Journal articles: 'Voting Correctly'

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Lau, Richard R., and David P. Redlawsk. "Voting Correctly." American Political Science Review 91, no. 3 (September 1997): 585–98. http://dx.doi.org/10.2307/2952076.

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The average voter falls far short of the prescriptions of classic democratic theory in terms of interest, knowledge, and participation in politics. We suggest a more realistic standard: Citizens fulfill their democratic duties if, most of the time, they vote “correctly.” Relying on an operationalization of correct voting based on fully informed interests, we present experimental data showing that, most of the time, people do indeed manage to vote correctly. We also show that voters' determinations of their correct vote choices can be predicted reasonably well with widely available survey data. We illustrate how this measure can be used to determine the proportion of the electorate voting correctly, which we calculate at about 75% for the five American presidential elections between 1972 and 1988. With a standard for correct vote decisions, political science can turn to exploring the factors that make it more likely that people will vote correctly.

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Richey, Sean. "The Social Basis of Voting Correctly." Political Communication 25, no. 4 (November 18, 2008): 366–76. http://dx.doi.org/10.1080/10584600802426973.

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Dassonneville, Ruth, Mary K. Nugent, Marc Hooghe, and Richard Lau. "Do Women Vote Less Correctly? The Effect of Gender on Ideological Proximity Voting and Correct Voting." Journal of Politics 82, no. 3 (July 2020): 1156–60. http://dx.doi.org/10.1086/707525.

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WATTS, ALISON. "The influence of social networks and homophily on correct voting." Network Science 2, no. 1 (April 2014): 90–106. http://dx.doi.org/10.1017/nws.2014.1.

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AbstractThere is empirical evidence suggesting that a person's family, friends, or social ties influence who a person votes for. Sokhey & McClurg (2012) find that as political disagreement in a person's social network increases, then a person is less likely to vote correctly. We develop a model where voters have different favorite policies and wish to vote correctly for the candidate whose favorite policy is closest to their own. Voters have beliefs about each candidate's favorite policy which may or may not be correct. Voters update their beliefs about political candidates based on who their conservative and liberal social ties are supporting. We find that if everyone's social network consists only of those most like themselves, then the conditions needed for correct voting to be stable are fairly weak; thus political agreement in one's social network facilitates correct voting. We also give conditions under which correct voting is stable for networks exhibiting homophily and for networks exhibiting random social interactions.

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Koford, Kenneth. "Dimensions in Congressional Voting." American Political Science Review 83, no. 3 (September 1989): 949–62. http://dx.doi.org/10.2307/1962068.

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While dimensional studies of congressional voting find a single, ideological dimension, regression estimates find several constituency and party dimensions in addition to ideology. I rescale several unidimensional studies to show their increased classification success over the null hypothesis that votes are not unidimensional. Several null hypotheses are explored. With these null hypotheses, 66%–75% of nonunidimensional roll call votes are nevertheless correctly classified by one dimension. After the rescaling, one dimension succeeds in correctly classifying 25%–50% of the votes, and second and third dimensions are important.

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Bergbower, Matthew L. "Campaign Intensity and Voting Correctly in Senate Elections." Journal of Elections, Public Opinion and Parties 24, no. 1 (August 25, 2013): 90–114. http://dx.doi.org/10.1080/17457289.2013.824894.

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Blais, André, Simon Labbé St-Vincent, Jean-Benoit Pilet, and Rafael Treibich. "Voting correctly in lab elections with monetary incentives." Party Politics 22, no. 4 (December 8, 2014): 544–51. http://dx.doi.org/10.1177/1354068814560933.

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PELC, ANDRZEJ. "VOTING MECHANISMS IN ASYNCHRONOUS BYZANTINE ENVIRONMENTS." Parallel Processing Letters 16, no. 01 (March 2006): 93–99. http://dx.doi.org/10.1142/s0129626406002496.

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A source sends a piece of data (message), relayed to a receiver by n processes, some of which can be faulty. We assume that the number of faulty processes is at most f and that faulty processes exhibit a Byzantine behavior. A deciding agent has to make a decision concerning the source message, on the basis of results obtained from the receiver. The environment is totally asynchronous. An Asynchronous Byzantine Voting Mechanism is a method that enables the deciding agent to always correctly determine the source message in this scenario. We show that there exists a correct Asynchronous Byzantine Voting Mechanism if and only if f < n/3. If this condition is satisfied, we provide such a mechanism. This result should be contrasted with the feasibility of synchronous voting mechansisms, in which the receiver can wait until all fault-free processes convey their values: for this scenario a correct voting mechanism exists whenever f < n/2.

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Nai, Alessandro. "The Maze and the Mirror: Voting Correctly in Direct Democracy." Social Science Quarterly 96, no. 2 (April 23, 2015): 465–86. http://dx.doi.org/10.1111/ssqu.12154.

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Blais, André, and Anja Kilibarda. "Correct Voting and Post-Election Regret." PS: Political Science & Politics 49, no. 04 (October 2016): 761–65. http://dx.doi.org/10.1017/s1049096516001372.

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ABSTRACTRegret is a basic affect associated with individual choice. While much research in organizational science and consumer behavior has assessed the precedents and consequents of regret, little attention has been paid to regret in political science. The present study assesses the relationship between one of the most democratically consequential forms of political behavior—voting—and feelings of regret. We examine the extent to which citizens regret how they voted after doing so and the factors that might lead one individual to be more regretful than another. Relying on surveys in five different countries after 11 regional and national elections, we find not only that political information leads to a decrease in post-election regret, but also that having voted correctly, or having voted in accordance with one’s underlying preferences regardless of information, similarly mitigates regret. The effect of correct voting on regret is greater among the least informed.

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Engelen, Bart. "Why Liberals Can Favour Compulsory Attendance." Politics 29, no. 3 (October 2009): 218–22. http://dx.doi.org/10.1111/j.1467-9256.2009.01358.x.

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It has been argued that compulsory voting conflicts with a number of liberal commitments, such as free thought, free speech and privacy. This article aims to show that compulsory voting, which is actually a misnomer for compulsory attendance, can in fact be defended on a liberal basis. If understood correctly, compulsory attendance laws and liberalism fit quite easily together.

