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Replication data for ``Multiple Principals and Legislative Cohesion.''
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Stereotype threat is a widely-cited psychological phenomenon with purported important real-world consequences. Reanalysis of data from the Nguyen and Ryan (2008) stereotype threat meta-analysis indicated the presence of small study effects in which the effect size for less precise studies was larger than the effect size for more precise studies. Four methods to adjust the meta-analysis effect size for potential publication bias produced divergent estimates, from essentially no change, to a 50 percent decrease, to a reduction of the estimated effect size to near zero. Caution is therefore warranted both for citing Nguyen and Ryan (2008) as evidence of a meaningful stereotype threat effect and for claiming that the stereotype threat effect size is negligible based on these adjustments, given that the detected small study effects might be due to unexplored moderators instead of publication bias.
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Positron emission tomography using 18F-Fluro-deoxy-glucose (18F-FDG) is a useful tool to detect regions of inflammation in patients. We utilized this imaging technique to investigate the kinetics of gastrointestinal recovery after radiation exposure and the role of bone marrow in the recovery process. Methods: Male Sprague-Dawley rats were either sham irradiated, irradiated with their upper half body shielded (UHBS) at a dose of 7.5 Gy, or whole body irradiated (WBI) with 4 or 7.5 Gy. Animals were imaged using 18F-FDG PET/CT at 5, 10 and 35 days post-radiation exposure. The gastrointestinal tract and bone marrow were analyzed for 18F-FDG uptake. Tissue was collected at all-time points for histological analysis. Results: Following 7.5 Gy irradiation, there was a significant increase in inflammation in the gastrointestinal tract as indicated by the significantly higher 18F-FDG uptake compared to sham. UHBS animals had a significantly higher activity compared to 7.5 Gy WBI at 5 days post-exposure. Animals that received 4 Gy WBI did not show any significant increase in uptake compared to sham. Analysis of the bone marrow showed a significant decrease of uptake in the 7.5 Gy animals 5 days post-irradiation, albeit not observed in the 4 Gy group. Interestingly, as the metabolic activity of the gastrointestinal tract returned to sham levels in UHBS animals it was accompanied by an increase in metabolic activity in the bone marrow. At 35 days post-exposure both gastrointestinal tract and bone marrow 18F-FDG uptake returned to sham levels. Conclusion: 18F-FDG imaging is a tool that can be used to study the inflammatory response of the gastrointestinal tract and changes in bone marrow metabolism caused by radiation exposure. The recovery of the gastrointestinal tract coincides with an increase in bone marrow metabolism in partially shielded animals. These findings further demonstrate the relationship between the gastrointestinal syndrome and bone marrow recovery, and that this interaction can be studied using non-invasive imaging modalities.
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Contains Stata code and data for replicating all figures and tables in the manuscript and appendix.
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This Stata 14 code replicates the figures and table in Clemens & Postel, "Temporary Work Visas as US-Haiti Development Cooperation: A Preliminary Impact Evaluation".
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Profound differences exist in how Americans from various racial and ethnic groups view police and court officials. We argue that vicarious experiences contribute to this racial and ethnic divide. Drawing on research on social communication, social network composition, and negativity biases in perception and judgment, we devise a theoretical framework to articulate why vicarious experiences magnify racial and ethnic disparities in evaluations of judicial actors. Four hypotheses are tested using original survey data from the state of Washington. Results provide strong evidence that vicarious experiences influence citizens’ evaluations of both police and courts, and do so in a manner that widens racial divides in how those actors are perceived.
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Over the past decade, a number of new measures have been developed that attempt to capture the political orientation of both incumbent and non-incumbent candidates for Congress, as well as other offices, on the same scale. These measures pose the tantalizing possibility of being able to answer a host of fundamental questions about political accountability and representation. In this paper, we examine the properties of six recent measures of candidates' political orientations in different domains. While these measures are commonly viewed as proxies for ideology, each involves very different choices, incentives, and contexts. Indeed, we show that there is only a weak relationship between these measures within party. This suggests that these measures are capturing domain-specific factors rather than just candidates' ideology. Moreover, these measures do poorly at distinguishing between moderate and extreme roll call voting records within each party. As a result, they fall short when it comes to facilitating empirical analysis of theories of accountability and representation in Congress. Overall, our findings suggest that future research should leverage the conceptual and empirical variation across these measures rather than assuming they are all synonymous with candidates' ideology.
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The large majority of inferences drawn in empirical political research follow from model-based associations (e.g. regression). Here, we articulate the benefits of pre- dictive modeling as a complement to this approach. Predictive models aim to specify a probabilistic model that provides a good fit to testing data that were not used to estimate the model’s parameters. Our goals are threefold. First, we review the central benefits of this under-utilized approach from a perspective uncommon in the existing literature: we focus on how predictive modeling can be used to complement and aug- ment standard associational analyses. Second, we advance the state of the literature by laying out a simple set of benchmark predictive criteria. Third, we illustrate our approach through a detailed application to the prediction of interstate conflict.
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How does individuals’ influence in a large social network change? Social scientists have difficulty answering this question because measuring influence requires frequent observations of a population of individuals’ connections to each other, while sampling that social network removes information in a way that can bias inferences. This paper introduces a method to measure influence over time accurately from sampled network data. Ranking individuals by the sum of their connections’ connections — neighbor cumulative indegree centrality — preserves the rank influence ordering that would be achieved in the presence of complete network data, lowering the barrier to measuring influence accurately. The paper then shows how to measure that variable changes each day, making it possible to analyze when and why an individual’s influence in a network changes. This method is demonstrated and validated on 21 Twitter accounts in Bahrain and Egypt from early 2011. The paper then discusses how to use the method in domains such as voter mobilization and marketing.
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Eye-tracking and behavioral data collected for the study titled "Where You Look Matters for Body Perception: Preferred Gaze Location Contributes to the Body Inversion Effect" published in PLoS One.
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  • Tabular Data
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