Hasil untuk "Political Science"

Vincent Hue, Bilal Benmahi, Mathieu Barthelemy et al.

Pollux is a candidate European instrument contribution to the Habitable Worlds Observatory (HWO), designed to advance our understanding of the formation and evolution of cosmic structures in the universe, and specifically search signs of life on extrasolar planets. This high-resolution spectrograph (R\,$>$\,40,000) with polarimetric capabilities offers nearly continuous and simultaneous coverage from the FUV ($\sim$100\,nm) to the NIR ($\sim$1.9\,$\micron$), making it a versatile tool for a wide range of scientific investigations from solar system studies to cosmology. Several Solar System ocean worlds have been the focal point of the scientific community to understand the conditions of their internal saline oceans, as well as the possible emergence of life beyond Earth. The ocean world science case will leverage Pollux's UV spectropolarimetric capabilities to investigate surface reflectance and composition, characterize airglow emissions in the environments of giant-planet moons, as well as constrain the microphysical properties of atmospheric aerosols.

Jorge Francisco Aguirre-Sala, Jorge Francisco Aguirre-Sala

The primary objective was to build a model that complements the provisions of the recent European Union AI regulation, the National Institute of Standards and Technology (NIST) Artificial Intelligence Risk Management Framework—which operationalizes the US President’s Executive Order 14110—and the first international standard for the Artificial Intelligence Management Systems (ISO/IEC 42001:2023) of the International Standardization Organization (ISO). This objective was a priority because Responsibility Articles 28 and 57 of the recent European Union regulations have set a deadline of August 2025 and August 2026 for designating an authority responsible for evaluations and testing before artificial intelligence (AI) systems are put into service. The previous objective analyzes the above regulations and provisions from the perspective of AI governance (AIG). That is, the approach seeks to balance the empowerment of algorithms in public administration with the citizen aspiration of empowerment. The method analytically reviews the stages and actions of an AI system to infer the design and development of the action and responsibilities of the actors involved in the AIG process from end to end. The results show a general AIG model for public administration that uses Artificial Intelligence before, during, and after its complete life cycle. The conclusions demand a holistic vision that includes both social and technical infrastructure.

Clara Lachenmaier, Judith Sieker, Sina Zarrieß

Communication among humans relies on conversational grounding, allowing interlocutors to reach mutual understanding even when they do not have perfect knowledge and must resolve discrepancies in each other's beliefs. This paper investigates how large language models (LLMs) manage common ground in cases where they (don't) possess knowledge, focusing on facts in the political domain where the risk of misinformation and grounding failure is high. We examine the ability of LLMs to answer direct knowledge questions and loaded questions that presuppose misinformation. We evaluate whether loaded questions lead LLMs to engage in active grounding and correct false user beliefs, in connection to their level of knowledge and their political bias. Our findings highlight significant challenges in LLMs' ability to engage in grounding and reject false user beliefs, raising concerns about their role in mitigating misinformation in political discourse.

Liangze Ke

This paper examines a novel proxy for political polarization, initially proposed by Caliskan et al., which estimates intergroup distances using computer vision. Analyzing 1,400+ YouTube videos with advanced object detection, their study quantifies demographic and religious divides in Turkiye, a deeply polarized nation. Our findings reveal strong correlations between intergroup distances and electoral polarization, measured via entropy-based voting metrics weighted by religiosity and political inclination. Two key insights emerge: (1) Greater distances between religious and nonreligious individuals (NRP vs RP) heighten electoral entropy, underscoring sociocultural fragmentation. (2) Intragroup diversity among nonreligious individuals (NRP vs NRP) stabilizes polarization, aligning with Axelrod's cultural dissemination model. This research advances computational social science and economics by showing that physical distancing serves as a scalable proxy for polarization, complementing traditional economic indicators.

