considers technical obstacles to generalized access to basic data in usable form and suggests means by which some of these obstacles might be over- come. The fourth section considers further arguments against data sharing and the conflicting values, goals, and obligations that seem open to underlie disagreement and discussions of data sharing; for these, solutions that go sig- nif~cantly beyond continued exhortation are less easily identified. The fifth section considers modes and facilities for data sharing, and the sixth section briefly considers practices of data sharing in several other areas of inquiry. We offer conclusions and recommendations in the final section. This paper has a number of limitations that should be made explicit. Data-sharing practices vary rather widely in the social sciences, and it is un- likely that the full range of this variation has been adequately taken into ac- count. While data-sharing practices in several rather specific areas of the na- tural and biomedical sciences are examined, this examination is somewhat un- systematic and far less than complete. To explore in anything approaching comprehensive fashion questions of data sharing and access to data collection facilities in the many and diverse areas of the other sciences would be a major research undertaking in its own right. Thus we are able to offer here only a few highly tentative generalizations. There are a very large number of organizations and facilities in the academ- ic, government, and private sectors that function in some way to share and provide access to computer-readable data relevant to social science research. Our discussion of these facilities is most complete for academically based or- ganizations; it is significantly less complete in the case of organizations in The public and private sectors. Our discussion of data-sharing practices and facil- ities is also heavily based on the United States; practices, facilities, and ex- periences in other nations are less to computer-readable data collected and processed more or less specifically to serve the goals of social science re- search and the purposes of monitoring social processes. We distinguish be- tween computer-readable data for research and computer-readable information of the sort found in data bases containing bibliographic citations and abstracts of published textual material. The latter are shared through many mechanisms and are outside the scope of this paper. There are similar questions regarding access to other categories of research source material, such as oral histories, and it is likely that somewhat similar principles and im- peratives would apply to these other categories of source material as apply to computer-readable data for social science research. The personal papers of statesmen, political, government, and other public figures constitute primary source materials for the research of historians and other social scientists as
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42 Jerome M. Clubb et al. well as of scholars of literature and the arts, and access to such materials is of- ten restricted and is at best uneven. However, the issues confronted in deal- ing with such materials are complex, controversial, and widely debated, and we have been forced to rule them outside the scope of the present paper. The operational records of government agencies and other organizations are also not considered in this paper. These records constitute research resources of very considerable value for investigation of social processes, and they are also of central importance for purposes of policy and performance evaluation and public accountability. Such records, moreover, are increasingly main- tained in computer-readable form so that transactions and activities are docu- mented in greater detail than formerly, and the records can also be manipu- lated for analytic purposes. However, these records fall within the purview of governmental, business, and other organizational archives that are today largely ill-equipped to manage them in their computer-readable form or to make them available for scientific use. A recent collection of essays (Geda et al., 1980) provides a useful summary of the issues and problems presented by these materials and calls attention to the risk of loss of major research oppor- tunities. These issues and problems are not reviewed in the present paper. VALUES AND ADVANTAGES OF DATA SHARING Beginning in the early 1960s, numerous books and articles have appeared that discussed the values and advantages to be gained through open access to basic social scientific data and that explore means for providing this access. Much of the early literature emphasized the impact of change in the technology of social science research. It was recognized that the social sciences were un- dergoing the introduction of complex technologies analogous in some ways to the costly instrumentation of the natural sciences. The consequences of this new technology were seen as providing abundant research opportunities, but these opportunities were also seen as accompanied by need for change in work practices and uneven access among social scientists to research resources and as interposing new obstacles to effective research. The advent of computer technology and its application to social science re- search meant Hat researchers had the capacity to manipulate large data collec- tions and to use complex methods of analysis in ways Hat previously had been virtually precluded. At the same time, however, researchers faced high costs for data collection arid for processing data to computer-readable form, uneven access to computational facilities and capabilities among social scientists, and the possibility and value of multiple uses of data collections. Hence the early literature emphasized need for mechanisms that would facilitate generalized access to data and to computational capabilities required for their use.
