The nisi prius Trial Notes of Lord Chancellor Hardwicke

The trial notes of Chief Justices William Mansfield and Dudley Ryder have proved to be rich sources for the study of common law judicial process in the decades after 1750. Equally valuable, but hitherto unanalyzed, are the trial notes of Philip Yorke, Lord Hardwicke, compiled when he was Chief Justice of King's Bench in the mid-1730s. This study provides an account of Hardwicke's notes, comparing and contrasting their style and substance to those of Mansfield and of Ryder, thereby enlarging our appreciation of the character and treatment of civil litigation in the royal courts under George II and George III.     

Using the Results from Rigorous Multisite Evaluations to Inform Local Policy Decisions

Evidence‐based policy at the local level requires predicting the impact of an intervention to inform whether it should be adopted. Increasingly, local policymakers have access to published research evaluating the effectiveness of policy interventions from national research clearinghouses that review and disseminate evidence from program evaluations. Through these evaluations, local policymakers have a wealth of evidence describing what works, but not necessarily where. Multisite evaluations may produce unbiased estimates of the average impact of an intervention in the study sample and still produce inaccurate predictions of the impact for localities outside the sample for two reasons: (1) the impact of the intervention may vary across localities, and (2) the evaluation estimate is subject to sampling error. Unfortunately, there is relatively little evidence on how much the impacts of policy interventions vary from one locality to another and almost no evidence on the implications of this variation for the accuracy with which the local impact of adopting an intervention can be predicted using findings from an evaluation in other localities. In this paper, we present a set of methods for quantifying the accuracy of the local predictions that can be obtained using the results of multisite randomized trials and for assessing the likelihood that prediction errors will lead to errors in local policy decisions. We demonstrate these methods using three evaluations of educational interventions, providing the first empirical evidence of the ability to use multisite evaluations to predict impacts in individual localities—i.e., the ability of “evidence‐based policy” to improve local policy.     

Mass Media and Electoral Preferences During the 2016 US Presidential Race

Political Behavior - This paper uses analyses of commercial polls alongside content-analytic measures of sentiment in the content of nine newspapers to explore the relationship between voter...     

Policy attribute framing: A comparison between three policy instruments for personal emissions reduction

A comparative experiment in the UK examined people's willingness to change energy consumption behavior under three different policy framings: energy tax, carbon tax, and personal carbon allowances (PCA). PCA is a downstream cap‐and‐trade policy proposed in the UK, in which emission rights are allocated to individuals. We hypothesized that due to economic, pro‐environmental and mental accounting drivers PCA would have greater potential to deliver emissions reduction than taxation. Participants (n = 1,096) received one version of a survey with the same energy‐behavior–related questions and identical incurred costs under one of the following framings: energy tax (where carbon was not mentioned), carbon tax, and PCA. Results suggest that policies that draw people's attention to carbon (PCA and carbon taxation) could have greater impact on their stated willingness to reduce energy consumption, and on the reduction amounts prompted, than would a non‐overt price signal (energy tax). There is mixed evidence, however, as to whether PCA or carbon taxation would produce the largest energy demand reductions. Some indication was found for a spillover toward wider carbon conservation under the PCA framing. © 2011 by the Association for Public Policy Analysis and Management.     

Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference

Kosuke Imai Department of Politics, Princeton University, Princeton, NJ 08544 e-mail: kimai{at}princeton.edu Gary King Department of Government, Harvard University, 1737 Cambridge Street, Cambridge, MA 02138 Elizabeth A. Stuart Departments of Mental Health and Biostatistics, Johns Hopkins Bloomberg School of Public Health, 624 North Broadway, Room 804, Baltimore, MD 21205 e-mail: estuart{at}jhsph.edu e-mail: king{at}harvard.edu (corresponding author) Although published works rarely include causal estimates frommore than a few model specifications, authors usually choosethe presented estimates from numerous trial runs readers neversee. Given the often large variation in estimates across choicesof control variables, functional forms, and other modeling assumptions,how can researchers ensure that the few estimates presentedare accurate or representative? How do readers know that publicationsare not merely demonstrations that it is possible to find aspecification that fits the author's favorite hypothesis? Andhow do we evaluate or even define statistical properties likeunbiasedness or mean squared error when no unique model or estimatoreven exists? Matching methods, which offer the promise of causalinference with fewer assumptions, constitute one possible wayforward, but crucial results in this fast-growing methodologicalliterature are often grossly misinterpreted. We explain howto avoid these misinterpretations and propose a unified approachthat makes it possible for researchers to preprocess data withmatching (such as with the easy-to-use software we offer) andthen to apply the best parametric techniques they would haveused anyway. This procedure makes parametric models producemore accurate and considerably less model-dependent causal inferences. Authors' note: Our thanks to Dan Carpenter and Jeff Koch fordata; Alberto Abadie, Neal Beck, Sam Cook, Alexis Diamond, BenHansen, Guido Imbens, Olivia Lau, Gabe Lenz, Paul Rosenbaum,Don Rubin, and Jas Sekhon for many helpful comments; and theNational Institutes of Aging (P01 AG17625-01), the NationalInstitute of Mental Health (MH066247), the National ScienceFoundation (SES-0318275, IIS-9874747, SES-0550873), and thePrinceton University Committee on Research in the Humanitiesand Social Sciences for research support. Software to implementthe methods in this paper is available at http://GKing.Harvard.edu/matchitand a replication data file is available as Ho et al. (2006).     