Shariar Kabir, Kevin Esterling, Yue Dong

Existing evaluations of political bias in large language models (LLMs) typically classify outputs as left- or right-leaning. We extend this perspective by examining how ideological tendencies vary across topics and how consistently models maintain their positions, a property we refer to as stability. To capture this dimension, we propose PReSS (Political Response Stability under Stress), a black-box framework that evaluates LLMs by jointly considering model and topic context, categorizing responses into four stance types: stable-left, unstable-left, stable-right, and unstable-right. Applying PReSS to 12 widely used LLMs across 19 political topics reveals substantial variation in stance stability; for instance, a model that is left-leaning overall can exhibit stable-right behavior on certain topics. This highlights the importance of topic-aware and fine-grained evaluation of political ideologies of LLMs. Moreover, stability has practical implications for controlled generation and model alignment: interventions such as debiasing or ideology reversal should explicitly account for stance stability. Our empirical analyses reveal that when models are prompted or fine-tuned to adopt the opposite ideology, unstable topic stances are more likely to change, whereas stable ones resist modification. Thus, treating stability as a moderating factor provides a principled foundation for understanding, evaluating, and guiding interventions in politically sensitive model behavior.

Amrit Poudel, Tim Weninger

Search engines play a crucial role in shaping public discourse by influencing how information is accessed and framed. While prior research has extensively examined various dimensions of search bias -- such as content prioritization, indexical bias, political polarization, and sources of bias -- an important question remains underexplored: how do search engines and ideologically-motivated user queries contribute to bias in search results. This study analyzes the outputs of major search engines using a dataset of political and social topics. The findings reveal that search engines not only prioritize content in ways that reflect underlying biases but also that ideologically-driven user queries exacerbate these biases, resulting in the amplification of specific narratives. Moreover, significant differences were observed across search engines in terms of the sources they prioritize. These results suggest that search engines may play a pivotal role in shaping public perceptions by reinforcing ideological divides, thereby contributing to the broader issue of information polarization.

Asta Valackiene, Jovita Giedraitiene

This study aims to explore the links between the efficiency of public sector e-services and sustainable competitive advantage. In line with the emerging approach, the instrumental case study design and the mixed research strategy were used as the most appropriate methodology to answer the general research question that was raised for this study. In this context, we present the positive experience that we have discovered via the Lithuanian case study. A unified model of evaluation of the e-services development system in the public sector was developed. The model explains the application of various e-services development systems methodologies and methods in the public sector and underpins the platform for the interaction of efficiency and sustainable competitive advantage processes. The model developed helps to make the assessment of e-services more effective and demonstrates a personalised outcome that can be applied by other public sector organisations. The paper discusses the efficiency trends in the development of e-services in the public sector in order to achieve Sustainable Development Goals, as well as distinguishes and highlights procedural steps that help to improve the development of e-services and sustainable competitive advantage.

Carlos Omar Soto-González, Cristhian Antonio Vega-Quezada, Sonia Sanabria-García et al.

En la actualidad, la liquidez y la rentabilidad constituyen un pilar fundamental para mejorar la eficiencia de las empresas. Al respecto, el objetivo de esta investigación es establecer los determinantes que influyen en la liquidez y rentabilidad de las Cooperativas de Ahorro y Crédito del Ecuador que pertenecen a los segmentos 1 y 2. La metodología a utilizar en el proceso de investigación se basa en el análisis de componentes principales y en una especificación estimada por el método del Modelo Autorregresivo de Rezagos Distribuidos Simple, utilizando los estados financieros de estas cooperativas del segmento 1 y 2, extraídos de la Superintendencia de Economía Popular y Solidaria desde 2015 hasta 2020, con un total de 408 observaciones. Los resultados demuestran que existen dos determinantes: el riesgo de crédito y el apalancamiento, los cuales son factores importantes que influyen directamente en la liquidez. Mientras, por el lado de la rentabilidad se muestra que existe la relación con las variables de capital físico, la tasa de financiamiento, el apalancamiento y el riesgo de crédito. Se concluye argumentando que los factores liquidez y rentabilidad son aspectos neurálgicos para el crecimiento de las cooperativas y para contribuir en la generación de una homeóstasis financiera.