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Sharing Data in the Social Sciences 43 It also became increasingly clear that standard publishing mechanisms of- fered few effective solutions to the problems of access to research data: the size of research data collections, and the attendant high costs of publishing ba- sic data, precluded this option. Furthermore, publication of scientific re- search data that already exist in computer-readable form was seen to add an unnecessary and expensive loop to the process of data sharing: to be used ef- fectively in research applications, such published data must be reconverted to computer-readable form by each and every analyst who wishes to use them in research. Finally, in more recent years numerous observers have noted that the publishing of research results falls far short of satisfying goals represented by the term "data sharing." Few if any professional journals or monographs permit or encourage the depth of exposition of research data and methods that underlie reported research findings; it is therefore rarely the case that pu- blished research reports satisfy a reader seeking to evaluate the basic data and techniques used in a research investigation. Increased use of sample surveys as a primary mode of data collection con- stituted a furler impetus to data sharing. By the 1960s, numerous collec- tions of sample survey data existed, some of them dating to the mid-1930s, and the survey method of data collection had attained highly sophisticated form. It was clear, however, that mounting a large-scale sample survey was beyond the financial reach of most social scientists and, consequently, many researchers were increasingly disadvantaged. Again, the possibility of multi- ple research applications and the cumulative values of data from well- designed sample surveys was stressed. To realize new research opportunities and to capitalize on new technology required creation of new data facilities. These facilities were viewed, in some cases, as functioning analogously to the laboratories and the research in- stallations of the physical sciences. They would provide mechanisms to implement the obligations of original data collectors to share their data with other researchers. They would devise and implement standards for data col- lection and processing, contribute to the development of general-purpose computational capabilities, and provide training in new approaches to social science research. Some of these same themes continue to underlie much of the literature since the 1960s. (A partial list of the earlier and subsequent literature is provided in the references and bibliography section.) Like the earlier literature, subse- quent contributions to this general discussion explore a variety of more specif- ic advantages and values of generalized access to basic computer-readable so- cial scientific data. In view of this large body of literature, we need only briefly summarize those values and advantages here.
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44 Jerome M. Clubb et al. Replication and Verification Improved capacity to verify and replicate reported research findings is among the most commonly discussed advantage of generalized access to data. Obviously, use of computers and computer-readable data and increased use of large bodies of data that are costly to collect increase the complexity of venfi- cation and replication as compared with more traditional data sources and re- search methods. The costs of a major survey are large, and repetition of the survey for purposes of replication and verification of an original effort is usually precluded. Thus replication and verification can often be accom- plished only through access to the data from the original survey. In addition, many of the phenomena studied by social scientists are in some senses nonre- curnng. National elections are, of course, repetitive, but the specific con- texts and characteristics of elections van. As a consequence, findings based on data collected for one election often cannot be verified and replicated with data collected for a subsequent election. Hence, the values of verification and replication can often be served by access to the original data. The need for simple verification of research findings is frequently mini- rnized since fraudulent research reports are thought to be rare. The risks of datacollection or analysis errors are greater, and erroneous findings due to such errors are probably more common. However, there are also occasional reports of fraudulent research, some of them with continuing and even dire consequences. For these reasons the opportunity for verification using ori- ginal data is often seen as a vital element of the research process and as dictat- ing generalized access to data. Access to basic data is often seen as facilitating three somewhat different forms of replication of reported findings. One of these might be described as "exact" replication. In this case the same data and methods are used to deter- mine whether He same results are obtained. The second form replicates and tests reported findings using the same data but different analytic methods or assumptions. Both of these are obviously forms of verification and are some- times seen as particularly important when data and research bear directly on current social policy concerns. The third form of replication looks toward testing the generality of reported findings. In tills case data from different contexts national or temporal, for example are used to discover the condi- tions under which particular relations do or do not apply and, hence, to gener- alize research hmdings. Methodological Improvement Further values served by open access to basic data are improvement of mea- surement and data collection methods. In this view, the obligation to share data with other researchers subjects data and data collection methods metho-
