Many legal theorists and political philosophers – among them John Rawls, Ronald Dworkin, Amy Gutmann, Dennis Thompson, and Joshua Cohen – believe that decision making through deliberation is a normative ideal that yields both better laws as well as a positive transformation in its participants. They further have assumed the judiciary is perhaps best equipped to realize this kind of “deliberative democracy,” and that the courts can effectively provide an example for other, less deliberative branches of government to follow. This essay argues, however, that judicial deliberation is both more complicated than is assumed by these theorists and also embodies a kind of deliberation different in nature than the one we would expect in a deliberative model. Indeed, contributions from social science suggest that judges are strategic (and oftentimes political) actors, and that their “deliberations” are more like akin to bargaining than reasoned exchanges. In addition, the products of judicial decision making – the courts’ opinions – often fail to reflect true deliberative reasoning. Thus, the judiciary might in many ways be less deliberative than its sister branches. This is not to say that judicial processes cannot be modified to become more deliberative – and therefore more normatively desirable -- but it does suggest that the assumption that the courts provide a deliberative model for other decision makers to follow might be based on a romanticized view of judicial processes, rather than on the way judges actually behave. This conclusion has, moreover, strong implications for the feasibility of deliberation as a decision making mechanism.

We marshal discoveries about human behavior and learning from social science research and show how they can be used to improve teaching and learning. The discoveries are easily stated as three social science generalizations: (1) social connections motivate, (2) teaching teaches the teacher, and (3) instant feedback improves learning. We show how to apply these generalizations via innovations in modern information technology inside, outside, and across university classrooms. We also give concrete examples of these ideas from innovations we have experimented with in our own teaching.

The American system of higher education is under attack by political, economic, and educational forces that threaten to undermine its business model, governmental support, and operating mission. The potential changes are considerably more dramatic and disruptive than what we've already experienced. Traditional colleges and universities urgently need a coherent, thought-out response. Their central role in ensuring the creation, preservation, and distribution of knowledge may be at risk and, as a consequence, so too may be the spectacular progress across fields we have come to expect as a result. Introduction and article for a symposium for PS: Political Science and Politics. Other symposium participants are Henry E. Brady (UC-Berkeley), Michael Laver (NYU), Nannerl O. Keohane (Princeton), Virginia Sapiro (BU), and John Mark Hansen (Chicago).

Causal inference is considered the gold standard in social science research. Making causal claims about ``immutable characteristics'' such as race, however, has been strongly discouraged. In contrast to previous literature, which assumes a fixed conception of race, we propose a different framework that in some cases reconciles race and causation. First, we distinguish those units of analysis in which intrinsic problems of race and causality can be avoided. Second, we demonstrate that race can be defined as a composite measure that has some mutable elements. These extensions allow us to synthesize two areas where causal claims about race may be permissible: (1) studies that measure the effect of exposing an entity to a racial cue and (2) studies that disaggregate race into constituent pieces and measure the causal effect of some mutable element. We demonstrate these techniques via examples from contemporary scholarship

This paper uses two new datasets to investigate the reliance by political actors on the external vetting of judicial candidates, in particular vetting conducted by the nation's largest legal organization, the American Bar Association (ABA). First, I demonstrate that poorly rated lower-court nominees are significantly more likely to have their nominations fail before the Senate. However, I also show that minority and female nominees are more likely than whites and males to receive these lower ratings, even after controlling for education, experience, and partisanship via matching. Furthermore, by presenting results showing that ABA ratings are unrelated to judges' ultimate reversal rates, I show that these scores are a poor predictor of how nominees perform once confirmed. The findings in this paper complicate the ABA's influential role in judicial nominations, both in terms of its utility in predicting judicial "performance" and also in terms of possible implicit biases against minority candidates, and suggest that political actors rely on these ratings perhaps for reasons unrelated to the courts.