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Bryant, Lisa A. "Seeing Is Believing: An Experiment on Absentee Ballots and Voter Confidence." American Politics Research 48, no. 6 (May 26, 2020): 700–704. http://dx.doi.org/10.1177/1532673x20922529.

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Since the 2000 election, researchers have taken an interest in the role of voter confidence and its importance as an assessment of public trust in electoral outcomes. Many factors may influence voter confidence including the way in which a voter casts their ballot. Previous research has found that absentee voters consistently report the lowest levels of confidence that their votes were counted correctly. This study uses an experiment to examine how voting method impacts voter confidence. Voters were randomly assigned to either an in-person or absentee voting condition. Participants assigned to the absentee condition expressed lower levels of confidence that their votes would be counted correctly than those assigned to the in-person voting condition. Voters who had to ask for assistance during the experiment also reported lower levels of confidence. This could have implications for voter confidence levels nationally as vote-by-mail continues to grow in popularity.

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Marky, Karola, Marie-Laure Zollinger, Peter Roenne, Peter Y. A. Ryan, Tim Grube, and Kai Kunze. "Investigating Usability and User Experience of Individually Verifiable Internet Voting Schemes." ACM Transactions on Computer-Human Interaction 28, no. 5 (October 31, 2021): 1–36. http://dx.doi.org/10.1145/3459604.

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Internet voting can afford more inclusive and inexpensive elections. The flip side is that the integrity of the election can be compromised by adversarial attacks and malfunctioning voting infrastructure. Individual verifiability aims to protect against such risks by letting voters verify that their votes are correctly registered in the electronic ballot box. Therefore, voters need to carry out additional tasks making human factors crucial for security. In this article, we establish a categorization of individually verifiable Internet voting schemes based on voter interactions. For each category in our proposed categorization, we evaluate a voting scheme in a user study with a total of 100 participants. In our study, we assessed usability, user experience, trust, and further qualitative data to gain deeper insights into voting schemes. Based on our results, we conclude with recommendations for developers and policymakers to inform the choices and design of individually verifiable Internet voting schemes.

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MacLaren, T., J. Townell, S. Shanmugham, V. Argent, L. De Ridder, A. Venkataraman, M. Clarke, and M. Khwaja. "Knowledge of Patients’ Voting Rights Amongst Mental Health Professionals Working in The London Borough of Westminster During The 2015 Uk General Election." European Psychiatry 33, S1 (March 2016): S450. http://dx.doi.org/10.1016/j.eurpsy.2016.01.1637.

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IntroductionBeing able to participate in elections and to vote are important components of social inclusion; empowering people with mental illness to have a voice.It is important that mental health professionals understand the voting rights of adults with mental illness in order to be able to provide appropriate advice and support.ObjectivesTo explore knowledge of the voting rights of adults living with mental illness amongst mental health professionals working in both community and inpatient settings in Westminster, London.AimsTo understand the level of knowledge amongst mental health professionals regarding the voting rights of patients with mental illness in order to identify unmet training needs.MethodsA survey, in the form of a staff quiz was undertaken in all community and inpatient teams prior to the May 2015 general election. All multidisciplinary team members were included.Resultsin total, 211 surveys were completed. Ninety-eight percent of staff correctly identified that being a psychiatric inpatient does not change an individual's right to vote. Less than 50% of the staff members demonstrated correct understanding of the rights of patients detained under forensic sections, and the rights of the homeless to vote.ConclusionsIt is encouraging that knowledge of voting rights amongst staff appeared higher in our survey than in some published surveys. However, despite the development of a Trust Voting Rights Policy and Educational Film prior to the 2015 general election further staff education, particularly the rights of those detained under forensic sections or who are homeless, is required.Disclosure of interestThe authors have not supplied their declaration of competing interest.

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Arapinis, Myrto, Nikolaos Lamprou, Elham Kashefi, and Anna Pappa. "Definitions and Security of Quantum Electronic Voting." ACM Transactions on Quantum Computing 2, no. 1 (April 2021): 1–33. http://dx.doi.org/10.1145/3450144.

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Recent advances indicate that quantum computers will soon be reality. Motivated by this ever more realistic threat for existing classical cryptographic protocols, researchers have developed several schemes to resist “quantum attacks.” In particular, for electronic voting (e-voting), several schemes relying on properties of quantum mechanics have been proposed. However, each of these proposals comes with a different and often not well-articulated corruption model, has different objectives, and is accompanied by security claims that are never formalized and are at best justified only against specific attacks. To address this, we propose the first formal security definitions for quantum e-voting protocols. With these at hand, we systematize and evaluate the security of previously proposed quantum e-voting protocols; we examine the claims of these works concerning privacy, correctness, and verifiability, and if they are correctly attributed to the proposed protocols. In all non-trivial cases, we identify specific quantum attacks that violate these properties. We argue that the cause of these failures lies in the absence of formal security models and references to the existing cryptographic literature.

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Stiers, Dieter, and Ruth Dassonneville. "Do volatile voters vote less correctly? An analysis of correct voting among vote (intention) switchers in US presidential election campaigns." Journal of Elections, Public Opinion and Parties 29, no. 3 (September 8, 2018): 283–98. http://dx.doi.org/10.1080/17457289.2018.1515210.

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Willysandro, Hansrenee, Johan Setiawan, and Agus Sulaiman. "Designing a Blockchain-Based Pemilu E-Voting Information System." IJNMT (International Journal of New Media Technology) 8, no. 1 (June 27, 2021): 42–49. http://dx.doi.org/10.31937/ijnmt.v8i1.1865.