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Sharing Data in the Social Sciences 45 dological improvement is encouraged. In somewhat similar fashion, the availability of extended collections of data is seen as holding benefits for the design of new data collection efforts: in opportunities for exploratory research to determine in differing contexts the adequacy of question wordings, unob- trusive scales, and indicators, leading to improved measures and measure- ment validation. Secondary Analysis The value of data collections for extended, or secondary, analysis is, of course, frequently discussed. The research potential of a welldesigned data collection is rarely exhausted by the original data collector, and data collec- tions usually have value beyond those for which they were originally de- signed. Thus data collections generally have multiple research applications. Moreover, the availability of extended collections of data provide a basis for realization of further values: in the possibilities of combining data, derived measures, or analytic results from diverse collections in order to address new research questions and in the comparative and longitudinal perspectives pro- vided by the availability of data collected at different times and in different places. Realization of the latter values, it should be noted, not only dictates that data be shared, but also that data be preserved and remain accessible for extended periods of time. Further values of data sharing for research are economic in nature and fol- low from opportunities for secondary analysis. Generalized use of data is be- lieved to reduce research costs. The ready availability of data means that re- searchers often do not need to collect data de novo but can pursue research interests and goals by drawing on existing data. In this way, duplication of data collection efforts and investments are reduced, and the research value of investments in data collection are more fully realized. Opportunities to carry out meaningful research are, in effect, democratized, and more social scien- tists are able to conduct research and contribute to the development of knowledge. ~ Generalized access to basic research data in readily usable form is also seen as serving a variety of additional values, including pedagogical ones. Original data are now frequently used in both substantive and methodological instruction at the graduate and undergraduate levels as well as, occasionally, at the secondary school level. Probably the best-known and most widely used examples of instructional applications of this sort are the SETUPS (Supplementary Empirical Teaching Units for Political Science) series deve- loped collaboratively by We American Political Science Association and the Inter-university Consortium for Political and Social Research. Twenty-one of these units have been prepared and more are now being
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46 Jerome M. Clubb et al. developed or are planned. Each unit includes a brief monograph that poses a substantive or methodological problem or set of problems and a specially tai- lored data file to address that problem. By using original data in this fashion, students are able to more directly experience the research process and come to better understand the empirical bases and the contingent nature of research findings. In a more general sense, instructional use of empirical data im- proves social scientific and numeric literacy and enhances students' critical capacity to evaluate the results of applications of social science methods, whether reported in scholarly publications or in the mass media. Ready access to data is also seen as holding values for public policy pur- poses. The availability of data facilitates and encourages use of empirical data in policy formation and evaluation and so improves policy. Ready ac- cess to data also means, in this view, a capacity to more rapidly address policy questions. Numerous illustrations of the values summarized above could be cited. Three somewhat diverse illustrations are touched upon here. One example is provided through research by James S. Coleman and his colleagues ( 1966) on the equality of educational opportunity. The second is taken from a quite different area of inquiry: research into the economic history of the antebellum Soup and the economics of slavery, carried out by Robert W. Fogel and Stanley L. Engerman and reported in Time on the Cross (1974~. In bow cases, the reported research engendered widespread debate and controversy, sometimes acrimonious, among both scholars involved in the areas of inquiry and others. However, because the original data on which the research was based were generally available, scholarly debate could often be conducted on empirical rather than purely speculative grounds.2 The underlying data could be explored and evaluated