3,585 research outputs found

    Financing Direct Democracy: Revisiting the Research on Campaign Spending and Citizen Initiatives

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    The conventional view in the direct democracy literature is that spending against a measure is more effective than spending in favor of a measure, but the empirical results underlying this conclusion have been questioned by recent research. We argue that the conventional finding is driven by the endogenous nature of campaign spending: initiative proponents spend more when their ballot measure is likely to fail. We address this endogeneity by using an instrumental variables approach to analyze a comprehensive dataset of ballot propositions in California from 1976 to 2004. We find that both support and opposition spending on citizen initiatives have strong, statistically significant, and countervailing effects. We confirm this finding by looking at time series data from early polling on a subset of these measures. Both analyses show that spending in favor of citizen initiatives substantially increases their chances of passage, just as opposition spending decreases this likelihood

    Stratosphere‐troposphere coupling and annular mode variability in chemistry‐climate models

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    The internal variability and coupling between the stratosphere and troposphere in CCMVal‐2 chemistry‐climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the models’ annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a well‐simulated stratosphere can improve simulation of tropospheric intraseasonal variability

    Conceptual and methodological advances in habitat-selection modeling: guidelines for ecology and evolution

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    Habitat selection is a fundamental animal behavior that shapes a wide range of ecological processes, including animal movement, nutrient transfer, trophic dynamics and population distribution. Although habitat selection has been a focus of ecological studies for decades, technological, conceptual and methodological advances over the last 20 yr have led to a surge in studies addressing this process. Despite the substantial literature focused on quantifying the habitat-selection patterns of animals, there is a marked lack of guidance on best analytical practices. The conceptual foundations of the most commonly applied modeling frameworks can be confusing even to those well versed in their application. Furthermore, there has yet to be a synthesis of the advances made over the last 20 yr. Therefore, there is a need for both synthesis of the current state of knowledge on habitat selection, and guidance for those seeking to study this process. Here, we provide an approachable overview and synthesis of the literature on habitat-selection analyses (HSAs) conducted using selection functions, which are by far the most applied modeling framework for understanding the habitat-selection process. This review is purposefully non-technical and focused on understanding without heavy mathematical and statistical notation, which can confuse many practitioners. We offer an overview and history of HSAs, describing the tortuous conceptual path to our current understanding. Through this overview, we also aim to address the areas of greatest confusion in the literature. We synthesize the literature outlining the most exciting conceptual advances in the field of habitat-selection modeling, discussing the substantial ecological and evolutionary inference that can be made using contemporary techniques. We aim for this paper to provide clarity for those navigating the complex literature on HSAs while acting as a reference and best practices guide for practitioners

    Agricultural climate change mitigation : Carbon calculators as a guide for decision making

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    This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of Agricultural Sustainability on 9 November 2017, available online: https://doi.org/10.1080/14735903.2017.1398628. Under embargo. Embargo end date: 9 November 2018.The dairy industry is receiving considerable attention in relation to both its significant greenhouse gas (GHG) emissions, and it’s potential for reducing those emissions, contributing towards meeting national targets and driving the industry towards sustainable intensification. However, the extent to which improvements can be made is dependent on the decision making processes of individual producers, so there has been a proliferation of carbon accounting tools seeking to influence those processes. This paper evaluates the suitability of such tools for driving environmental change by influencing on-farm management decisions. Seven tools suitable for the European dairy industry were identified, their characteristics evaluated, and used to process data relating to six scenario farms, emulating process undertaken in real farm management situations. As a result of the range of approaches taken by the tools, there was limited agreement between them as to GHG emissions magnitude, and no consistent pattern as to which tools resulted in the highest/lowest results. Despite this it is argued, that as there was agreement as to the farm activities responsible for the greatest emissions, the more complex tools were still capable of performing a ‘decision support’ role, and guiding management decisions, whilst others could merely focus attention on key issues.Peer reviewe

    Risk of Lower Extremity Injury in a Military Cadet Population After a Supervised Injury-Prevention Program

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    Specific movement patterns have been identified as possible risk factors for noncontact lower extremity injuries. The Dynamic Integrated Movement Enhancement (DIME) was developed to modify these movement patterns to decrease injury risk

    Voting Technology, Vote-by-Mail, and Residual Votes in California, 1990-2010

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    This paper examines how the growth in vote-by-mail and changes in voting technologies led to changes in the residual vote rate in California from 1990 to 2010. We find that in California’s presidential elections, counties that abandoned punch cards in favor of optical scanning enjoyed a significant improvement in the residual vote rate. However, these findings do not always translate to other races. For instance, find that the InkaVote system in Los Angeles has been a mixed success, performing very well in presidential and gubernatorial races, fairly well for ballot propositions, and poorly in Senate races. We also conduct the first analysis of the effects of the rise of vote-by-mail on residual votes. Regardless of the race, increased use of the mails to cast ballots is robustly associated with a rise in the residual vote rate. The effect is so strong that the rise of voting by mail in California has mostly wiped out all the reductions in residual votes that were due to improved voting technologies since the early 1990s