Nicol Viljoen

This article focuses on che raised. fourth or Lydian scale degree of the scale in Chopin's mazurkas from the viewpoint of the stylised mazurka's fusion of folkloric elements and nineteenth-century tonal language. A brief exposition of the functions of the raised fourth and its integradon into the tonal structures of the mazurkas is given. An investigation of the raised fourth in three selected mazurkas· reveals a significant expansion of its role musi~al meaning, function and effect, As an authentic, modal, structural, motivic and form-generating device, it is in terms of integral co tonal elaboration, development, unification, colouration and contrast.

Tai-Quan Peng, Kaiqi Yang, Sanguk Lee et al.

As large language models (LLMs) become increasingly embedded in civic, educational, and political information environments, concerns about their potential political bias have grown. Prior research often evaluates such bias through simulated personas or predefined ideological typologies, which may introduce artificial framing effects or overlook how models behave in general use scenarios. This study adopts a persona-free, topic-specific approach to evaluate political behavior in LLMs, reflecting how users typically interact with these systems-without ideological role-play or conditioning. We introduce a two-dimensional framework: one axis captures partisan orientation on highly polarized topics (e.g., abortion, immigration), and the other assesses sociopolitical engagement on less polarized issues (e.g., climate change, foreign policy). Using survey-style prompts drawn from the ANES and Pew Research Center, we analyze responses from 43 LLMs developed in the U.S., Europe, China, and the Middle East. We propose an entropy-weighted bias score to quantify both the direction and consistency of partisan alignment, and identify four behavioral clusters through engagement profiles. Findings show most models lean center-left or left ideologically and vary in their nonpartisan engagement patterns. Model scale and openness are not strong predictors of behavior, suggesting that alignment strategy and institutional context play a more decisive role in shaping political expression.

Wyam WALIDI, Hafida EL AMRANI

This paper looks at the polyphonic analysis of Moroccan caricature in the context of the Covid-19 pandemic. It highlights the importance of the image as an information tool within an area of multiple communication. As a form of visual expression, caricature aims to convey information concisely and persuasively, while reflecting the perspective of its creator. The present study sets out to understand caricature by adopting a linguistic approach and focusing specifically on the analysis of linguistic polyphony in Moroccan caricatures related to the global health crisis. This approach adopts Ducrot's enunciative theory as an analytical framework. Based on Imad Sanouni's caricatures addressing this theme, the present analysis highlights the diversity of voices and perspectives within a caricatural image image, faithfully illustrating the crisis experienced by Moroccan society during the pandemic. Results show that these drawings faithfully reflect this epidemiological period through the means of iconographic and linguistic codes to create layers of meaning and discourse. By combining visual and linguistic elements, this study demonstrates that caricature could constitute a polyphonic means of visual communication, contributing

Giordano Paoletti, Lorenzo Dall'Amico, Kyriaki Kalimeri et al.

At the beginning of the COVID-19 pandemic, fears grew that making vaccination a political (instead of public health) issue may impact the efficacy of this life-saving intervention, spurring the spread of vaccine-hesitant content. In this study, we examine whether there is a relationship between the political interest of social media users and their exposure to vaccine-hesitant content on Twitter. We focus on 17 European countries using a multilingual, longitudinal dataset of tweets spanning the period before COVID, up to the vaccine roll-out. We find that, in most countries, users' endorsement of vaccine-hesitant content is the highest in the early months of the pandemic, around the time of greatest scientific uncertainty. Further, users who follow politicians from right-wing parties, and those associated with authoritarian or anti-EU stances are more likely to endorse vaccine-hesitant content, whereas those following left-wing politicians, more pro-EU or liberal parties, are less likely. Somewhat surprisingly, politicians did not play an outsized role in the vaccine debates of their countries, receiving a similar number of retweets as other similarly popular users. This systematic, multi-country, longitudinal investigation of the connection of politics with vaccine hesitancy has important implications for public health policy and communication.

