John Echeverri-Gent's (2009) fine article in this symposium makes a compelling case for a greater focus on the study of inequality by political scientists. A topic we have too often neglected, its dynamics go to the core of our disciplinary concerns and we clearly should have more to offer to its understanding. APSA is to be commended for supporting the work of the Task Force on Difference, Inequality, and Developing Societies (2008), which Echeverri-Gent led, and which, in large part, informs his article in these pages. It should generate a renewed focus by political scientists on international inequality and on the role of domestic inequality in the development process.

The monograph, Biotechnology: Public Policy and the Social Sciences—Critical Needs in Teaching and Research [Biotechnology], emphasizes the need for social scientists to increase their participation in public policy regarding biotechnology through research, teaching and policy recommendations. The authors (Robert H. Blank, Lynton K. Caldwell, Thomas C. Wiegele, and Raymond A. Zilinskas) persuasively argue that critical issues are at stake here. Although scientific methodology and definitions underlie important choices regarding biotechnology, we face issues that go beyond scientific inquiry and expertise. Recombinant DNA research raised concerns in the late 1970s, which were sufficiently addressed through the NIH guidelines. Now commercial developments in biotechnology are posing other quite significant social and ethical issues. The idea that nonscientists should become actively involved in science policy is not new, but the message bears repeating. It has been standard practice in our society for technical experts to claim exclusive authority in broad areas of decision-making involving technical matters. Only recently, for example, have we begun to insist upon full disclosure from our doctors, and reclaim the right to make important decisions about our own lives and bodies. Technical experts cannot fully address ethical and social concerns. Moreover, in the area of biotechnology, experts have strong interests, both intellectual and financial; they are not likely to make unbiased decisions. These choices properly belong to the political realm.

The study of AIDS, as a disease, a social problem, or, in my case, as a political phenomenon is necessarily difficult and invasive. Learning about AIDS requires invasion of the most private spheres of peoples' lives, involves watching people at their most vulnerable, and often requires becoming closely involved with people whose lives and circumstances are far away from the researcher's own comfort zone. As the title of this essay suggests, my research has led me to take on a variety of roles; first, in order to gather the information I sought and, later, because of the information I had gathered. Roughly speaking, these roles can be characterized with respect to the distance of the researcher from the subject matter. As a scholar, I endeavored, particularly in the early stages of my research, to hold myself apart from what I saw and to compare my findings against those of other researchers. However, as time moved on, I found myself increasingly playing two other roles, roles I have come to characterize as witness and activist. My efforts to lessen the distance between the subjects of my research and myself resulted from both practical and personal motivations. As a practical matter, like many other social scientists, I quickly discovered that I had far greater access to information—in the form of written documents, interviews, and observation opportunities—as an insider. Personally I found myself wanting to contribute what I could to help solve, or at least lessen the severity of, the problems unfolding all around me.

As I have moved closer to the subjects of my research, and to the perspectives they hold, I have been forced to confront head-on a perennial dilemma of scholars: objectivity. How does one study an issue “objectively,” particularly when the issue is fraught with controversy? Does taking a side render future observations invalid? Is there some magic line between researcher and subject that is not to be crossed? If so, where is it?

The findings presented below represent what I have discovered about interest organizing and political activism in the context of AIDS.

For some 70 years, peoples of highly diverse origins and cultures were part of a political system called the Soviet Union. The leadership of the Soviet Union took great pride in attempting to organize that diversity into a “melting pot,” in which citizens of each ethnic background were to enjoy the same basic rights and privileges. Extraordinary political effort was expended by Soviet leaders to promote and advertise the success of this union of equals.

We will provide an empirical assessment of the attitudes of youth in two former Soviet republics, how they now see each other, and how they feel various minorities in each new republic should be treated politically. It involves the use of a common instrument in each of these new states that was designed to measure how each ethnic group feels about the other former Soviet peoples and basic ethnic policies in their own states. In addition, data on a variety of other political and social issues are examined, primarily to examine whether certain quality of life indicators are more positively responded to in a former Soviet republic than in Russia proper.

What is the probability of students cheating?

I found myself asking this question quite literally recently, when 10 of my students in an upper-level undergraduate methods course turned in identical results for a take-home exercise. Of course, on some exercises I expect students to produce identical findings, such as when I ask for the mean and variance of a particular variable. In this case, however, I had asked students to produce a new random variable and to summarize its values in a frequency distribution. My initial reaction was to suspect the students of collaborating on the exercise (contrary to my syllabus and the assignment's instructions), though the number of students who produced identical results—10 out of a class of 30—made me skeptical that so many students could conspire so effectively. The very nature of the students made it unlikely that they collaborated together. I teach at a large public-service university, with students that represent a broad variety of backgrounds, nationalities, interests, and ages. The course also is cross-listed among disciplines, so the 10 students included both political science and geography majors. My review of the names of the 10 students persuaded me that it was highly unlikely that they cheated. I have found, furthermore, that many students will not voluntarily work in groups. So how did this diverse group of students produce an identical “random” variable?