and the findings empirically tested and contested. The consequence in both cases was ~at, despite controversy, debate was of a higher order and more effectively conducted; weaknesses of original data col- lection and research were better identified, and new and potentially rewarding areas for furler research found. A third illustration is of a still different order and is provided by the American National Election Studies, which are directed by Warren E. Miller. These surveys have been conducted by He Survey Research Center and the Center for Political Studies of the Institute for Social Research (located at the University of Michigan) for each national election since 1952. Data from the surveys provide an incomparable resource for cross-sectional and longitudinal investigation of the formation and durability of political attitudes and of American political processes. In more recent years, moreover, similar studies stimulated in part by these studies—have been conducted in many other nations, including Australia, Austria, Canada, Denmark, Finland, France, Israel, Italy, Japan, the Netherlands, Norway, Spain, Sweden, He
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Sharing Data in the Social Sciences 47 United Kingdom, and West Germany. In some of these nations, their series now span well over two decades. The venous studies show marked similarity in theoretical foci, in the structure of questions and measures, and in other de- sign characteristics. Thus, taken collectively, the data from these surveys constitute a powerful resource for both longitudinal inquiry and cross-national comparison, and they also exemplify the advantages, for purposes of design- ing new data collection efforts, of general availability of data collections. Distinctions and Reservations While the values summarized above are recognized and stressed, discussions of data sharing also draw distinctions, both explicitly and implicitly, between different categories of data in terms of the importance of sharing and the obli- gations of researchers to provide access. Data collections that threaten priva- cy or place individuals or organizations "at risk" are usually seen as requiring special treatment, although such concerns were less frequently expressed in the earlier literature than they are now, and distinctions are also made in the case of proprietary data collected for the purposes of private enterprise. Issues of privacy and confidentiality and questions of proprietary data are dis- cussed in a subsequent section; here we are concerned with distinctions that center on such issues as the presumed intrinsic importance of data collections, the purposes they were designed to serve, and He relative ease with which particular categories of data collections can be replicated. Distinctions are often drawn between large-scale data collections, particu- larly sample survey data collected at public expense, and smaller bodies of data collected at personal expense. There is widespread agreement that the former category of data should be shared and made generally available in a timely fashion, although there is less agreement as to what constitutes "timely." Sharing smaller data collections, particularly those created at indi- vidual expense, is often seen as less important, and obligations to provide ac- cess to such data are considered less pressing. These distinctions seem to be based on the presumed lesser value of smaller data collections for the purposes of secondary analysis, the sources of financial support for data collection, and the greater ease and lower cost at which smaller data collections can be dupli- cated. A similar distinction is sometimes also made for data collected from published or other public record sources. The presumption seems to be that because the original data can be found in published or otherwise publicly available sources, they can also be collected and processed by the secondary user; consequently, sharing is less obligatory or useful. Further and more specific distinctions are also sometimes made in terms of the purposes data collections are intended to serve and their potential for af- fecting government, public affairs, and human life. Hedrick et al. (1978)
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48 Jerome M. Clubb et al. suggest, for example, the importance of general and immediate access to data collected for purposes of formulating and evaluating public policy. And their views might be extended to include other categories of data for applied social science research. Such data are designed to provide a basis for social pro- grarn and policy decisions, and their potential for directly affecting people's lives is great. Thus in this view there is greater need for rapid evaluation of data and for replication of analytic findings than in the case of data designed to serve the purposes of more basic social science research. Distinctions such as these may be useful and even necessary in pragmatic terms. Obviously, it would not be realistic to envision sharing and open ac- cess to all data collected by social scientists. However, distinctions of this sort may be difficult to implement in practice, and they may appear in conflict win the values and advantages summarized above. It is, after all, difficult to anticipate the potential secondary research applications of data collections whatever their size, focus, or