Beomjune Kim, Eunsun Lee, Dongbin Na

Many users reading online articles in various magazines may suffer considerable difficulty in distinguishing the implicit intents in texts. In this work, we focus on automatically recognizing the political intents of a given online newspaper by understanding the context of the text. To solve this task, we present a novel Korean text classification dataset that contains various articles. We also provide deep-learning-based text classification baseline models trained on the proposed dataset. Our dataset contains 12,000 news articles that may contain political intentions, from the politics section of six of the most representative newspaper organizations in South Korea. All the text samples are labeled simultaneously in two aspects (1) the level of political orientation and (2) the level of pro-government. To the best of our knowledge, our paper is the most large-scale Korean news dataset that contains long text and addresses multi-task classification problems. We also train recent state-of-the-art (SOTA) language models that are based on transformer architectures and demonstrate that the trained models show decent text classification performance. All the codes, datasets, and trained models are available at https://github.com/Kdavid2355/KoPolitic-Benchmark-Dataset.

Daria Pilewska

W niniejszym artykule zaprezentowane zostały peregrynacje w głąb epok, do miejsc, gdzie kształtowały się idee praw zwierząt, obecne w świadomości współczesnych Europejczyków. Pomimo że postrzeganie stworzeń innych niż ludzie jest wyraźnym problemem współczesnego społeczeństwa w Europie, ugruntowany przez wieki antropocentryzm utrudnia przyjęcie podmiotowości zwierząt na płaszczyźnie politycznej, prawnej, a nawet obyczajowej. Artykuł stanowi analizę kształtowania się rzeczywistości społecznej i politycznej, w kontekście percepcji zwierząt, będącej odbiciem charakterystycznych dla poszczególnych okresów w dziejach postaw i idei. Celem poniższej refleksji jest wskazanie przyczyn utrudniających, a często i uniemożliwiających wprowadzenie zmian w polityce ochrony zwierząt zarówno w Europie, jak i w Polsce. Z racji tego, że artykuł ma charakter eseistyczno-teoretyczny, zrezygnowano z formułowania hipotez badawczych.

Manoel Júnior, Philipe Melo, Daniel Kansaon et al.

Instant messaging platforms such as Telegram became one of the main means of communication used by people all over the world. Most of them are home of several groups and channels that connect thousands of people focused on political topics. However, they have suffered with misinformation campaigns with a direct impact on electoral processes around the world. While some platforms, such as WhatsApp, took restrictive policies and measures to attenuate the issues arising from the abuse of their systems, others have emerged as alternatives, presenting little or no restrictions on content moderation or actions in combating misinformation. Telegram is one of those systems, which has been attracting more users and gaining popularity. In this work, we present the "Telegram Monitor", a web-based system that monitors the political debate in this environment and enables the analysis of the most shared content in multiple channels and public groups. Our system aims to allow journalists, researchers, and fact-checking agencies to identify trending conspiracy theories, misinformation campaigns, or simply to monitor the political debate in this space along the 2022 Brazilian elections. We hope our system can assist the combat of misinformation spreading through Telegram in Brazil.

Julene Siddique, Peter Joseph

Social theories and humanitarian movements, despite their good intentions, have had limited effectiveness. This paper introduces Socio-Systemic science as a conceptual and implementation framework designed for effective high impact systemic action. The science of Socio-Systemic impact is led by the Social Architect who understands how to consciously catalyse key drivers of systemic change. The rise of a systems-based worldview forms the basis of a new way of understanding modern problems, inferring the kind of thinking and leadership required today. The Social Architect is a new entity in this development, working to apply grounded sociological science and understandings of natural systems to improving the human condition. Where traditional activism falls short through structural illiteracy and continually stumbles in engaging mere symptoms of world issues, the Social Architects act as the compassionate analysts addressing the systemic causes of world issues. We can no longer turn a blind eye to structural violence and systemic failure. Inside the dark heart of structural violence are the keys of societal re-architecting that are in fact our only hope out of it. The first part of this paper outlines the science of Socio-Systemic impact. The second part explains how to put the science into practice; reviews current implementation methods being deployed by leading Social Architects; outlines the key skills and roles of the Social Architect working individually as well as strategies for integral systemic action, and, lastly, suggests further action strategies and prospects for the future.

Rob Richie, Benjamin Oestericher, Deb Otis et al.

