Project description:Gun-related deaths are on the rise in the US, and following recent mass shootings, gun policy has emerged as an issue in the 2020 election cycle. Political advertising is an increasingly important tool for candidates seeking office to communicate their policy priorities. Over $6 billion was spent on political ads in the 2016 election cycle, and spending in the 2020 cycle is expected to be even higher. Tracking gun-related political advertising over time can offer critical insights into how candidates view the salience of gun policy in the context of the 2020 election and beyond. We analyzed the coverage of guns in over fourteen million candidate-related television ad airings for presidential, congressional, gubernatorial, and state legislative races over four election cycles: 2012, 2014, 2016, and 2018. The share of candidate-related ad airings that referred to guns increased from 1 percent in the 2012 cycle to over 8 percent in the 2018 cycle. Pro-gun rights content dominated but dropped from 86 percent of airings mentioning guns in the 2012 cycle to 45 percent in the 2018 cycle. Advertising in favor of gun regulation and against the National Rifle Association increased over time. These shifts offer insights into how gun issues are being framed in the 2020 election cycle.
Project description:Mass elections are key mechanisms for collective decision-making. But they are also blamed for creating intergroup enmity, particularly while they are underway; politicians use polarizing campaign strategies, and losing sides feel resentful and marginalized after results are announced. I investigate the impact of election proximity-that is, closeness to elections in time-on social cleavages related to religion, a salient form of group identity worldwide. Integrating data from ∼1.2 million respondents across 25 cross-country survey series, I find no evidence that people interviewed shortly before or after national elections are more likely to express negative attitudes toward religious outgroups than those interviewed at other times. Subgroup analysis reveals little heterogeneity, including by levels of political competition. Generalized social trust, too, is unaffected by election calendars. Elections may not pose as great a risk to social cohesion as is commonly feared.
Project description:Recently we have witnessed a number of rapid shifts toward populism in the rhetoric and policies of major political parties, as exemplified in the 2016 Brexit Referendum, 2016 US Election, and 2017 UK General Election. Our perspective here is to focus on understanding the underlying societal processes behind these recent political shifts. We use novel methods to study social dynamics behind the 2016 Presidential election. This is done by using network science methods to identify key groups associated with the US right-wing during the election. We investigate how the groups grew on Twitter, and how their associated accounts changed their following behaviour over time. We find a new external faction of Trump supporters took a strong influence over the traditional Republican Party (GOP) base during the election campaign. The new group dominated the GOP group in terms of new members and endorsement via Twitter follows. Growth of new accounts for the GOP party all but collapsed during the campaign. While the Alt-right group was growing exponentially, it has remained relatively isolated. Counter to the mainstream view, we detected an unexpectedly low number of automated 'bot' accounts and accounts associated with foreign intervention in the Trump-supporting group. Our work demonstrates a powerful method for tracking the evolution of societal groups and reveals complex social processes behind political changes.
Project description:Motivation and methodExisting rational expectations models cannot satisfactorily explain why political budget manipulations systematically raise re-election chances and only occur in "specific contexts". This paper offers a theoretical explanation by including unsophisticated voters into an opportunistic political cycle model; unsophisticated voters are unable to take the optimal behaviour of other agents (fully) into account, but may, nonetheless, vaguely suspect government deception.ResultsFirst, rationally expected manipulations are, on average, fruitless in equilibrium. By including unsophisticated voters we can, however, corroborate empirically found electoral effects of political budget manipulations. Second, unsophisticated voters become anxious and suspicious in an intransparent or uncertain world, but the government tries to "outperform" their scepticism by increasing budget manipulations in order to appear more competent and, ultimately, increase re-election chances. It is, therefore, not surprising that political budget cycles are observed in countries suffering from intransparencies such as developing countries or new democracies. Third and in addition, the model presented here predicts that political opportunism produces, unintentionally, a countercyclical policy effect in election years, thereby, for instance, alleviating the typical problem of policy procyclicality in developing countries.Additional contributionThe paper also offers a theoretical explanation for political distortions found in forecasts by US states. Based on overly optimistic revenue forecasts the incumbent state government can conduct expansionary fiscal policies in order to appear more competent prior to an upcoming election. Since the resulting deficit can only be observed afterwards, the government can effectively circumvent a constitutional balanced budget constraint. As a result, there are political forecast and budget cycles in the state. More generally, however, these findings may also apply to European countries where balanced budget constraints are or will be in place (for instance the debt brakes in Switzerland and Germany); similarly, they apply to the supra-national European Fiscal Compact of the European Union.
Project description:Assuring election integrity is essential for the legitimacy of elected representative democratic government. Until recently, other than in-person election observation, there have been few quantitative methods for determining the integrity of a democratic election. Here we present a machine learning methodology for identifying polling places at risk of election fraud and estimating the extent of potential electoral manipulation, using synthetic training data. We apply this methodology to mesa-level data from Argentina's 2015 national elections.