content. Even data from the most limited case study, for example, can sometimes be combined with other data to provide a basis for more extended explorations. The view that data collected from pub- lic sources and processed to computer-readable form can be readily duplicated is at best only partly correct. Such data collection efforts usually involve large investments of time and energy, and to duplicate them is obviously wasteful. Of greater importance, data collections of this sort often draw on multiple sources, some of which may not be easily accessible, and often use complex derived measures and aggregations. Given the imperfections of the mechanics of citation, it is frequently impossible to completely identify pre- cise sources and methods and to reconstruct derived measures and indexes. Hence duplication of such data collections and replication and verification of reported findings are often difficult if not impossible. The recent controversy centering upon research reported by Martin S. Feldstein that shows social security as a disincentive to saving is a case in point (Feldstein, 1974, 1980; Leimer and Lesnoy, 1980~. In this instance, Me original sources from which the data were obtained were not as easily identified or available to others as was apparently assumed, and complex derived indexes could not be readily reconstructed. Because the data were not shared, He process of replicating and verifying the reported findings was slowed, a programming error Hat marred the original analysis was not more promptly discovered, and effective debate and evaluation of the findings were delayed. It is likely that few people would contest the importance of early and gener- al access to data explicitly designed to provide a basis for policy formation or evaluation or for social action. However, to argue that access to data for more basic research is of lesser importance presents difficulties. It is worth noting that Isaac Ehrlich's research on the deterrent effects of capital punish-
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Sharing Data in the Social Sciences 49 meet, one of the controversial recent examples of contestable research with immediate policy consequences (Ehrlich, 1975; Bowers and Pierce, 1975; Passell and Taylor, 1975) was apparently not commissioned to provide a basis for policy decisions. The capacity to predict that particular research will or will not have policy consequences is far from perfect, and it is plausible to, argue that most research has the potential for policy consequences. It may well be that for practical reasons distinctions such as discussed in this section must be made. However, the values and advantages of general and timely access to data appear commanding, and the rule should be, it would seem, to err on the side of these values and advantages rather than to move prematurely to distinctions. INCIDENCE OF DATA SHARING The importance and value of data sharing in the social sciences can be ~llus- trated in a number of concrete, albeit somewhat unsystematic, ways. As will be noted at several points below, nothing approaching comprehensive infor- mation is available documenting either the incidence of data sharing or the multiple use of data collections. Several illustrations indicate, however, that very considerable sharing occurs and that data sharing is one of the vital un- derpinnings of research and instruction in the social sciences. The illustra- tions below also suggest that significant progress has been made toward real- ization of the values summarized in the preceding section. Social Science Data Archives Data sharing occurs in a variety of ways, including informal sharing among individual scholars and research groups as well as through organizations that function as data repositories and dissemination services. Indeed, one indica- tion of the importance of data sharing is the development in the United States and other nations during the past two decades of numerous organizations that serve as mechanisms to provide general access to the basic data of social science research. These facilities include national indeed, international "social science data archives" in the academic sector, venous private organi- zations that provide access to data, as well as organizations that maintain and disseminate data collected by government agencies. In addition, numerous local facilities maintain data collections, usually obtained from national data organizations, for use by a particular university community, government agency, or private firm. (A selected list of data organizations appears as the appendix to this paper.) The existence of these facilities and the resources in- vested in them suggests, of course, the value and importance of data sharing and multiple use of data collections.