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Data is an important thing as a base of an analytic or a hypothesis for concluding participant vote data in the Indonesian General Election. The data needs to be processed and secured, so the integrity of the data is in good condition. It also needs to protect the participant voting rights, so the information is correctly displayed. The research problems include creating a system that protects the integrity of election data and creating a system that protects election rights for each voter. Based on the problems, this research discusses a blockchain-based electronic voting information system that would secure the integrity of data and also protecting the participant voting rights in a General Election. The system uses Ethereum as a blockchain with Solidity as a programming language to build a smart contract and is built in Microsoft Windows platform. In this research, consortium blockchain and biometric fingerprint authentication are used as a problem-solving method, and waterfall steps is used as a system development method. The result of this research is a proposed design of the e-voting system. The conclusion based on this research is a blockchain-based e-voting system that secures the integrity of the data in a selection process and ensures protection to each vote right. Index Terms—Authentication; Blockchain; Data; Integrity; E-Voting; System

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van Elsas, Erika J., Emily M. Miltenburg, and Tom W. G. van der Meer. "If I recall correctly. An event history analysis of forgetting and recollecting past voting behavior." Journal of Elections, Public Opinion and Parties 26, no. 3 (March 7, 2016): 253–72. http://dx.doi.org/10.1080/17457289.2016.1150286.

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Chen, Duen Kai. "Data Mining Based Intelligent System for Voting Behavior Analysis." Applied Mechanics and Materials 284-287 (January 2013): 3070–73. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3070.

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In this study, we report a voting behavior analysis intelligent system based on data mining technology. From previous literature, we have witnessed increasing number of studies applied information technology to facilitate voting behavior analysis. In this study, we built a likely voter identification model through the use of data mining technology, the classification algorithm used here constructs decision tree model to identify voters and non voters. This model is evaluated by its accuracy and number of attributes used to correctly identify likely voter. Our goal is to try to use just a small number of survey questions while maintaining the accuracy rates of other similar models. This model was built and tested on Taiwan’s Election and Democratization Study (TEDS) data sets. According to the experimental results, the proposed model can improve likely voter identification rate and this finding is consistent with previous studies based on American National Election Studies.

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Okandeji, A., M. B. Olajide, A. A. Okubanjo, and F. Onaifo. "Design and development of biometric voting system using fingerprint and facial recognition." Nigerian Journal of Technological Research 15, no. 3 (November 23, 2020): 34–43. http://dx.doi.org/10.4314/njtr.v15i3.5.

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The election process adopted in Nigeria is mostly paper based or manual. This manually handled process can be time-consuming, and prone to security breaches and electoral fraud. Consequently, this work proposes a biometrically authenticated voting system to provide inexpensive solution to the electoral process in Nigeria. In particular, the biometric database is constructed by filling it with the audio fingerprints and the associated metadata of many audio clips, and then the fingerprint of an unknown clip (or the distorted version of the clip brought by compression or standard audio processing) is extracted and compared to that of the clip in the database. If the fingerprint of the unknown clip is in the database, it will be correctly identified by the matching procedures. The project is implemented with biometric system i.e. fingerprint scanning and facial recognition. Accordingly, this is used to ensure enhanced security, and to avoid fake, repeated voting. Results obtained showed that the proposed system is fast, accurate, reliable, and cost effective, thus a viable option to replace the manual voting process. Keywords: Biometrics, electoral process, facial recognition, finger print scanning

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Henrie, B. L., Thomas A. Mason, and J. F. Bingert. "Automated Twin Identification Technique for Use with Electron Backscatter Diffraction." Materials Science Forum 495-497 (September 2005): 191–96. http://dx.doi.org/10.4028/www.scientific.net/msf.495-497.191.

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Historically, twinning classification has been obtained by optical microscopy, bulk x-ray and neutron diffraction, and transmission electron microscopy (TEM). Recent research has shown that automated electron backscatter diffraction (EBSD) can be used to quantify twin content and thereby greatly improve the reliability of twinning statistics. An automated twin identification technique for use with EBSD has facilitated a greater understanding of deformation twinning in materials. The key features of this automated framework are the use of the crystallographic definition of twin relationships, and the correct identification of the parent orientation in a parent/twin pair. The complex nature of the parent/twin interactions required the use of a voting scheme to correctly identify parent orientations. In those few cases where the voting scheme was unable to determine parent orientation (< 2%) the algorithm allows for manual selection. Twin area fractions are categorized by operative twin systems along with secondary and tertiary twinning. These statistics are reported for deformation and annealing twin populations in deformed a-zirconium and asannealed 316L stainless steel, respectively. These improved twin statistics can help provide insight into the effect of deformation processes on microstructural evolution, as well as provide validation of plasticity models for materials that exhibit deformation twinning.

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Edie, Carlene J. "Retrospective in Commemoration of Carl Stone: Jamaican Pioneer of Political Culture." Journal of Interamerican Studies and World Affairs 39, no. 2 (1997): 135–57. http://dx.doi.org/10.2307/166513.

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The late Professor Carl Stone was perhaps best known in the academic community as a political behavioralist who pioneered the systematic study of voting behavior in Jamaica, using the Michigan model of opinion research. In the Caribbean, he was famous for his "hitting the nail on the head" election predictions, correctly predicting, in terms of the victorious party, the outcome of all national elections held in Jamaica between 1976 and 1993 and, in several instances, in terms of constituency seats and percentage of votes received.

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Zeng, Fanliang, Zuxin Li, Zhe Zhou, and Shuxin Du. "Fault Classification Decision Fusion System Based on Combination Weights and an Improved Voting Method." Processes 7, no. 11 (November 1, 2019): 783. http://dx.doi.org/10.3390/pr7110783.

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It is difficult to correctly classify all faults by using only one classifier, and the performance of most classifiers varies under different conditions. In view of this, a new decision fusion system is proposed to solve the problem of fault classification. The proposed decision fusion system is innovative in two aspects: the use of combined weights and a new improved voting method. The combined weights integrate the subjective and objective weights, where the analytic hierarchy process and entropy weight-technique for order performance by similarity to ideal solution are used to determine the subjective and objective weights of different base classifiers under multiple performance evaluation indicators. Moreover, a new improved voting method based on the concept of classifier validity is proposed to increase the accuracy of the decision system. Finally, the method is validated by the Tennessee Eastman benchmark process, and the classification accuracy of the new method is shown to be improved by more than 5.06% compared to the best base classifier.

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Loomis, John B., and Julie M. Mueller. "A Spatial Probit Modeling Approach to Account for Spatial Spillover Effects in Dichotomous Choice Contingent Valuation Surveys." Journal of Agricultural and Applied Economics 45, no. 1 (February 2013): 53–63. http://dx.doi.org/10.1017/s1074070800004570.

