Hasil untuk "Political Science"

B. Peters

H. Eckstein, F. Greenstein, N. Polsby

S. Huntington

This now-classic examination of the development of viable political institutions in emerging nations is a major and enduring contribution to modern political analysis. In a new Foreword, Francis Fukuyama assesses Huntington's achievement, examining the context of the book's original publication as well as its lasting importance. "This pioneering volume, examining as it does the relation between development and stability, is an interesting and exciting addition to the literature."--American Political Science Review "'Must' reading for all those interested in comparative politics or in the study of development."--Dankwart A. Rustow, Journal of International Affairs

S. Kreps, D. Kriner

Communications engaging uncertainty in COVID-19 research affect public trust in science and support for science-based policy. While scientific uncertainty always invites the risk of politicization and raises questions of how to communicate about science, this risk is magnified for COVID-19. The limited data and accelerated research timelines mean that some prominent models or findings inevitably will be overturned or retracted. In this research, we examine the attitudes of more than 6000 Americans across five different survey experiments to understand how the cue giver and cue given about scientific uncertainty regarding COVID-19 affect public trust in science and support for science-based policy. Criticism from Democratic political elites undermines trust more than criticism from Republicans. Emphasizing uncertainty in projections can erode public trust in some contexts. Downplaying uncertainty can raise support in the short term, but reversals in projections may temper these effects or even reduce scientific trust. Careful science communication is critical to maintaining public support for science-based policies as the scientific consensus shifts over time.

Zoltan Bartha

This paper investigates the extent of political rent seeking in Hungary in the 2010s. Political capitalism--where powerful private interests influence public policy for private gain--creates opportunities for rent seeking that vary across sectors. The analysis is based on a theoretical model assuming rent seeking occurs in a three-stage process: changes in economic institutions granting regulatory privileges, which are enhanced by political-business networks; this leads to scarcities, and increased market power in certain markets; which then generates rents. To quantify this, the study evaluates Hungarian political capitalism by examining the impact of political decisions on firms' rents, analysing the profit trends of the 1,000 largest Hungarian firms (selected annually by net sales) and comparing their mean profit share (earnings before tax) across two periods: 2008-2012 and 2019-2023. A significant increase in a sector's mean profit share was assumed to indicate increased rent seeking. Using Welch's two-sample t-tests, three sectors were identified as potentially experiencing increased rent seeking: agriculture, construction, and financial and insurance activities. Quantitative findings include a 320% increase in mean agricultural profit share (70% in mean ROA), a more than fivefold increase in construction mean profit share (mean ROA from 3.3% to 10.1%), and a more than 6.5 times increase in financial sector mean profit share. Furthermore, a similar Czech analysis showed no significant increases in any sector's profit share, suggesting that the detected rises in Hungarian sectors are linked to domestic activities rather than external factors, which strengthens the findings.

Peter Kyungtae Park

Shift-share designs are gaining popularity in political science. This article introduces what shift-share designs are, reviews their application in the literature, synthesizes recent methodological developments, and discusses their potential utility in the field. Although shift-share designs have a long historical use in economics, their causal properties only recently began to be understood. Articles in political science tend to be aware of these developments, but do not fully discuss and test identifying assumptions and sometimes apply the methods incorrectly. Most articles rely on the share exogeneity framework, suggesting that the shifter exogeneity framework is underutilized despite its comparable prevalence in economics. I illustrate shifter exogeneity framework and develop auxiliary theoretical results that are potentially useful in applying the framework in political science settings.

Michał Ledwosiński

Artykuł podejmuje problematykę kompetencji miękkich w kontekście przekładoznawstwa oraz ich znaczenia w pracy tłumacza, zwłaszcza w środowiskach zawodowych, kształtowanych przez nowe technologie. Analizie poddano relacje między kompetencjami twardymi a miękkimi oraz wpływ kompetencji interpersonalnych na efektywność pracy tłumaczeniowej w warunkach współczesnej współpracy zespołowej. Celem tekstu jest ukazanie, że rozwój technologiczny nie redukuje znaczenia umiejętności społecznych, lecz wręcz potęguje potrzebę ich obecności w zawodzie tłumacza.

Yueqing Liang, Liangwei Yang, Chen Wang et al.

Large Language Models (LLMs) have achieved significant advances in natural language processing, yet their potential for high-stake political decision-making remains largely unexplored. This paper addresses the gap by focusing on the application of LLMs to the United Nations (UN) decision-making process, where the stakes are particularly high and political decisions can have far-reaching consequences. We introduce a novel dataset comprising publicly available UN Security Council (UNSC) records from 1994 to 2024, including draft resolutions, voting records, and diplomatic speeches. Using this dataset, we propose the United Nations Benchmark (UNBench), the first comprehensive benchmark designed to evaluate LLMs across four interconnected political science tasks: co-penholder judgment, representative voting simulation, draft adoption prediction, and representative statement generation. These tasks span the three stages of the UN decision-making process--drafting, voting, and discussing--and aim to assess LLMs' ability to understand and simulate political dynamics. Our experimental analysis demonstrates the potential and challenges of applying LLMs in this domain, providing insights into their strengths and limitations in political science. This work contributes to the growing intersection of AI and political science, opening new avenues for research and practical applications in global governance. The UNBench Repository can be accessed at: https://github.com/yueqingliang1/UNBench.

