Norman H. Nie

Citizen Activity: Who Participates? What Do They Say?

We use responses to a large-scale national survey designed to oversample political activists to investigate the extent to which participant publics are representative of the public as a whole. Building upon the finding that while voters differ from nonvoters in their demographic attributes, their attitudes as measured by responses to survey questions are not distinctive, we consider a variety of political acts beyond voting that citizens can use to multiply their political input and to communicate more precise messages to policymakers. In addition, we consider not only respondents demographic characteristics and policy attitudes but also their circumstances of economic deprivation and dependence upon government programs. Although activists are representative of the public at large in terms of their attitudes, they differ substantially in their demographic attributes, economic needs, and the government benefits they receive. Furthermore, in terms of the issues that animate participation, groups differentiated along these lines bring very different policy concerns to their activity.

Social Structure and Political Participation: Developmental Relationships, Part I *

Economic development has consequences for many aspects of social life. Some of these social consequences, in turn, have an impact on a nations political life. Studies of social mobilization, for example, have demonstrated that economic development is associated with sharp increases in the general level of political participation. These studies report strong relationships between aggregate socio-economic measures such as per capita income, median level of education, and percentage of the population in urban areas, on one hand, and aggregate measures of political participation, such as voting turnout, on the other. Simultaneously, scholars conducting surveys of individual political participation consistently have reported that an individuals social status, education, and organizational memberships strongly affect the likelihood of his engaging in various types of political activities. In spite of the consistency of both sets of findings across many studies and although the findings appear frequently in analysis of political stability, democracy, and even strategies of political growth, we know little about the connections between social structure and political participation. With few exceptions the literature on individual participation is notable for low level generalizations (the better educated citizen talks about politics more regularly), and the absence of systematic and comprehensive theory. While the literature on the growth of national political participation has been more elaborate theoretically, the dependence on aggregate measures has made it difficult to determine empirically how these macro social changes structure individuals life experiences in ways which alter their political behavior.

More on Evaluating Computer Programs

Most authors have been quite careful in comparing packages on a predetermined set of features and avoiding sweeping generalizations. Journals have usually been fair in providing software developers with the opportunity to respond to published evaluations. The recent paper by Velleman and Welsch (1981) is a notable exception. Although the authors provide an excellent discussion of some regression diagnostics, their conclusion as to the acceptability of SPSS for regression analysis leaves us bewildered. If the sole criterion for an acceptable regression program is producing partial residual plots as standard output, almost all of the packages fail equally. If it is providing a variety of diagnostics, SPSS NEW REGRESSION and SCSS REGRESSION calculate almost all of the statistics computed by BMDP9R when METHOD = NONE is specified (which the authors recommend). Among the statistics are residuals, Studentized residuals, deleted residuals, Studentized deleted residuals, predicted values and their standard errors, adjusted (PRESS) predicted values, and Cooks and Mahalanobis distances. The authors are correct in observing that in the SPSS batch system residuals and other statistics that are saved cannot be accessed outside of the procedure during the same run (a constraint shared by BMDP, though the authors miss that fact). This restriction does not occur in SCSS or in the upcoming release of the batch system. To minimize the inconvenience, the SPSS NEW REGRESSION procedure is designed to provide extensive facilities for display and analysis of residuals within the procedure itself. For example, histograms and normal probability plots are available, and the various residuals can be plotted against independent or dependent variables, as well as each other. Cases with large values of the diagnostic statistics can be identified and residuals can be plotted in sequence, either for all cases or for those satisfying a user-specified criterion. Statistics and displays are produced separately for cases used in building the model and for those not selected. For a complete discussion of the facilities available in SPSS NEW REGRESSION see Hull and Nie (1981) and Norusis (1982). The SCSS system is described in Nie (1980). Velleman and Welsch are entitled to their private opinions about the acceptability of various software packages. However, when their opinions appear in scientific publications, they owe their readers data to support them. Journals should not treat software evaluations more casually than other papers. The same standards of objectivity and factual presentation must be required.

Statistical Software Design and Scientific Breakthrough: Some Reflections on the Future

Data analysis software has played a major role in the recent evolution of certain types of scientific disciplines which are characterized by weak theory and intercorrelated independent variables. The evolution of these fields of inquiry has depended as much upon data analysis packages for their progress as astronomy has upon the telescope, cellular biology the microscope, and particle physics the accelerator. Three new developments in the capabilities and organization of these software packages are pending or will emerge in the foreseeable future, and are discussed in terms of their potential impact on accelerated scientific discovery in the fields of inquiry that such software packages serve. They are: research-oriented graphics, true conversational analysis, and voice controlled software. These developments may help produce a revolution in scientific insight in a number of disparate fields.

The Development of the Internet in Everyday Life in America

Internet technology has the potential to affect various aspects of an individual’s life, from time allocation to mental well-being. However, discussions about the Internet’s effect on the individual often devolve into simplistic “good” versus “bad” debates, with little attention paid to the nuances of the medium and its effects. In previous work (Nie/ Erbring 2002; Hillygus 2002a; Nie/Hillygus 2002b; Nie/ Hillygus/ Erbring 2003), we have made an effort to move beyond this debate, focusing instead on the effects of Internet use at different times and different places on face-to-face interaction. In this chapter, we assess the current state of the continuing debate, taking into account the maturation of the Internet as a technology and the growing and changing group of Internet users.

Appendix 1. THE DATA

This appendix describes the entire data series used to estimate the multicountry model described in Chapter 3. The model was estimated with seasonally adjusted quarterly national-income account data from 1971 to 1986. The exact starting and ending quarters vary slightly among the equations because of differences in estimation methods, differences in numbers of lags or leads in each equation, and differences in data availability in each country at the time of estimation. The data were obtained from readily available sources. For all countries except the United States, most of the data were obtained from international agencies. The financial data on interest rates, exchange rates, and money supply are from the OECDs Main Economic Indicators (MEI) and the Federal Reserve Bank of St. Louiss International Economic Conditions (IEC). The national income account data are from the OECDs Quarterly National Accounts (QNA). The wage data are from the OECDs Main Economic Indicators and from the IMFs International Financial Statistics (IFS). The U.S. data were obtained directly from Citibase data diskettes. Some Japanese data were obtained from the Economic Planning Agencys Annual Report on National Accounts. The degree of detail in the breakdown of GNP by spending component differs from country to country in the OECDs Quarterly National Accounts, and the differences in disaggregation in the model for some of the countries reflect this. There is no consumption breakdown for Germany or Italy. Nor is there a breakdown for fixed investment for Germany and Italy. For Japan, nonresidential investment is not broken down into structures and equipment. Most of the national-income account data are published in seasonally adjusted form, but only seasonally unadjusted data are available for the German national account data and for Japanese disaggregated consumption. These seasonally unad-justed data series were seasonally adjusted, using the computer program microTSP, before they were used for estimation. All the national income data is in constant dollars. The base years for real GNP, the price deflators, and the wage index are different in each country. Some of the auxiliary series used to compute the series in the model are also included in the data description. The conversion description records the transformations that have been made on the original series before estimation or model