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We present a demonstration of a Bayesian spatial probit model for a dichotomous choice contingent valuation method willingness-to-pay (WTP) questions. If voting behavior is spatially correlated, spatial interdependence exists within the data, and standard probit models will result in biased and inconsistent estimated nonbid coefficients. Adjusting sample WTP to population WTP requires unbiased estimates of the nonbid coefficients, and we find a $17 difference in population WTP per household in a standard vs. spatial model. We conclude that failure to correctly model spatial dependence can lead to differences in WTP estimates with potentially important policy ramifications.

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Sun, Hongjun, Feihong Yu, and Haiyan Xu. "Discriminating the Nature of Thyroid Nodules Using the Hybrid Method." Mathematical Problems in Engineering 2020 (August 7, 2020): 1–13. http://dx.doi.org/10.1155/2020/6147037.

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Prompt and correct diagnosis of benign and malignant thyroid nodules has always been a core issue in the clinical practice of thyroid nodules. Ultrasound imaging is one of the most common visualizing tools used by radiologists to identify the nature of thyroid nodules. However, visual assessment of nodules is difficult and often affected by inter- and intraobserver variabilities. This paper proposes a novel hybrid approach based on machine learning and information fusion to discriminate the nature of thyroid nodules. Statistical features are extracted from the B-mode ultrasound image while deep features are extracted from the shear-wave elastography image. Classifiers including logistic regression, Naive Bayes, and support vector machine are adopted to train classification models with statistical features and deep features, respectively, for comparison. A voting system with certain criteria is used to combine two classification results to obtain a better performance. Experimental and comparison results demonstrate that the proposed method classifies the thyroid nodules correctly and efficiently.

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Ansolabehere, Stephen. "Effects of Identification Requirements on Voting: Evidence from the Experiences of Voters on Election Day." PS: Political Science & Politics 42, no. 01 (January 2009): 127–30. http://dx.doi.org/10.1017/s1049096509090313.

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At the heart of the efforts to improve elections in the United States are two important values: access and integrity. To guarantee the right to vote, the polls must be accessible to all who wish to vote. To guarantee legitimate elections, only eligible people should be allowed to vote, and all votes must be tabulated correctly. These values have different implications for administrative procedures, ranging from the implementation of registration systems to the choice of voting equipment to the set up of polling places and training of poll workers. Often these values work hand in hand, but at times they are at odds. Such is the case with the authentication of voters at the polls (see National Commission on Federal Election Reform 2002).

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Glas, Jeffrey M., Sean Richey, J. Benjamin Taylor, and Junyan Zhu. "Polls and Elections: There Is NothingWrongwith Kansas: The Effect of Race and Economics on Voting Correctly in U.S. Presidential Elections." Presidential Studies Quarterly 46, no. 1 (February 19, 2016): 158–72. http://dx.doi.org/10.1111/psq.12256.

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Kernell, Georgia. "Giving Order to Districts: Estimating Voter Distributions with National Election Returns." Political Analysis 17, no. 3 (2009): 215–35. http://dx.doi.org/10.1093/pan/mpp002.

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Correctly measuring district preferences is crucial for empirical research on legislative responsiveness and voting behavior. This article argues that the common practice of using presidential vote shares to measure congressional district ideology systematically produces incorrect estimates. I propose an alternative method that employs multiple election returns to estimate voters' ideological distributions within districts. I develop two estimation procedures—a least squared error model and a Bayesian model—and test each with simulations and empirical applications. The models are shown to outperform vote shares, and they are validated with direct measures of voter ideology and out-of-sample election predictions. Beyond estimating district ideology, these models provide valuable information on constituency heterogeneity—an important, but often immeasurable, quantity for research on representatives— strategic behavior.

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Andreadis, Ioannis, and Heiko Giebler. "Validating and Improving Voting Advice Applications: Estimating Party Positions Using Candidate Surveys." Statistics, Politics and Policy 9, no. 2 (December 19, 2018): 135–60. http://dx.doi.org/10.1515/spp-2018-0012.

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AbstractLocating political parties correctly regarding different policy issues is not just crucial for research on parties, party competition, and many similar fields but also for the electorate. For the latter, it has become more and more important as the relevance of voting advice applications (VAA) has increased and as their main usage is to compare citizens’ policy preferences to the offer of political parties. However, if party positions are not adequately assigned, citizens are provided with suboptimal information which decreases the citizens’ capacities to make rational electoral decision. VAA designers follow different approaches to determining party positions. In this paper, we look beyond most common sources like electoral manifestos and expert judgments by using surveys of electoral candidates to validate and improve VAAs. We argue that by using positions derived from candidate surveys we get the information by the source itself, but at the same time we overcome most of the disadvantages of the other methods. Using data for the 2014 European Parliament election both in Greece and Germany, we show that while positions taken from the VAAs and from the candidate surveys do match more often than not, we also find substantive differences and even opposing positions. Moreover, these occasional differences have already rather severe consequences looking at calculated overlaps between citizens and parties as well as representations of the political competition space and party system polarization. These differences seem to be more pronounced in Greece. We conclude that candidate surveys are indeed a valid additional source to validate and improve VAAs.

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Atenasio, David. "Blameless Participation in Structural Injustice." Social Theory and Practice 45, no. 2 (2019): 149–77. http://dx.doi.org/10.5840/soctheorpract201942655.

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According to Iris Marion Young, a structural injustice occurs when members participating in one or more scheme(s) of social coordination act blamelessly, but the schemes, in combination with norms and background conditions, systematically prevent some from developing their capacities and fulfilling their rights. Because participants are mostly blameless, Young argues that traditional individualist theories of responsibility inadequately address structural injustices. Young instead proposes a social connection theory of responsibility, whereby participants in a structural injustice acquire forward-looking responsibilities to remediate the injustice by organizing, voting, protesting and pressuring institutions. In this paper, I argue that Young’s theory of structural injustice conflates several different moral failings, and that when we correctly disambiguate structural injustices, we can successfully address them with traditional individualist theories of responsibility, both forward-looking and backward-looking.