Grounded in experience in 2020, both major political parties have reasons to expand use of ranked choice voting (RCV) in their 2024 presidential primaries. RCV may offer a ‘win-win’ solution benefiting both the parties and their voters. RCV would build on both the pre-1968 American tradition of parties determining a coalitional presidential nominee through multiple ballots at party conventions and the modern practice of allowing voters to effectively choose their nominees in primaries. Increasingly used by parties around the world in picking their leaders, RCV may allow voters to crowd-source a coalitional nominee. Most published research about RCV focuses on state and local elections. In contrast, this article analyzes the impact on voters, candidates, and parties from five state Democratic parties using RCV in party-run presidential nomination contests in 2020. First, it uses polls and results to examine how more widespread use of RCV might have affected the trajectory of contests for the 2016 Republican nomination. Second, it contrasts how more than three million voters in the 2020 Democratic presidential primaries backed withdrawn candidates with the low rate of such wasted votes for withdrawn candidates in the states with RCV ballots. Finally, it concludes with an examination of how RCV might best interact with the parties’ current rules and potential changes to those rules.

Guilhem Cassan, Milan Van Steenvoort

The difference in COVID 19 death rates across political regimes has caught a lot of attention. The "efficient autocracy" view suggests that autocracies may be more efficient at putting in place policies that contain COVID 19 spread. On the other hand, the "biasing autocracy" view underlines that autocracies may be under reporting their COVID 19 data. We use fixed effect panel regression methods to discriminate between the two sides of the debate. Our results show that a third view may in fact be prevailing: once pre-determined characteristics of countries are accounted for, COVID 19 death rates equalize across political regimes. The difference in death rate across political regime seems therefore to be primarily due to omitted variable bias.

Teguh Yuwono, Laila Kholid Alfirdaus, Dzunuwanus Ghulam Manar

Tidak ada yang meragukan bahwa IT (Information and Technology) adalah kunci dalam menyambut perubahan 4.0 yang dipandang telah mendisrupsi banyak hal. Namun demikian, tidak banyak unit-unit pemerintahan yang secara cepat beradaptasi dengan situasi baru. Di tengah respon yang cukup kalang-kabut oleh pemerintah, baik di tingkat pusat maupun daerah, Banyuwangi relatif mampu melakukan penyesuaian diri dengan perubahan-perubahan baru yang berlandaskan Internet-of-Thing (IoT). Tentu saja, Banyuwangi tidak sedang menuju untuk menjadi seperti Silicon Valley, Amerika Serikat, yang telah lama dikenal sebagai episentrum bisnis-bisnis IT global. Banyuwangi masih sebatas gesit dalam memanfaatkan keterbukaan akses dan informasi untuk masuk ke dalam alur bisnis berbasis IT yang semakin ekspansif. Dampak dari kecepatan penyesuaian diri tersebut telah berhasil mengubah banyak hal menjadi lebih baik di masyarakat, baik secara ekonomi, pelayanan publik, maupun pendidikan. Hasil penelitian penulisselama tahun 2019 menunjukkan bahwa inovasi IT oleh Pemerintah Kabupaten Banyuwangi menjadi jantung bagi perubahan banyak aspek kehidupan di sana. Inovasi ini kemudian merangsang lahirnya inovasi baru di banyak hal lainnya

Sedarmayanti Sedarmayanti

Sejak munculnya iklim yang lebih demokratis dalam pemerintahan, kinerja instansi pemerintah semakin menjadi sorotan, dan masyarakat mulai banyak menuntut nilai yang diperoleh atas pelayanan yang diberikan intansi pemerintah. Tuntutan tersebut, diutarakan karena masyarakat masih merasa belum puas atas kualitas pelayanan yang diberikan oleh instansi pemerintah. Sampai saat ini, pengukuran kinerja instansi pemerintah dalam melaksanakan tugasnya belum dilakukan secara obyektif, hal tersebut disebabkan karena belum dilaksanakannya sistem pengukuran kinerja yang berisi keberhasilan dan kegagalan instansi pemerintah.