In this paper, we leverage the natural experiment of a child's gender to identify the effect of having daughters on the votes of judges. Using new data on the family lives of U.S. Courts of Appeals judges, we find that, conditional on the number of children a judge has, judges with daughters consistently vote in a more pro-woman fashion on gender issues than judges who have only sons. This result survives a number of robustness tests and appears to be driven primarily by Republican judges. More broadly, this result demonstrates that personal experiences influence how judges make decisions, and it is the first paper to show that empathy may indeed be a component in how judges decide cases.

In this paper, I use two new data sets to demonstrate that black federal judges are consistently overturned on appeal more often than similar white judges. The effect is robust and persists after taking into account previous professional and judicial experience, educational backgrounds, qualification ratings assigned by the American Bar Association, and differences in partisanship. This study is the first to explore how higher-court judges evaluate opinions written by judges of color, and it has clear implications: despite attempts to make judiciary more reflective of the general population, racial disparities within the legal system continue to persist.

The last five years have seen an explosion in the amount of data available to social scientists. Although a blessing, these extremely large sources of data can cause problems for political scientists working with standard statistical software programs, which are poorly suited to analyzing big data sets. In this essay, we describe a few approaches to handling extremely large datasets within the R programming language, both at the command line prior to R and after we fire up R. We show that handling large datasets is about either (1) choosing tools that can shrink the problem or (2) fine-tuning R to handle massive data files.

The recent subprime mortgage crisis has brought to the forefront the possibility of discriminatory lending on the basis of race or gender. Using the over 10 million observations collected by the federal government in 2006 through the Home Mortgage Disclosure Act, this paper explores these claims causally. In so doing, the paper explores two possible theories of discrimination: (1) that any discriminatory lending patterns are picking up the fact that minority borrowers went to different lenders, perhaps as a result of predatory lending, and (2) the possibility that individual lenders discriminated against identically situated borrowers. The results presented provide limited evidence for the idea that borrowers of different races went to different lenders, but only in certain regions of the country and only for certain minority groups. In addition, many of these results are sensitive to missing confounders – e.g., financial data like credit scores and down payments, which the federal government does not collect. Ultimately, the results’ sensitivity suggests that more data gathering is in order before definitive assertions can be made by legal and policy actors.

Recreational DNA ancestry testing may seem frivolous, or at least unconnected with important issues in politics and political science. But, in fact, it opens new vistas onto two crucial questions: what is the relationship, if any, between biology and race? How much and why do individuals and groups prefer clear, singular racial identities or blurred, mixed racial self-images? This article probes those questions from an unusual angle: media treatment of and public responses to various choices in DNA ancestry testing. We analyze two databases of U.S. newspaper articles, one with almost 6,000 and a second of 700 items, and two new public opinion surveys. The first uses vignettes to obtain the views of a representative sample of Americans, and the second probes the responses of a representative sample who have conducted such tests. We find that the media emphasize stories focused on singularity, and that vignette respondents also generally prefer and are more influenced by singular rather than plural test results. Minority group members are especially receptive to DNA testing and its message of group singularity. Views of actual testers, however, suggest that when all Americans have access to genome sequencing, the politics of racial ancestry testing may change dramatically.

Just as physics gained public visibility and ideological contention as it matured over the twentieth century, so genomic science will gain public visibility and competing normative valences as it becomes increasingly important during the twenty-first century. We begin by describing Americans’ level of technology optimism or pessimism across four arenas in genomic science and one arena (climate change) outside genomic science. We then ask “so what?” – do people who perceive more harm than good in genomic science hold different policy preferences from those who perceive more good than harm? Do optimists and pessimists differ in their perceptions of elite actors, or their willingness to be directly involved with the new science? Finally, we consider variations within the public. Is knowledge about genetics associated with more optimism about genomic science? Are people with direct interests in one arena of genomics more optimistic (or pessimistic) about its future than they are about other arenas? Do religiosity or characteristics such as race or gender play a role in levels of optimism about genomics in general or particular genomics arenas? We conclude, first, that public attitudes toward genomic science are coherent and intelligible, perhaps surprisingly so given how new and complex the substantive issues are, and, second, that citizens differ from most social scientists, legal scholars, and policy advocates in their overall embrace of genomics’ possibilities for benefitting society.