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Bhatt, Mittal, Vishal Dahiya, and Arvind K. Singh. "A Comparative Analysis of Classificaton methods for Diagnosis of Lower Back Pain." Oriental journal of computer science and technology 11, no. 2 (June 7, 2018): 135–39. http://dx.doi.org/10.13005/ojcst11.02.09.

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In this paper different classification methods are compared using base and meta(Combination of Multiple Classifier for training) level classifiers, for the fruitful diagnosis of Lower Back Pain. The Lower Back Pain becomes chronic with age, so needs to be correctly diagnose with symptoms in the early age. Five independent classifiers were implemented at base level and meta level. At meta level, five combinations of different classifiers were implemented, using voting technique. According to the scores, the overall classification using Naïve Bayes and Multilayer Perceptron got the maximum efficiency 83.87%. The purpose of this paper is to diagnose healthy individuals efficiently. To carry out study the Lower Back Pain Symptoms Dataset is used from very famous platform for predictive modeling, Kaggle. The experiments were carried out in WEKA (Waikato Environment for Knowledge Analysis), suite of machine learning software1.

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Wilson, Elizabeth J., and David A. Paleologos. "Usage and performance of bellwether polls for election forecasting." International Journal of Market Research 60, no. 2 (February 11, 2018): 132–46. http://dx.doi.org/10.1177/1470785317753097.

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A non-traditional methodology of polling in small areas, called bellwethers, improves the accuracy of forecasts drawn from a large area. Bellwether areas are small government units (such as cities or counties) which exhibit voting patterns close to actual election outcomes in the larger areas of which they are a part (such as states). The bellwether methodology of one polling organization is described in detail using data from the 2012 US Senate election in Massachusetts. An overview of the performance of the bellwether methodology is provided. In use at Suffolk University Political Research Center since 2003, bellwethers combined with state polls correctly forecast election outcomes in 97% of trials where a clear winner could be determined (i.e., no ties). The contribution of this work is to offer an open-source methodology for improving accuracy in election forecasting.

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Kheliya, T. G., S. Yu Martsevich, G. B. Selivanova, Yu V. Lukina, L. Yu Drozdova, and V. P. Voronina. "Knowledge of modern principles of rational cardiovascular therapy in Moscow primary care physicians: survey-based assessment." Cardiovascular Therapy and Prevention 11, no. 5 (October 20, 2012): 61–66. http://dx.doi.org/10.15829/1728-8800-2012-5-61-66.

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Aim. To assess the knowledge of primary care physicians on the choice of medications for the long-term treatment of cardiovascular disease (CVD); on the control of pharmacological therapy effectiveness and safety; and on the selection of optimal medications for specific clinical situations. Material and methods. In 2010, a voluntary survey of Moscow physicians working at specialised and municipal out-patient clinics was conducted. The number of participants was 281 (response rate 70%). Results. Thirty percent of the physicians correctly identified a selective β-adrenoblocker (β-AB) from the list of various medications. Typical adverse effects of statins, β-ABs, and calcium antagonists were known to 33%, 66,4%, and 38%, respectively. Every fifth respondent (22,6%) would recommend ACE inhibitors or angiotensin II receptor antagonists (captopril or losartan) to pregnant women. Sixty six percent of the participants identified the patients’ unwillingness to simultaneously take many medications and the fear of adverse effects (AE) as the major barriers to prescribing modern complex pharmacological therapy. Conclusion. Specialised questionnaires, used for interactive voting, and point-based assessment system provided an opportunity to identify the inadequate physicians’ knowledge of pharmacological therapyrelated AE and of the AE registration system. Poor knowledge of clinical recommendations affects the physicians’ ability to make correct decisions in specific clinical situations.

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Holloway, Jenny P., Hans W. Ittmann, Nontombeko Dudeni-Tlhone, and Peter MU Schmitz. "From SA to the USA: Election forecasting." ORiON 34, no. 2 (January 14, 2019): 83–106. http://dx.doi.org/10.5784/34-2-581.

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Elections draw enormous interest worldwide, especially if these involve major countries, and there is much speculation in the media as to possible outcomes from these elections. In many of these recent elections, such as the UK and USA, however, forecasts from market surveys, electoral polls, scientific forecasting models and even exit polls, obtained from voters as they leave the voting stations, failed to predict the correct outcome. Election night forecasts, which endeavour to forecast the ultimate result before the final outcome is known using early results, were also carried out, with some more accurate than others.After successfully predicting most of the metropolitan region results correctly in the South African local 2016 municipal elections, using an election night forecasting model developed for South Africa (SA), the question of adapting the model to work outside of SA on a different electoral system was raised. The focus of this paper is to describe the results obtained for the 2016 USA presidential election, on election night, using an adapted version of the SA model. This paper also addresses the applicability of the model assumptions as well as the data issues involved in forecasting outside of South Africa. It is shown that even with many hurdles experienced in the process the model performed relatively well.

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Luo, Chih-Mei. "Brexit and its Implications for European Integration." European Review 25, no. 4 (September 6, 2017): 519–31. http://dx.doi.org/10.1017/s1062798717000308.

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On the eve of 60th anniversary of the Treaty of Rome, the UK voted to withdraw from the EU (so-called Brexit). The implications for European integration and EU policies are far from clear and require further investigation. This paper aims to answer: what does Brexit imply for European integration? What messages were sent to the EU from the UK referendum? Did EU leaders interpret these messages and implications correctly and did they respond with the right policy? After examining the competing interpretations, this paper argues that the sharp divisions between different socio-economic classes shown in voting behaviour highlight the imperative of addressing economic inequality and distributive injustice, which are rooted in the structural flaws of EU governance and have been aggravated by the mismanagement of the Euro crisis. To move European integration forward and to keep a ‘political Europe’ sustainable, a ‘social Europe’ making an ‘economic Europe’ more inclusive and fair is required.

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Sidey-Gibbons, Chris, Charlotte C. Sun, Cai Xu, Amy Schneider, Sheng-Chieh Lu, Ishwaria Mohan Subbiah, Alexi A. Wright, and Larissa Meyer. "Predicting 180-day mortality for women with ovarian cancer using machine learning and patient-reported outcome data." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): e13555-e13555. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e13555.