Mauve Science Collaboration, Marcel Agueros, Don Dixon et al.

Mauve is a low-cost small satellite developed and operated by Blue Skies Space Ltd. The payload features a 13 cm telescope connected with a fibre that feeds into a UV-Vis spectrometer. The detector covers the 200-700 nm range in a single shot, obtaining low resolution spectra at R~20-65. Mauve has launched on 28th November 2025, reaching a 510 km Low-Earth Sun-synchronous orbit. The satellite will enable UV and visible observations of a variety of stellar objects in our Galaxy, filling the gaps in the ultraviolet space-based data. The researchers that have already joined the mission have defined the science themes, observational strategy and targets that Mauve will observe in the first year of operations. To date 10 science themes have been developed by the Mauve science collaboration for year 1, with observational strategies that include both long duration monitoring and short cadence snapshots. Here, we describe these themes and the science that Mauve will undertake in its first year of operations.

Carolina Torreblanca, William Dinneen, Guy Grossman et al.

How has the credibility revolution shaped political science? We address this question by classifying 91,632 articles published between 2003 and 2023 across 156 political science journals using large language models, focusing on research design, credibility-enhancing practices, and citation patterns. We find that design-based studies -- those leveraging plausibly exogenous variation to justify causal claims -- have become increasingly common and receive a citation premium. In contrast, model-based approaches that rely on strong modeling assumptions have declined. Yet the rise of design-based work is uneven: it is concentrated in top journals and among authors at highly ranked institutions, and it is driven primarily by the growth of survey experiments. Other credibility-enhancing practices that help reduce false positives and false negatives, such as placebo tests and power calculations, remain rare. Taken together, our findings point to substantial but selective change, more consistent with a partial reform than a revolution.

Roderik Rekker

People have a tendency to disregard information that contradicts their partisan or ideological identity. This inclination can become especially striking when citizens reject notions that scientists would consider “facts” in the light of overwhelming scientific evidence and consensus. The resulting polarization over science has reached alarming levels in recent years. This theoretical review conceptualizes political polarization over science and argues that it is driven by two interrelated processes. Through psychological science rejection, people can implicitly disregard scientific facts that are inconsistent with their political identity. Alternatively, citizens can engage in ideological science rejection by adhering to a political ideology that explicitly contests science. This contestation can in turn be subdivided into four levels of generalization: An ideology can dispute either specific scientific claims, distinct research fields, science in general, or the entire political system and elite. By proposing this interdisciplinary framework, this article aims to integrate insights from various disciplines.

Dongyun Han, Abdullah-Al-Raihan Nayeem, Jason Windett et al.

Politics is the set of activities related to strategic decision-making in groups. Political scientists study the strategic interactions between states, institutions, politicians, and citizens; they seek to understand the causes and consequences of those decisions and interactions. While some decisions might alleviate social problems, others might lead to disasters such as war and conflict. Data visualization approaches have the potential to assist political scientists in their studies by providing visual contexts. However, political researchers' perspectives on data visualization are unclear. This paper examines political scientists' perspectives on visualization and how they apply data visualization in their research. We discovered a growing trend in the use of graphs in political science journals. However, we also found a knowledge gap between the political science and visualization domains, such as effective visualization techniques for tasks and the use of color studied by visualization researchers. To reduce this gap, we survey visualization techniques applicable to the political scientists' research and report the visual analytics systems implemented for and evaluated by political scientists. At the end of this paper, we present an outline of future opportunities, including research topics and methodologies, for multidisciplinary research in political science and data analytics. Through this paper, we expect visualization researchers to get a better grasp of the political science domain, as well as broaden the possibility of future visualization approaches from a multidisciplinary perspective.

Kai-Robin Lange, Jonas Rieger, Niklas Benner et al.

From a monarchy to a democracy, to a dictatorship and back to a democracy -- the German political landscape has been constantly changing ever since the first German national state was formed in 1871. After World War II, the Federal Republic of Germany was formed in 1949. Since then every plenary session of the German Bundestag was logged and even has been digitized over the course of the last few years. We analyze these texts using a time series variant of the topic model LDA to investigate which events had a lasting effect on the political discourse and how the political topics changed over time. This allows us to detect changes in word frequency (and thus key discussion points) in political discourse.