Simulating Models of Issue Voting

Ola Listhaug Department of Sociology and Political Science, Norwegian University of Science and Technology, N-7491 Trondheim, Norway e-mail: olal{at}svt.ntnu.no e-mail: rabinowitz{at}unc.edu (corresponding author) How should one analyze data when the underlying models beingtested are statistically intractable? In this article, we offera simulation approach that involves creating sets of artificialdata with fully known generating models that can be meaningfullycompared to real data. The strategy depends on constructingsimulations that are well matched to the data against whichthey will be compared. Our particular concern is to considerconcurrently how voters place parties on issue scales and howthey evaluate parties based on issues. We reconsider the Lewisand King (2000) analysis of issue voting in Norway. The simulationfindings resolve the ambiguity that Lewis and King report, asvoters appear to assimilate and contrast party placements andto evaluate parties directionally. The simulations also providea strong caveat against the use of individually perceived partyplacements in analyses of issue voting.     

The Impact of Petition Signing on Voter Turnout

Generally speaking, campaign-related contact motivates voters. One form of such contact not much explored in the voter mobilization literature is the petitioning for ballot initiatives that occurs with considerable frequency in about half the states and even more localities. Using newly-available data that allow us to match individual petition signers with their subsequent election behavior, we explore the role of having had a hand in a ballot measure’s qualifying stage in propelling individual voters to the polls. Specifically, we perform multivariate analysis on a random sample of 1,000 registered Arkansas voters, 1,100 registered Florida voters, and all 71,119 registered voters in Gainesville, Florida to measure the influence of petition-signing in spurring voter turnout. We find marginal effects in the statewide samples, but substantial and significant turnout effects in the Gainesville municipal election—an off-cycle, low-profile election. Furthermore, the effect of petition-signing—across all of our samples—is strongest among irregular, as compared to habitual, voters. These findings are in keeping with recent campaign mobilization experimental research and comport with previous findings on the “educative effects” of ballot measures on voter turnout.     

The effect of body coverings on the formation of adipocere in an aqueous environment

Adipocere is a postmortem decomposition product that consists of a mixture of fatty acids. The rate of formation of adipocere from pig adipose tissue in an aqueous environment has been monitored. The effect of various clothing and carpet material types on the process was investigated. The fatty acid composition of the adipocere was determined at regular intervals using gas chromatography-mass spectrometry. Examination of the changes to fatty acid concentrations allowed the degree of adipocere formation in the different environments to be estimated. The study demonstrated that the rate at which adipocere forms is particularly accelerated by the presence of coverings produced from natural materials. Elemental analysis by inductively coupled plasma-mass spectrometry revealed, for the most part, little change to the cations present in the adipocere formed. However, an increase in Ca concentration was observed for tissue wrapped in acrylic carpet, which was associated with a CaCO(3) additive used in the carpet manufacture.     

The consequences of perpetrating psychological aggression in dating relationships: a descriptive investigation

Psychological aggression is the most prevalent form of aggression in dating relationships, with women perpetrating as much, if not more, psychological aggression than men. Researchers have advocated for an examination of the consequences that follow psychological aggression for the perpetrator, in hopes that this will lead to innovative intervention programs aimed at ameliorating dating violence. The current study investigated the self-reported consequences of having perpetrated psychological aggression against a dating partner among female college students in a current dating relationship (N = 115). Participants endorsed numerous consequences as having followed their perpetration of psychological aggression, including both punishing and potentially reinforcing consequences. Furthermore, findings indicated that for some perpetrators, psychological aggression may function as a method of emotion regulation. Implications of these findings for future research and intervention are discussed.     

Siemens' ‘Anglo‐Saxon’ strategy: Is globalising business enough?

In the 1990s German conglomerates have attempted to move towards Anglo‐Saxon business values. Siemens saw shareholder value as the key measure of competitiveness. To become more Anglo‐Saxon, the strategy of Siemens was to globalise its business and change corporate culture. These changes have proved to be insufficient. Vertically integrated conglomerates need to break up their business empires, focus on their core competencies and move towards de‐integrated networking relations if they want high stock‐market performance.