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e13555 Background: Contra to national guidelines, women with ovarian cancer often receive aggressive treatment until the end-of-life. We trained machine learning algorithms to predict mortality within 180 days for women with ovarian cancer. Methods: Data were collected data from a single academic cancer institution in the United States. Women with recurrent ovarian cancer completed biopsychosocial patient-reported outcome measures (PROMs) every 90 days. We randomly partitioned our dataset into training and testing samples with a 2:1 ratio. We used synthetic minority oversampling to reduce class imbalance in the training dataset. We fitted training data to six machine learning algorithms and combined their classifications on the testing dataset into a voting ensemble. We assessed the accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) for each algorithm. Results: We recruited 245 patients who completed 1319 assessments. The final voting ensemble performed well across all performance metrics (Accuracy = .79, Sensitivity = .71, Specificity = .80, AUROC = .76). The algorithm correctly identified 25 of the 35 women in the testing dataset who died within 180 days of assessment Conclusions: Machine learning algorithms trained using PROM data offer state-of-the-art performance in predicting whether a woman with ovarian cancer will reach the end-of-life within 180 days. We highlight the importance of PROM data in ML models of mortality. Our model exhibits substantial improvements in prediction sensitivity compared to other similar models trained using electronic health record data alone. This model could inform clinical decision making and improve the uptake of appropriate end-of-life care. Further research is warranted to expand on these findings in a larger, more diverse sample.

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Attallah, Omneya, Alan Karthikesalingam, Peter JE Holt, Matthew M. Thompson, Rob Sayers, Matthew J. Bown, Eddie C. Choke, and Xianghong Ma. "Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 231, no. 11 (September 19, 2017): 1048–63. http://dx.doi.org/10.1177/0954411917731592.

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Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox’s proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data. However, it depends on data replication to handle censoring which leads to unbalanced and biased prediction results especially in highly censored data. Other methods cannot deal with high censoring. Therefore, in this article, a new hybrid feature selection method is proposed which presents a solution to high level censoring. It combines support vector machine, neural network, and K-nearest neighbor classifiers using simple majority voting and a new weighted majority voting method based on survival metric to construct a multiple classifier system. The new hybrid feature selection process uses multiple classifier system as a wrapper method and merges it with iterated feature ranking filter method to further reduce features. Two endovascular aortic repair datasets containing 91% censored patients collected from two centers were used to construct a multicenter study to evaluate the performance of the proposed approach. The results showed the proposed technique outperformed individual classifiers and variable selection methods based on Cox’s model such as Akaike and Bayesian information criterions and least absolute shrinkage and selector operator in p values of the log-rank test, sensitivity, and concordance index. This indicates that the proposed classifier is more powerful in correctly predicting the risk of re-intervention enabling doctor in selecting patients’ future follow-up plan.

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Perezhniak, Boris, Catherine Karmazina, Ruslana Dudnyk, Kostiantyn Solyannik, and Oleksandra Severinova. "Electronic technologies during local elections: new challenges." Cuestiones Políticas 38, Especial II (December 8, 2020): 287–301. http://dx.doi.org/10.46398/cuestpol.382e.22.

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The COVID-19 pandemic poses new challenges, as no one can propresa will burst a new wave of morbidity. It is therefore worth thinking about the implementation of the electronic voting procedure. In view of this, it is important to explore the role of electronic technology in local elections, share it with the experience of several countries, as well as as analyse new opportunities for the transformation of the electoral process. The aim of the work is to study the role of electronic technologies during local elections. The subject of research is electronic technologies during local elections and social relationships that arise, change and end during the use of electronic processes during local elections. The research methodology combined a set of philosophical, general, and special approaches to scientific knowledge. A study of electronic technologies in local elections has shown that electronic technologies play an important role in electoral processes. It is concluded that, under modern conditions, it is important for Ukraine to support the electoral process with the latest electronic technologies, because these technologies, if used correctly, ensuring election democracy and greater the efficiency of democracy institutions represents.

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He, Wenjing, Hongjun Song, Yuanyuan Yao, and Xinlin Jia. "A Multiscale Method for Road Network Extraction from High-Resolution SAR Images Based on Directional Decomposition and Regional Quality Evaluation." Remote Sensing 13, no. 8 (April 12, 2021): 1476. http://dx.doi.org/10.3390/rs13081476.

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Road network is an important part of modern transportation. For the demands of accurate road information in practical applications such as urban planning and disaster assessment, we propose a multiscale method to extract road network from high-resolution synthetic aperture radar (SAR) images, which consists of three stages: potential road area segmentation, preliminary network generation, and road network refinement. Multiscale analysis is implemented using an image pyramid framework together with a fixed-size filter. First, a directional road detector is designed to highlight road targets in feature response maps. Subsequently, adaptive fusion is performed independently at each image scale, followed by a threshold method to produce potential road maps. Then, binary maps are decomposed according to the obtained direction information. For each connected component (CC), quality evaluation is conducted to further distinguish road segments and polynomial curve fitting is adopted as a thinning method. Multiscale information fusion is realized through the weighted sum of road curves. Finally, tensor voting and spatial regularization are employed to generate the final road network. Experiments on three TerraSAR images demonstrate the effectiveness of the proposed algorithm to extract road network completely and correctly.

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Tebueva, Fariza, Sergey Ryabtsev, and Igor Struchkov. "A method of counteracting Byzantine robots with a random behavior strategy during collective design-making in swarm robotic systems." E3S Web of Conferences 270 (2021): 01034. http://dx.doi.org/10.1051/e3sconf/202127001034.