My investigation of this question took me well beyond issues of student conduct. To answer the question to my satisfaction, I found I had to understand how campus computer networks operate and ultimately how the statistical software my students use works. My journey took me into the arcane world of “random” numbers in computers, and required me to understand how statistical software generates so-called pseudo-random numbers. When I finally found an answer to my puzzle, I learned that the problem was not with my students, but with the software on which we all rely for research and, increasingly, pedagogy. Many researchers today know there is no such thing as a computer-generated truly random number. Although many political scientists know this has profound consequences for their work—whether for sampling purposes or Monte Carlo experiments—to my knowledge instructors of quantitative methods courses have given little thought to its implications in the classroom. For one, it is easy and tempting to mistake the problems of pseudo-random number generation for student malfeasance. For another, it speaks to the students' (and instructor's) conceptual grasp of the slippery idea of “randomness.” For this reason, I offer my own experience as a cautionary tale.

Conventional wisdom pervades presidential politics, and there is no doubt that this will again be true in 2016. First among “old politicians’ tales” is that a political party’s placement of a national convention in a specific state can affect presidential voting there, swinging or flipping it to its presidential candidate. Second, the selection of a vice-presidential candidate as a favorite son (or daughter) will deliver a state’s electoral votes to a presidential ticket. Is either of these pearls of wisdom true? This article tests the truth of both the convention location and favorite-son claims and finds little evidence of their efficacy.

For the second presidential election in a row the prediction of the “Klarner Model” was within half a percent of the actual result. This model forecast that Obama would receive 51.3% of the two-party vote, while he actually received 51.8%. The model also called all states correctly, with the exception of Florida, which was predicted to be narrowly lost by Obama with 49.7% of the vote. These forecasts were made on July 15, 2012. This success does not indicate the model is better than the other models in the symposium as luck is a major determinant of which model gets closest to the mark. Although the Klarner Model correctly called 49 out of 50 states, that means little in an election where merely calling states on the basis of 2008 results would have called all but two correctly.

Ethnic differences based on national origin are often undistinguished within the Black community in the United States. The assumption of a singular Black ethnicity (or the notion that all Blacks in the U.S. identify their origins within the U.S.) defines the majority of scholarly work on Black political identity and political behavior. However, the growing visibility of Black immigrant communities in major metropolitan areas of the U.S. raises the following question for scholars of immigration and race politics: What are the political implications of ethnic diversity within the Black community?

This article summarizes research on the profession of community college faculty generally and data gathered from a survey of political science faculty teaching at community colleges nationwide conducted in 2018. The purpose of the article is to educate the discipline about what life is like for faculty at two-year schools and specifically how political science faculty at these schools perceive their role.

In recent years, scholars, journals, and professional organizations in political science have been working to improve research transparency. Although better transparency is a laudable goal, the implementation of standards for reproducibility still leaves much to be desired. This article identifies two practices that political science should adopt to improve research transparency: (1) journals must provide detailed replication guidance and run provided material; and (2) authors must begin their work with replication in mind. We focus on problems that occur when scholars provide research materials to journals for replication, and we outline best practices regarding documentation and code structure for researchers to use.

In this article, we chronicle our experience in team-teaching large-lecture sections of “Introduction to American Government.” A dual-instructor approach allows us to accommodate 250 students, which obviates the need for five separate sections (and instructors) of the course. In addition, our “Crossfire Approach,” in which we engage one another in frequent and unstructured political debate, generates student interest in the course and in the political science major. Students who were enrolled in this course from 2007 through 2011 were significantly more likely to declare political science as their major than those who took it from any other instructor or either of us teaching it individually. This approach conserves departmental resources while simultaneously growing the program—a clear win-win situation.

They did not seem to be in a position to help the other body. Yet, on October 10, 2002, members of the House Judiciary Committee listened to witnesses discuss how the Senate could be more efficient. In 2003, Senate committees heard similar testimony. During the hearings, eminent law professors suggested that the practice of allowing filibusters on judicial nominees could not be imposed by previous Senates on the current one. It, therefore, would be within the power of the 51 Republican Senators to uphold a point of order against the filibuster and proceed to govern by majority rule (Kmiec 2003). In Washington, this course of action is called the “nuclear option.” Although the informal use of the nuclear option has several variations, each variation has a common underlying feature that can be formally defined. The nuclear option is a dramatic refusal to recognize delaying tactics permitted under the rules that facilitates the institutionalization of majoritarian procedures in a legislative body. Occurring in legislatures such as the 1881 British House of Commons, the use of the nuclear option can be a watershed event wherever the majority lacks an unassailable way to end debate.