Silencing the Dummy Variable: A Plea to Heed One's Audience and Publish More

No-this is not what it seems. This is not a discourse on statistics, but it is a discussion of a type of methodology that of how, when they are writing, polit ical scientists can better approach their audience. Put differently, this article is related to the more general proposition that scholars need to demonstrate not only that they can conduct research but also that they can communicate it effec tively to a wide audience. And, although critical of some social science writing, it carries a suggestion for increasing your range of publication options. Today's political science graduate stu dents are often well versed in statistics, and they feel comfortable in talking sta tistical language; moreover, they know that to obtain a job, they must be able to respond at job talks to questions about methods and statistics, and they often respond in technical language in order to seem au courant. Certainly in presenting papers to other political scientists at pro fessional meetings, they continue to speak in the same way, with full statistical sails flying, as terms like "autocorrelation," "endogeneity," and "heteroskedasticity" trip off their tongues, and "logit" and "probit" are a basic part of their lingua franca. Certainly to the extent that these papers are intended for ultimate submis sion to leading general political science journals, it is important that methodology and statistical analysis be adequately ex plained and that tables of data-all those beta values and the like-be presented. For some, there seems to be no other way. While perhaps toning down the statistics when teaching undergraduates, political scientists seem to believe that the "one true way" is to be to let one's statistics fly full force. But wait a minute! What if a potential audience doesn't understand sophis ticated-and perhaps not even "unsophisticated"-statistics? What if those who work in a related field people who would be interested in the substance of your research-lack training in statistics and might have no more than a master's degree, if that? Does one sim ply write them off as unable to under stand what you as a political scientist have discovered?2 To listen to many colleagues, the im plicit answer does seem to be that, at least unconsciously, one does write off those "others." To remove the statistics from one's research presentations, I am told, would mean "we wouldn't be true social scientists"; the statistics "must be available for readers to understand what we've done." I wish to suggest otherwise. To appreciate my argument requires accepting the premise that there most certainly is good social science of value to practitioners working for the govern ment or private agencies, and even to the educated lay public with an interest in politics, policy, and government. That premise applies to a wide variety of jour nals where practitioners are part of the audience, but most particularly to those which deal with policy analysis in gen eral, specific substantive areas of policy, or aspects of bureaucratic and judicial administration. If you say, "Well, of course, I accept the idea that research about politics and government ultimately has to inform people practicing politics and gover nance," what then? As an editor of a peer-reviewed journal with a primary audience of practitioners, few of whom are trained in statistics, I have some suggestions that I have implemented perhaps over the anguished screams of some authors, or at least despite their out-of-earshot mutterings of dark imprecations-and which seem to have "worked," and I have some other obser vations to share. It is not my intent here to argue the point that we should be engaging the rest of the world, perhaps to strengthen pub lic policy discourse, although I do not doubt we could have that effect if we communicate clearly with others. It is also not my intent to argue for more "ap plied research" because practitioners seek studies that address their concerns. It is to argue that even if we continue to en gage in "normal science"-in order to satisfy our peers and obtain tenure and promotion we can make that normal science more useful for practitioners by making it more accessible. To the extent that we do base our research on real world problems, whether it be disaster mitigation or campaign contributions to judicial elections, there is all the more reason to have the resultant written prod uct speak in terms that are understand able by those who find themselves in the crucible of experience and who are won dering what to do next. However, I as sume that most political scientists will continue to do standard basic social sci ence research, and thus I speak primarily about how to reach an "applied audience." The principal prescription offered here is two-fold and simple: keep all but the most basic statistics (percentages, ratios, perhaps chi squares) out of the manu script and ban all "stat talk." That means no more mention of words which will quickly make readers' eyes glaze over: no more "logit"-except perhaps in a footnote; no more terms like "dummy variable"; and no more extensive de scription of what was coded "1" and what was coded "O." And it also means no tables with mind-numbing numbers that are meaningless to the reader. By mind-numbing, I do not mean simple cross-tabulations, which most readers should be able to follow-but even there, must one always say "bivariate correla tion"? My argument also means not pre senting every table possible, nor, in those tables, carrying each number out to what a colleague calls the "false precision" of four decimal places. Thus, even when presenting statistics, there can be simpler ways. Someone familiar with logit has suggested that "rather than reporting co efficients and what may be statistical significance, one could present predicted probabilities," which are far easier to understand. If complicated and sophisticated statis tical analysis has to be performed so you can be sure of your findings, you should, of course, still carry it out. But perform ing it and expounding on it in technical language are not the same; the former does not compel the latter. Thus results can, and should, be presented in clear English prose, not in "stat talk." A social scientist who has long worked in the business world (and thus has clients who are practitioners, albeit of a different Stephen L. Wasby is professor emeritus at the University at Albany, SUNY and visit ing scholar at University of Massachusetts, Dartmouth. He is editor-in-chief of Justice System Journal. E-mail: wasb@albany.edu