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The active introduction of robotics swarm systems into life brings the issues of their information security up to date. Known security approaches often do not take into account the peculiarities of the implementation of swarm systems, such as collective design-making, and only consider the presence of Byzantine robots with a strategy of behavior consisting in voting against a majority when a consensus is reached. The aim of this work is to increase the security of the collective design-making process in a swarm robotics system from the imposition of false and ineffective alternatives by Byzantine robots with a random behavior strategy. It is proposed to use an approach based on the use of a distributed ledger and analysis of deviations in the process of collective design-making, which will allow identifying and isolating harmful effects. The solution to the problem of detecting Byzantine robots is based on the application of the criterion of the degree of confidence of a robot in choosing an alternative when a consensus is reached by the swarm system and is based on the assumption that the distribution of the degree of confidence of a Byzantine robot due to ignoring the parameters of the external environment and voting for random alternatives is significantly different from the behavior an ordinary robot. The elements of novelty of the presented solution include the use of the degree of confidence criterion to ensure the safety of collective design-making and the ability to take into account various strategies of behavior of Byzantine robots. The use of the presented solution makes it possible to increase the efficiency of reaching consensus by a swarm robotics system in the presence of Byzantine robots. The simulation for a swarm of 20 robots, including 5 Byzantine ones with random behavior, showed an increase in the probability of correctly reaching a consensus by 12.5%. The practical significance of the presented solutions lies in the possibility of ensuring the stability of reaching consensus by a swarm robotics system in the presence of robots with harmful behavior.

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Sewak, Mihir S., Narender P. Reddy, and Zhong-Hui Duan. "Gene Expression Based Leukemia Sub-Classification Using Committee Neural Networks." Bioinformatics and Biology Insights 3 (January 2009): BBI.S2908. http://dx.doi.org/10.4137/bbi.s2908.

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Analysis of gene expression data provides an objective and efficient technique for sub-classification of leukemia. The purpose of the present study was to design a committee neural networks based classification systems to subcategorize leukemia gene expression data. In the study, a binary classification system was considered to differentiate acute lymphoblastic leukemia from acute myeloid leukemia. A ternary classification system which classifies leukemia expression data into three subclasses including B-cell acute lymphoblastic leukemia, T-cell acute lymphoblastic leukemia and acute myeloid leukemia was also developed. In each classification system gene expression profiles of leukemia patients were first subjected to a sequence of simple preprocessing steps. This resulted in filtering out approximately 95 percent of the non-informative genes. The remaining 5 percent of the informative genes were used to train a set of artificial neural networks with different parameters and architectures. The networks that gave the best results during initial testing were recruited into a committee. The committee decision was by majority voting. The committee neural network system was later evaluated using data not used in training. The binary classification system classified microarray gene expression profiles into two categories with 100 percent accuracy and the ternary system correctly predicted the three subclasses of leukemia in over 97 percent of the cases.

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Bethlehem, Jelke. "The Representativity of Election Polls." Statistics, Politics and Policy 8, no. 1 (January 1, 2017): 1–12. http://dx.doi.org/10.1515/spp-2016-0002.

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AbstractElection polls are conducted in many countries during election campaigns. Provided such polls are set up and carried out correctly, they can give an accurate indication of the voting intentions of people. However, the last couple of years these polls seem to be less able to predict election results. Examples are the polls for the general election in the UK of 2015, the Brexit referendum in the UK, and the presidential election in the US of 2016. The polls in the UK and the US have all in common that they are either telephone polls or online polls. It is shown in this paper that both type of polls suffer from lack of representativity. The compositions of their samples differ from that of the population. This can have several causes. For telephone polls, problems are mainly caused by increasing nonresponse rates, and lack of proper sampling frames. Most online polls are based on samples from web panels that are recruited by means of self-selection instead of random samples. Such web panels also not representative. The paper analyses the shortcomings of these election polls. The problems are illustrated by describing the polls in the UK and the US in some more detail.

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Luna-Garcia, H., A. Mendoza-Gonzalez, R. Mendoza-Gonzalez, H. Gamboa-Rosales, J. I. Galván-Tejada, J. M. Celaya-Padilla, C. E. Galvan-Tejada, et al. "Analyzing Typical Mobile Gestures in mHealth Applications for Users with Down Syndrome." Mobile Information Systems 2018 (July 11, 2018): 1–9. http://dx.doi.org/10.1155/2018/2830851.

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Mobile technology has provided many advantages for all members of the Information Society. Communication, Organization, Transportation, Health, and Entertainment are just a few areas of mobile technology application. Nevertheless, there are still some people who find difficulties using it. Although there are a lot of applications of mHealth available for almost any kind of mobile device, there is still a lack of understanding and attending users’ needs, especially those of users with disabilities. People with Down syndrome have the potential to function as active members of our society, taking care of themselves and their own, having jobs, voting, and so on, but their physical limitations prevent them from handling correctly technological tools that could enhance their performance, including mobile technology. In this paper, we had analyzed how suitable the mHealth applications are for users with Down syndrome. We tested 24 users and analyzed their physical performance in fine-motor movements while developing a set of tasks over a mHealth application. Results showed that the design of a mHealth application for users with Down syndrome must center its interaction with simple gestures as tap and swipe avoiding more complex ones as spread and rotate. This research is a starting point to understand the fundamentals of people with Down syndrome interacting with mobile technology.

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Yang, Bin, Chunxiang Cao, Ying Xing, and Xiaowen Li. "Automatic Classification of Remote Sensing Images Using Multiple Classifier Systems." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/954086.

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It is a challenge to obtain accurate result in remote sensing images classification, which is affected by many factors. In this paper, aiming at correctly identifying land use types reflec ted in remote sensing images, support vector machine, maximum likelihood classifier, backpropagation neural network, fuzzy c-means, and minimum distance classifier were combined to construct three multiple classifier systems (MCSs). Two MCSs were implemented, namely, comparative major voting (CMV) and Bayesian average (BA). One method called WA-AHP was proposed, which introduced analytic hierarchy process into MCS. Classification results of base classifiers and MCSs were compared with the ground truth map. Accuracy indicators were computed and receiver operating characteristic curves were illustrated, so as to evaluate the performance of MCSs. Experimental results show that employing MCSs can increase classification accuracy significantly, compared with base classifiers. From the accuracy evaluation result and visual check, the best MCS is WA-AHP with overall accuracy of 94.2%, which overmatches BA and rivals CMV in this paper. The producer’s accuracy of each land use type proves the good performance of WA-AHP. Therefore, we can draw the conclusion that MCS is superior to base classifiers in remote sensing image classification, and WA-AHP is an efficient MCS.

