Regulatory Review: Presidential Control Through Selective Communication and Institutional Conflict

The range and quantity of government activity has grown exponentially over the course of this century. In response, an "institutional Presidency" has developed. Today’s President is at the locus of a network of relationships designed to increase his capacity to influence the flow of events. This paper examines a small sample of those relationships: His relationship with the Office of Information and Regulatory Affairs (OIRA), a division of the Office of Management and Budget (OMB) that reviews regulations. OIRA was one of the key instruments used by the Ronald Reagan and George H.W. Bush Administrations to limit regulation. The operational question of this paper is: What happened to the OIRA-White House relationship when there was a change in party and policy preferences in the White House in 1993? That is, how does a relatively pro-regulatory White House use OIRA? To answer this question, this paper examines panel data on the policy preferences and social interaction patterns of OIRA members, time series data on the disposition of reviewed regulations, and structured interviews with members of OIRA. Analysis of these data indicates that the review process institutionalizes conflict between the OMB and agencies, resulting in appeals to the President when actors believe that the President will support their views. Thus, the George H.W. Bush and Bill Clinton Administrations economized on their limited ability to monitor the Executive Branch by focusing their attention and political support on members of OIRA with compatible viewpoints

ConStance: Modeling Annotation Contexts to Improve Stance Classification

Manual annotations are a prerequisite for many applications of machine learning. However, weaknesses in the annotation process itself are easy to overlook. In particular, scholars often choose what information to give to annotators without examining these decisions empirically. For subjective tasks such as sentiment analysis, sarcasm, and stance detection, such choices can impact results. Here, for the task of political stance detection on Twitter, we show that providing too little context can result in noisy and uncertain annotations, whereas providing too strong a context may cause it to outweigh other signals. To characterize and reduce these biases, we develop ConStance, a general model for reasoning about annotations across information conditions. Given conflicting labels produced by multiple annotators seeing the same instances with different contexts, ConStance simultaneously estimates gold standard labels and also learns a classifier for new instances. We show that the classifier learned by ConStance outperforms a variety of baselines at predicting political stance, while the model's interpretable parameters shed light on the effects of each context.Comment: To appear at EMNLP 201

Building Effective Intra-Organizational Networks: The Role of Teams

This paper integrates the largely independent literatures on networks and teams. Our objective is twofold: (1) To understand what constitutes an effective organizational network when much of the work of the organization is done by teams; and (2) to examine the internal and external social capital needs of teams. We raise questions to guide future research, and point to potential managerial implications

Who Wants to Deliberate--And Why?

Interest in deliberative theories of democracy has grown tremendously among political theorists over the last twenty years. Many scholars in political behavior, however, are skeptical that it is a practically viable theory, even on its own terms. They argue (inter alia) that most people dislike politics, and that deliberative initiatives would amount to a paternalistic imposition. Using two large, representative samples investigating people's hypothetical willingness to deliberate and their actual behavior in response to a real invitation to deliberate with their member of Congress, we find: 1) that willingness to deliberate in the U.S. is much more widespread than expected; and 2) that it is precisely people who are less likely to participate in traditional partisan politics who are most interested in deliberative participation. They are attracted to such participation as a partial alternative to "politics as usual."

Networks, Hierarchies, and Markets: Aggregating Collective Problem Solving in Social Systems

How do decentralized systems collectively solve problems? Here we explore the interplay among three canonical forms of collective organization--markets, networks, and hierarchies--in aggregating decentralized problem solving. We examine these constructs in the context of how the offices of members of Congress individually and collectively wrestle with the Internet, and, in particular, their use of official websites. Each office is simultaneously making decisions about how to utilize their website. These decisions are only partially independent, where offices are looking at each other for lessons, following the same directives from above about what to do with the websites, and confront the same array of potential vendors to produce their website. Here we present the initial results from interviews with 99 Congressional offices and related survey of 100 offices about their decisions regarding how to use official Member websites. Strikingly, we find that there are relatively few efforts by offices to evaluate what constituents want or like on their websites. Further, we find that diffusion occurs at the "tip of the iceberg": offices often look at each others' websites (which are publicly visible), but rarely talk to each other about their experiences or how they manage what is on their websites (which are not publicly visible). We also find that there are important market drivers of what is on websites, with the emergence of a small industry of companies seeking to serve the 440 Members. Hierarchical influences--through the House and through the party conferences--also constrain and subsidize certain practices.

Explaining the Diffusion of Web-Based Communication Technology among Congressional Offices: A Natural Experiment using State Delegations

Do legislators learn to use new communication technologies from each other? Using data from the official homepages of members of the U.S. House of Representatives, we test whether web-based communication technology diffuses through congressional state delegations. We use a natural experimental design that exploits ignorable state boundaries to distinguish between causal diffusion processes and spatial heterogeneity. Using nonlinear conditional autoregressive models for the statistical test, we find that web communication technology practices are weakly driven by communication within state delegations, and with the effect slightly more pronounced among Democrats than among Republicans