Yu Wang

Interest is increasing among political scientists in leveraging the extensive information available in images. However, the challenge of interpreting these images lies in the need for specialized knowledge in computer vision and access to specialized hardware. As a result, image analysis has been limited to a relatively small group within the political science community. This landscape could potentially change thanks to the rise of large language models (LLMs). This paper aims to raise awareness of the feasibility of using Gemini for image content analysis. A retrospective analysis was conducted on a corpus of 688 images. Content reports were elicited from Gemini for each image and then manually evaluated by the authors. We find that Gemini is highly accurate in performing object detection, which is arguably the most common and fundamental task in image analysis for political scientists. Equally important, we show that it is easy to implement as the entire command consists of a single prompt in natural language; it is fast to run and should meet the time budget of most researchers; and it is free to use and does not require any specialized hardware. In addition, we illustrate how political scientists can leverage Gemini for other image understanding tasks, including face identification, sentiment analysis, and caption generation. Our findings suggest that Gemini and other similar LLMs have the potential to drastically stimulate and accelerate image research in political science and social sciences more broadly.

Éltető Andrea, Szemlér Tamás

Hungary had been one of the frontrunners in the political and economic transition process in Central and Eastern Europe in the 1990s, and in 2004 it joined the European Union. Since 2010, Hungary has gradually become an autocratic regime, a process that has been facilitated by the political benefits of EU integration and money transfers. While the support of the Hungarian people for EU membership has remained high, tensions have increased between the Hungarian government and EU institutions. This article evaluates how the external shock of Russia’s war against Ukraine has shaken Hungary’s so far developed authoritarian equilibrium within the EU. The authors show how embedded the Hungarian autocracy has become and argue that although there have been some effects to the pillars of the authoritarian equilibrium, it has remained stable, and most probably will continue to do so, as long as the illiberal regime stays in power.

Kmar Bendana, Choukri Hmed, Antoine Perrier et al.

Petar Ivanov, Ivan Koychev, Momchil Hardalov et al.

Developing tools to automatically detect check-worthy claims in political debates and speeches can greatly help moderators of debates, journalists, and fact-checkers. While previous work on this problem has focused exclusively on the text modality, here we explore the utility of the audio modality as an additional input. We create a new multimodal dataset (text and audio in English) containing 48 hours of speech from past political debates in the USA. We then experimentally demonstrate that, in the case of multiple speakers, adding the audio modality yields sizable improvements over using the text modality alone; moreover, an audio-only model could outperform a text-only one for a single speaker. With the aim to enable future research, we make all our data and code publicly available at https://github.com/petar-iv/audio-checkworthiness-detection.

Dominik Bär, Francesco Pierri, Gianmarco De Francisci Morales et al.

Political advertising on social media has become a central element in election campaigns. However, granular information about political advertising on social media was previously unavailable, thus raising concerns regarding fairness, accountability, and transparency in the electoral process. In this paper, we analyze targeted political advertising on social media via a unique, large-scale dataset of over 80000 political ads from Meta during the 2021 German federal election, with more than 1.1 billion impressions. For each political ad, our dataset records granular information about targeting strategies, spending, and actual impressions. We then study (i) the prevalence of targeted ads across the political spectrum; (ii) the discrepancies between targeted and actual audiences due to algorithmic ad delivery; and (iii) which targeting strategies on social media attain a wide reach at low cost. We find that targeted ads are prevalent across the entire political spectrum. Moreover, there are considerable discrepancies between targeted and actual audiences, and systematic differences in the reach of political ads (in impressions-per-EUR) among parties, where the algorithm favors ads from populists over others.

Gabriel Cohn

Resumo O artigo destaca a dificuldade de se definir “fascismo”. Mesmo assim, nota como foram elaboradas concepções genéricas de fascismo, a partir das quais, variados casos podem ser confrontados. Chama igualmente a atenção para a existência de uma dimensão institucional e uma dimensão ideológica no fascismo; a primeira tendo sido enfrentada, a segunda negligenciada. Ao se confrontar o Brasil com “fascismo clássico”, indica que aqui não teríamos a criação de algo novo, mas a explicitação de traços profundamente arraigados de nossa sociedade. Nesse sentido, é sugerido que entre nós, mais do que falar propriamente em fascismo, se poderia apontar para a existência de algo como um “fascismo latente”, sempre capaz de vir à tona e, portanto, especialmente preocupante.

Girum Tareke Zewude, Sisay Demissew Beyene, Belayneh Taye et al.

The outbreak of the COVID-19 pandemic has impacted many professions with short-, medium-, and long-term consequences. Hence, this study examined the mediating role of sense of coherence (SOC) and resilience in the relation to COVID-19 stress and teachers’ well-being (TWB). It recruited 836 teachers from Ethiopia’s higher-education institutions, of which 630 (75.4%) were men and 206 (24.6%) were women, with a mean age of 32.81 years and a standard deviation of 6.42. Findings showed that COVID-19 stress negatively predicted SOC, resilience, and TWB and that SOC and resilience positively predicted TWB. It was concluded that SOC and resilience, both together and separately, mediated the relation between COVID-19 stress and TWB. These results were discussed alongside relevant literature, and the study is found to be valuable for practitioners and researchers who seek to improve well-being using SOC and resilience as resources across teaching professions.