    Tests of the Equivalence Principle with Neutral Kaons

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    We test the Principle of Equivalence for particles and antiparticles, using CPLEAR data on tagged K0 and K0bar decays into pi^+ pi^-. For the first time, we search for possible annual, monthly and diurnal modulations of the observables |eta_{+-}| and phi_{+-}, that could be correlated with variations in astrophysical potentials. Within the accuracy of CPLEAR, the measured values of |eta_{+-}| and phi_{+-} are found not to be correlated with changes of the gravitational potential. We analyze data assuming effective scalar, vector and tensor interactions, and we conclude that the Principle of Equivalence between particles and antiparticles holds to a level of 6.5, 4.3 and 1.8 x 10^{-9}, respectively, for scalar, vector and tensor potentials originating from the Sun with a range much greater than the distance Earth-Sun. We also study energy-dependent effects that might arise from vector or tensor interactions. Finally, we compile upper limits on the gravitational coupling difference between K0 and K0bar as a function of the scalar, vector and tensor interaction range.Comment: 15 pages latex 2e, five figures, one style file (cernart.csl) incorporate

    Diagnosis of obstructive coronary artery disease using computed tomography angiography in patients with stable chest pain depending on clinical probability and in clinically important subgroups: meta-analysis of individual patient data

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    OBJECTIVE: To determine whether coronary computed tomography angiography (CTA) should be performed in patients with any clinical probability of coronary artery disease (CAD), and whether the diagnostic performance differs between subgroups of patients. DESIGN: Prospectively designed meta-analysis of individual patient data from prospective diagnostic accuracy studies. DATA SOURCES: Medline, Embase, and Web of Science for published studies. Unpublished studies were identified via direct contact with participating investigators. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Prospective diagnostic accuracy studies that compared coronary CTA with coronary angiography as the reference standard, using at least a 50% diameter reduction as a cutoff value for obstructive CAD. All patients needed to have a clinical indication for coronary angiography due to suspected CAD, and both tests had to be performed in all patients. Results had to be provided using 2×2 or 3×2 cross tabulations for the comparison of CTA with coronary angiography. Primary outcomes were the positive and negative predictive values of CTA as a function of clinical pretest probability of obstructive CAD, analysed by a generalised linear mixed model; calculations were performed including and excluding non-diagnostic CTA results. The no-treat/treat threshold model was used to determine the range of appropriate pretest probabilities for CTA. The threshold model was based on obtained post-test probabilities of less than 15% in case of negative CTA and above 50% in case of positive CTA. Sex, angina pectoris type, age, and number of computed tomography detector rows were used as clinical variables to analyse the diagnostic performance in relevant subgroups. RESULTS: Individual patient data from 5332 patients from 65 prospective diagnostic accuracy studies were retrieved. For a pretest probability range of 7-67%, the treat threshold of more than 50% and the no-treat threshold of less than 15% post-test probability were obtained using CTA. At a pretest probability of 7%, the positive predictive value of CTA was 50.9% (95% confidence interval 43.3% to 57.7%) and the negative predictive value of CTA was 97.8% (96.4% to 98.7%); corresponding values at a pretest probability of 67% were 82.7% (78.3% to 86.2%) and 85.0% (80.2% to 88.9%), respectively. The overall sensitivity of CTA was 95.2% (92.6% to 96.9%) and the specificity was 79.2% (74.9% to 82.9%). CTA using more than 64 detector rows was associated with a higher empirical sensitivity than CTA using up to 64 rows (93.4% v 86.5%, P=0.002) and specificity (84.4% v 72.6%, P<0.001). The area under the receiver-operating-characteristic curve for CTA was 0.897 (0.889 to 0.906), and the diagnostic performance of CTA was slightly lower in women than in with men (area under the curve 0.874 (0.858 to 0.890) v 0.907 (0.897 to 0.916), P<0.001). The diagnostic performance of CTA was slightly lower in patients older than 75 (0.864 (0.834 to 0.894), P=0.018 v all other age groups) and was not significantly influenced by angina pectoris type (typical angina 0.895 (0.873 to 0.917), atypical angina 0.898 (0.884 to 0.913), non-anginal chest pain 0.884 (0.870 to 0.899), other chest discomfort 0.915 (0.897 to 0.934)). CONCLUSIONS: In a no-treat/treat threshold model, the diagnosis of obstructive CAD using coronary CTA in patients with stable chest pain was most accurate when the clinical pretest probability was between 7% and 67%. Performance of CTA was not influenced by the angina pectoris type and was slightly higher in men and lower in older patients. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42012002780
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