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Bernal-Orozco, María Fernanda, Patricia Belen Salmeron-Curiel, Ruth Jackelyne Prado-Arriaga, Jaime Fernando Orozco-Gutiérrez, Nayeli Badillo-Camacho, Fabiola Márquez-Sandoval, Martha Betzaida Altamirano-Martínez, et al. "Second Version of a Mini-Survey to Evaluate Food Intake Quality (Mini-ECCA v.2): Reproducibility and Ability to Identify Dietary Patterns in University Students." Nutrients 12, no. 3 (March 19, 2020): 809. http://dx.doi.org/10.3390/nu12030809.

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Evaluation of food intake quality using validated tools makes it possible to give individuals or populations recommendations for improving their diet. This study’s objective was to evaluate the reproducibility and ability to identify dietary patterns of the second version of the Mini Food Intake Quality Survey (Mini-ECCA v.2). The survey was administered using a remote voting system on two occasions with four-week intervals between administrations to 276 health science students (average age = 20.1 ± 3.1 years; 68% women). We then performed a per-question weighted kappa calculation, a cluster analysis, an ANOVA test by questionnaire item and between identified clusters, and a discriminant analysis. Moderate to excellent agreement was observed (weighted κ = 0.422–0.662). The cluster analysis identified three groups, and the discriminant analysis obtained three classification functions (85.9% of cases were correctly classified): group 1 (19.9%) was characterized by higher intake of water, vegetables, fruit, fats, oilseeds/avocado, meat and legumes (healthy food intake); group 2 (47.1%) frequently consumed both fish and unhealthy fats (habits in need of improvement); group 3 (33%) frequently consumed sweetened beverages, foods not prepared at home, processed foods, refined cereals and alcohol (unhealthy food intake). In conclusion, the Mini-ECCA v.2 has moderate to excellent agreement, and it is able to identify dietary patterns in university students.

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Milic, Thomas. "Correct Voting in Direct Legislation." Swiss Political Science Review 18, no. 4 (December 2012): 399–427. http://dx.doi.org/10.1111/spsr.12000.

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Ha, Shang E., and Richard R. Lau. "Personality Traits and Correct Voting." American Politics Research 43, no. 6 (January 23, 2015): 975–98. http://dx.doi.org/10.1177/1532673x14568551.

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Sokhey, Anand Edward, and Scott D. McClurg. "Social Networks and Correct Voting." Journal of Politics 74, no. 3 (July 2012): 751–64. http://dx.doi.org/10.1017/s0022381612000461.

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Hajek, Bruce, Yihong Wu, and Jiaming Xu. "Recovering a hidden community beyond the Kesten–Stigum threshold in O(|E|log*|V|) time." Journal of Applied Probability 55, no. 2 (June 2018): 325–52. http://dx.doi.org/10.1017/jpr.2018.22.

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Abstract Community detection is considered for a stochastic block model graph of n vertices, with K vertices in the planted community, edge probability p for pairs of vertices both in the community, and edge probability q for other pairs of vertices. The main focus of the paper is on weak recovery of the community based on the graph G, with o(K) misclassified vertices on average, in the sublinear regime n1-o(1) ≤ K ≤ o(n). A critical parameter is the effective signal-to-noise ratio λ = K2(p - q)2 / ((n - K)q), with λ = 1 corresponding to the Kesten–Stigum threshold. We show that a belief propagation (BP) algorithm achieves weak recovery if λ > 1 / e, beyond the Kesten–Stigum threshold by a factor of 1 / e. The BP algorithm only needs to run for log*n + O(1) iterations, with the total time complexity O(|E|log*n), where log*n is the iterated logarithm of n. Conversely, if λ ≤ 1 / e, no local algorithm can asymptotically outperform trivial random guessing. Furthermore, a linear message-passing algorithm that corresponds to applying a power iteration to the nonbacktracking matrix of the graph is shown to attain weak recovery if and only if λ > 1. In addition, the BP algorithm can be combined with a linear-time voting procedure to achieve the information limit of exact recovery (correctly classify all vertices with high probability) for all K ≥ (n / logn) (ρBP + o(1)), where ρBP is a function of p / q.

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Mohamed, Hassan, Kazuo Nadaoka, and Takashi Nakamura. "Towards Benthic Habitat 3D Mapping Using Machine Learning Algorithms and Structures from Motion Photogrammetry." Remote Sensing 12, no. 1 (January 1, 2020): 127. http://dx.doi.org/10.3390/rs12010127.

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The accurate classification and 3D mapping of benthic habitats in coastal ecosystems are vital for developing management strategies for these valuable shallow water environments. However, both automatic and semiautomatic approaches for deriving ecologically significant information from a towed video camera system are quite limited. In the current study, we demonstrate a semiautomated framework for high-resolution benthic habitat classification and 3D mapping using Structure from Motion and Multi View Stereo (SfM-MVS) algorithms and automated machine learning classifiers. The semiautomatic classification of benthic habitats was performed using several attributes extracted automatically from labeled examples by a human annotator using raw towed video camera image data. The Bagging of Features (BOF), Hue Saturation Value (HSV), and Gray Level Co-occurrence Matrix (GLCM) methods were used to extract these attributes from 3000 images. Three machine learning classifiers (k-nearest neighbor (k-NN), support vector machine (SVM), and bagging (BAG)) were trained by using these attributes, and their outputs were assembled by the fuzzy majority voting (FMV) algorithm. The correctly classified benthic habitat images were then geo-referenced using a differential global positioning system (DGPS). Finally, SfM-MVS techniques used the resulting classified geo-referenced images to produce high spatial resolution digital terrain models and orthophoto mosaics for each category. The framework was tested for the identification and 3D mapping of seven habitats in a portion of the Shiraho area in Japan. These seven habitats were corals (Acropora and Porites), blue corals (H. coerulea), brown algae, blue algae, soft sand, hard sediments (pebble, cobble, and boulders), and seagrass. Using the FMV algorithm, we achieved an overall accuracy of 93.5% in the semiautomatic classification of the seven habitats.

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Journal articles on the topic 'Voting Correctly'

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