Project description:Research on glass cliff political candidacies shows that compared to men, women are more likely to run for office in districts where they are likely to lose. We examined if party differences in whether female candidates face these worse conditions in the United States could account for persistent and growing party and state variation in women's representation. Using election data from 2011 to 2016, we compared Republican versus Democratic candidacies at the state legislative level. We found that women in both parties faced glass cliffs in House races, but not in the Senate. For Republican women, glass cliff conditions accounted for worse election outcomes, but Democratic women were more likely to win when these conditions were considered. Variation in party by state measures of glass cliff effects were also found to explain state variation in women's office holding. We found that for Democrats, more women win when more women run, but for Republicans, more women win only when the seats they face are more winnable. These results point to the role of polarized traditional versus progressive political ideologies in structuring the motives which underlie glass cliff conditions for women in politics, suggesting that practical solutions be tailored to party. To overcome the growing gap in women's representation, current efforts to increase the quantity of women running would be complemented by a focus on improving the quality of contests they face, with Republican women most likely to benefit. Further research attending to the multiple sources of variation which impact gendered election outcomes can inform more targeted solutions for advancing equality. Online slides for instructors who want to use this article for teaching are available on PWQ's website at http://journals.sagepub.com/doi/suppl/10.1177/0361684321992046.
Project description:Protein domains are conspicuous structural units in globular proteins, and their identification has been a topic of intense biochemical interest dating back to the earliest crystal structures. Numerous disparate domain identification algorithms have been proposed, all involving some combination of visual intuition and/or structure-based decomposition. Instead, we present a rigorous, thermodynamically-based approach that redefines domains as cooperative chain segments. In greater detail, most small proteins fold with high cooperativity, meaning that the equilibrium population is dominated by completely folded and completely unfolded molecules, with a negligible subpopulation of partially folded intermediates. Here, we redefine structural domains in thermodynamic terms as cooperative folding units, based on m-values, which measure the cooperativity of a protein or its substructures. In our analysis, a domain is equated to a contiguous segment of the folded protein whose m-value is largely unaffected when that segment is excised from its parent structure. Defined in this way, a domain is a self-contained cooperative unit; i.e., its cooperativity depends primarily upon intrasegment interactions, not intersegment interactions. Implementing this concept computationally, the domains in a large representative set of proteins were identified; all exhibit consistency with experimental findings. Specifically, our domain divisions correspond to the experimentally determined equilibrium folding intermediates in a set of nine proteins. The approach was also proofed against a representative set of 71 additional proteins, again with confirmatory results. Our reframed interpretation of a protein domain transforms an indeterminate structural phenomenon into a quantifiable molecular property grounded in solution thermodynamics.
Project description:A sustainable global community requires the successful integration of environment and engineering. In the public and private sectors, designing cyclical ("closed loop") resource networks increasingly appears as a strategy employed to improve resource efficiency and reduce environmental impacts. Patterning industrial networks on ecological ones has been shown to provide significant improvements at multiple levels. Here, we apply the biological metric cyclicity to 28 familiar thermodynamic power cycles of increasing complexity. These cycles, composed of turbines and the like, are scientifically very different from natural ecosystems. Despite this difference, the application results in a positive correlation between the maximum thermal efficiency and the cyclic structure of the cycles. The immediate impact of these findings results in a simple method for comparing cycles to one another, higher cyclicity values pointing to those cycles which have the potential for a higher maximum thermal efficiency. Such a strong correlation has the promise of impacting both natural ecology and engineering thermodynamics and provides a clear motivation to look for more fundamental scientific connections between natural and engineered systems.
Project description:The present data set contains self-report data of German individuals participating in a longitudinal data assessment via online surveys conducted in the year preceeding the general elections in Germany. Data of N = 122 individuals are included in the data set. Those individuals participated in an initial, extensive survey between November 2020 and February 2021 (T1) as well as in a final survey after the general German elections, thus, between the end of September 2021 and October 2021 (T3). Of those individuals, n = 93 additionally participated in an intermediate survey in between the previously mentioned ones between the end of May and the end of June 2021 (T2). Next to the assessment of sociodemographic variables, information on (political) news consumption, such as the frequency of being confronted with counter-attitudinal news, and on political attitudes, for example via current voting intentions for one of the major German parties, were assessed in the initial survey (T1). In the intermediate survey (T2), participants provided information on recent political news consumption habits including the frequency of being confronted with counter-attitudinal news, current voting intentions for one of the major German parties, as well as on extraordinary events that happened recently and impacted their voting intentions. In the final survey (T3), sociodemographic variables and actual voting decisions in the general German elections in 2021 were assessed. Moreover, variables on recent political news consumption habits, including the frequency of being confronted with counter-attitudinal news, and extraordinary events that happened recently and impacted voting decisions were assessed. Finally, a detailed self-report questionnaire retrospectively assessing political news consumption for the time between participation in the initial survey (T1) and the final survey (T3) was completed by participants. Not only did this questionnaire assess which online and offline news channels (e.g., TV, print, news websites) participants used. Besides, the questionnaire included items on how many outlets per channel were used and the frequency of being confronted with counter-attitudinal news within each channel. This data set is provided alongside the present article to be used for further investigations of the stability of voting intentions, thus, political attitudes. Moreover, a content analysis of the open responses on which extraordinary events happened and impacted voting intentions/decisions can provide further knowledge on factors influencing voting intentions and their variability versus stability.
Project description:How much free energy is irreversibly lost during a thermodynamic process? For deterministic protocols, lower bounds on energy dissipation arise from the thermodynamic friction associated with pushing a system out of equilibrium in finite time. Recent work has also bounded the cost of precisely moving a single degree of freedom. Using stochastic thermodynamics, we compute the total energy cost of an autonomously controlled system by considering both thermodynamic friction and the entropic cost of precisely directing a single control parameter. Our result suggests a challenge to the usual understanding of the adiabatic limit: Here, even infinitely slow protocols are energetically irreversible.