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78 Jerome M. Clubb et al. Machine-Readable Archives, Public Archives of Canada, 395 Wellington Street, Ottawa, Ontario, Canada K1A ON3 Machine-Readable Archives Division, (NNR), National Archives and Records Service, Washington, D C. 20408 National Center for Education Statistics, Data Systems Branch, 205 Presidential Building, 400 Maryland Avenue, S.W., Washington, D.C. 20202 National Center for Health Statistics, Scientific and Technical Information Branch, Room 1-57 Center Building, 3700 East-West Highway, Hyattsville, Maryland 20782 National Center for Social Statistics, Office of Information Systems, Washington, D.C. 20201 National Opinion Research Center, University of Chicago, 6030 South Ellis Avenue, Chicago, Illinois 60637 National Technical Information Service, U.S. Department of Commerce, 5285 Port Royal Road, Springfield, Virginia 22151 Northwestern University Information Center, Vogelback Computing Center, Northwestern University, Evanston, Illinois 60201 Norwegian Social Science Data Services, Universiteet i Bergen, Christiesgate 1~19, N-5014 Bergen-University, Norway Oklahoma Data Archive, Center for the Application of the Social Sciences, Oklahoma State University, Stillwater, Oklahoma 74074 Polimetrics Laboratory, Department of Political Science, Ohio State University, Columbus, Ohio 43210 Political Science Data Archive, Department of Political Science, Michigan State University, East Lansing, Michigan 48823 Political Science Laboratory and Data Archive, Department of Political Science, 248 Woodburn Hall, Indiana University, Bloomington, Indiana 47401 Project Impress, Dartmouth College, Hanover, New Hampshire 03755 Project TALENT Data Bank, American Institutes for Research, P.O. Box 1113, Palo Alto, California 94302 Public Opinion Survey Unit, University of Missouri, Columbia, Missouri 65201 Roper Public Opinion Research Center, Box U-164R, University of Connecticut, Stores, Connecticut 06268 Social Data Exchange Association, 229 Waterman Street, Providence, Rhode Island 02906 Social Science Computer Research Institute, 621 Mervis Hall, University of Pittsburgh, Pittsburgh, Pennsylvania 15260 Social Science Data Archive, Laboratory for Political Research, 321A Schaeffer Hall, University of Iowa, Iowa City, Iowa 52240 Social Science Data Archive, Survey Research Laboratory, 414 David Kinley Hall, Urbana, Illinois 61810 Social Science Data Archive, Box 596, University of Notre Dame, Notre Dame, Indiana 46556 Social Science Data Archives, Department of Sociology and Anthropology, Carleton University, Colonel By Drive, Ottawa, Ontario, Canada K1S SB6 Social Science Data Center, University of Connecticut, Stom, Connecticut 06268 Social Science Data Center, University of Pennsylvania, 353 McNeil Building, CR, 3718 Locust Walls, Philadelphia, Pennsylvania 19104 Social Science Data Library, Manning Hall 026A, University of Norm Carolina, Chapel Hill, Norm Carolina 27514 Social Science User Service, Princeton University Computer Center, 87 Prospect Avenue, Princeton, New Jersey 08540 Social Security Administration, Office of Research and Statistics, Room 1120,, Universal North Building, 1875 Connecticut Avenue, N.W., Washington, D.C. 20009
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Sharing Data in the Social Sciences SSRC Survey Archive, University of Essex, Wivenhoe Park, Colchester, Essex, England State Data Program, 2538 Channing Way, University of Califomia, Berkeley, California 94720 State Government Data Base, Council of State Governments, Iron Works Pike, Lexington, Kentucky 40578 Statistics Canada, 1006-General Purpose Building, Ottawa, Ontano, Canada K1A OT6 Steinmetzarchief, Herengracht 41~12, 1017 BX Amsterdam, The Netherlands lithe United Nations Statistical Office, The United Nations, New York, New York 10017 Zentralarchiv fur empirische Sozialforschung, Universitaet zu Koeln, Bachemer Strasse 40, W5000 Koeln 41, West Germany REFERENCES AND SELECTED BIBLIOGRAPHY 79 Bancroft, T.A. 1972 The statistical community and the protection of privacy. The American Statistician 26(4):1~16. Banks, A.S. 1973 Problems in the Use of Archival Data. Prepared for the Panel on Research Problems in Comparative Analysis, Annual Meeting of the International Studies Association, May 1~17, New York. Benson, L. 1968 The empirical and statistical basis for comparative analysis of historical change. In Stein Rokkan, ea., Comparative Studies Across Cultures and Nations. Pans: Mouton. Bick, W., and Muller, P.J. 1980 The nature of process-produced data towards a social-scientific source cnticism. In Jerome M. Clubb and Erwin K. Scheuch, eds., Historical Social Research: The Use of Historical and Process-Produced Data. Stuttgart, Germany: Klett-Cotta. Bisco, R., ed. 1970 Data Bases, Computers, arid the Social Sciences. New York: Wiley-Interscience. Bogue, A.G. 1976 The historian and social science data archives in the United States. American Behavioral Scientist 19:419 442. Bond, K. 197g Confidentiality and the protection of human subjects in social science research. The American Sociologist 13(3):144. Bomch, R.F. 1972 Strategies for eliciting and merging confidential social research data. Policy Sciences 3(3):275-297. Bomch, R.F., and Reis, J. 1978 An illustrative project on secondary analysis. Pp. 88-111 in R.F. Boruch and P.M. Wortman, eds., New Directions for Program Evaluation. San Francisco: Jossey-Bass. Boruch, R.~., and Wortrnan, P.M. 1978 An illustrative project on secondary analysis. New Directions for Program Evaluation 4:8~1 10. Bowers, W.l., and Pierce, G.L. 1975 The illusion of deterrence in Isaac Ehrlich's research on capital punishment. Yale Law Journal 85:185-208. Bowman, R.T. 1970 The idea of a federal statistical data center its purpose and structure. Pp. 63 69 in Ralph L. Bisco, ea., Data Bases, Computers, and the Social Sciences. New York: Wiley Interscience.
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Representative terms from entire chapter: