Hasil untuk "Political Science"

P. Hall, Rosemary C R Taylor

E. Ostrom

Extensive empirical evidence and theoretical developments in multiple disciplines stimulate a need to expand the range of rational choice models to be used as a foundation for the study of social dilemmas and collective action. After an introduction to the problem of overcoming social dilemmas through collective action, the remainder of this article is divided into six sections. The first briefly reviews the theoretical predictions of currently accepted rational choice theory related to social dilemmas. The second section summarizes the challenges to the sole reliance on a complete model of rationality presented by extensive experimental research. In the third section, I discuss two major empirical findings that begin to show how individuals achieve results that are “better than rational” by building conditions where reciprocity, reputation, and trust can help to overcome the strong temptations of short-run self-interest. The fourth section raises the possibility of developing second-generation models of rationality, the fifth section develops an initial theoretical scenario, and the final section concludes by examining the implications of placing reciprocity, reputation, and trust at the core of an empirically tested, behavioral theory of collective action.

Steven R. Brown

Gary King, James Honaker, Anne Joseph O'Connell et al.

Michelle L. Dion, J. Sumner, S. Mitchell

Accumulated evidence identifies discernible gender gaps across many dimensions of professional academic careers including salaries, publication rates, journal placement, career progress, and academic service. Recent work in political science also reveals gender gaps in citations, with articles written by men citing work by other male scholars more often than work by female scholars. This study estimates the gender gap in citations across political science subfields and across methodological subfields within political science, sociology, and economics. The research design captures variance across research areas in terms of the underlying distribution of female scholars. We expect that subfields within political science and social science disciplines with more women will have smaller gender citation gaps, a reduction of the “Matthew effect” where men’s research is viewed as the most central and important in a field. However, gender citation gaps may persist if a “Matilda effect” occurs whereby women’s research is viewed as less important or their ideas are attributed to male scholars, even as a field becomes more diverse. Analysing all articles published from 2007–2016 in several journals, we find that female scholars are significantly more likely than mixed gender or male author teams to cite research by their female peers, but that these citation rates vary depending on the overall distribution of women in their field. More gender diverse subfields and disciplines produce smaller gender citation gaps, consistent with a reduction in the “Matthew effect”. However, we also observe undercitation of work by women, even in journals that publish mostly female authors. While improvements in gender diversity in academia increase the visibility and impact of scholarly work by women, implicit biases in citation practices in the social sciences persist.

Joe Soss, Vesla M. Weaver

J. Wilkerson, Andreu Casas

Joanna Wyszkowska-Kuna

The aim of this article is to assess the competitiveness and specialisation of Polish knowledge-intensive business services (KIBS) export during the years 2004–2022. The product mapping method is used, which is based on the values of two indicators, i.e.: the normalised revealed comparative advantage index (NRCA) and the trade balance index (TBI). The study contributes to the academic literature by: (1) identifying the leading exported KIBS as well as KIBS with the potential to gain comparative advantage in Polish exports; (2) examining export competitiveness and specialisation in very narrow KIBS categories for the entire period of Poland's participation in European Single Market; (3) comparing the competitiveness and export specialisation of the KIBS sector in Poland in the EU and non-EU markets. The empirical results demonstrate that some of the KIBS industries in Poland have improved their competitiveness during the period of EU membership, but rather in exports outside the EU than to the EU. This may be due to strong competition in EU market and the fact that distance does not play a significant role in trade in services, especially in case of KIBS delivered online (e.g. computer services). Poland has developed a regional specialisation in the export of accountancy services, which is proved by the highest values of both indicators for this category, compared to other KIBS categories in Poland and compared to other EU countries. On the other hand, computer services appeared to be the leading exported product from the KIBS sector, but only outside the EU. Unfortunately, despite the upward trends, the importance of the leading exported KIBS in Polish exports is still small, especially in EU market. Therefore, it is necessary to take further actions aimed at strengthening the competitiveness of the KIBS sector in Poland, and the support for investments in human capital, digital transformation and R&D is crucial.

Lisa Dellmuth, Maria-Therese Gustafsson, Suanne Mistel Segovia-Tzompa

Abstract There is a lively debate about the legitimacy of the international climate regime, as represented by the United Nations Framework Convention on Climate Change, and the quality of non-state actor participation in the regime. This commentary examines perceptions of involved non-state actors from 2021–2022 regarding their participation and regime legitimacy. The findings reveal no legitimacy crisis for the adaptation and mitigation regimes, but the surveyed NSAs are divided in their legitimacy beliefs. NSAs also express significant disappointment about their opportunities for participation.

Bhal Chandra Joshi, Aris Karastergiou, Marta Burgay et al.

The large instantaneous sensitivity, a wide frequency coverage and flexible observation modes with large number of beams in the sky are the main features of the SKA observatory's two telescopes, the SKA-Low and the SKA-Mid, which are located on two different continents. Owing to these capabilities, the SKAO telescopes are going to be a game-changer for radio astronomy in general and pulsar astronomy in particular. The eleven articles in this special issue on pulsar science with the SKA Observatory describe its impact on different areas of pulsar science. In this lead article, a brief description of the two telescopes highlighting the relevant features for pulsar science is presented followed by an overview of each accompanying article, exploring the inter-relationship between different pulsar science use cases.

David Rozado

Political biases in Large Language Model (LLM)-based artificial intelligence (AI) systems, such as OpenAI's ChatGPT or Google's Gemini, have been previously reported. While several prior studies have attempted to quantify these biases using political orientation tests, such approaches are limited by potential tests' calibration biases and constrained response formats that do not reflect real-world human-AI interactions. This study employs a multi-method approach to assess political bias in leading AI systems, integrating four complementary methodologies: (1) linguistic comparison of AI-generated text with the language used by Republican and Democratic U.S. Congress members, (2) analysis of political viewpoints embedded in AI-generated policy recommendations, (3) sentiment analysis of AI-generated text toward politically affiliated public figures, and (4) standardized political orientation testing. Results indicate a consistent left-leaning bias across most contemporary AI systems, with arguably varying degrees of intensity. However, this bias is not an inherent feature of LLMs; prior research demonstrates that fine-tuning with politically skewed data can realign these models across the ideological spectrum. The presence of systematic political bias in AI systems poses risks, including reduced viewpoint diversity, increased societal polarization, and the potential for public mistrust in AI technologies. To mitigate these risks, AI systems should be designed to prioritize factual accuracy while maintaining neutrality on most lawful normative issues. Furthermore, independent monitoring platforms are necessary to ensure transparency, accountability, and responsible AI development.

Waseq Billah

Social media broadly refers to digital platforms and applications that simulate social interactions online. This study investigates the impact of social media platforms and their algorithms on political interest among users. As social media usage continues to rise, platforms like Facebook and X (formerly Twitter) play increasingly pivotal roles in shaping political discourse. By employing statistical analyses on data collected from over 3,300 participants, this research identifies significant differences in how various social media platforms influence political interest. Findings reveal that moderate Facebook users demonstrate decreased political engagement, whereas even minimal engagement with X significantly boosts political interest. The study further identifies demographic variations, noting that males, older individuals, Black or African American users, those with higher incomes show greater political interest. The demographic analysis highlights that Republicans are particularly active on social media - potentially influencing their social media engagement patterns. However, the study acknowledges a crucial limitation - the lack of direct data regarding the content users are exposed to which is shaping their social media experiences. Future research should explore these influences and consider additional popular platforms to enhance the understanding of social media's political impact. Addressing these gaps can provide deeper insights into digital political mobilization, aiding policymakers, educators, and platform designers in fostering healthier democratic engagement.

Margarida Mendonca, Alvaro Figueira

Social media has reshaped political discourse, offering politicians a platform for direct engagement while reinforcing polarization and ideological divides. This study introduces a novel topic evolution framework that integrates BERTopic-based topic modeling with Moral Foundations Theory (MFT) to analyze the longevity and moral dimensions of political topics in Twitter activity during the 117th U.S. Congress. We propose a methodology for tracking dynamic topic shifts over time and measuring their association with moral values and quantifying topic persistence. Our findings reveal that while overarching themes remain stable, granular topics tend to dissolve rapidly, limiting their long-term influence. Moreover, moral foundations play a critical role in topic longevity, with Care and Loyalty dominating durable topics, while partisan differences manifest in distinct moral framing strategies. This work contributes to the field of social network analysis and computational political discourse by offering a scalable, interpretable approach to understanding moral-driven topic evolution on social media.

Lincan Li, Jiaqi Li, Catherine Chen et al.

In recent years, large language models (LLMs) have been widely adopted in political science tasks such as election prediction, sentiment analysis, policy impact assessment, and misinformation detection. Meanwhile, the need to systematically understand how LLMs can further revolutionize the field also becomes urgent. In this work, we--a multidisciplinary team of researchers spanning computer science and political science--present the first principled framework termed Political-LLM to advance the comprehensive understanding of integrating LLMs into computational political science. Specifically, we first introduce a fundamental taxonomy classifying the existing explorations into two perspectives: political science and computational methodologies. In particular, from the political science perspective, we highlight the role of LLMs in automating predictive and generative tasks, simulating behavior dynamics, and improving causal inference through tools like counterfactual generation; from a computational perspective, we introduce advancements in data preparation, fine-tuning, and evaluation methods for LLMs that are tailored to political contexts. We identify key challenges and future directions, emphasizing the development of domain-specific datasets, addressing issues of bias and fairness, incorporating human expertise, and redefining evaluation criteria to align with the unique requirements of computational political science. Political-LLM seeks to serve as a guidebook for researchers to foster an informed, ethical, and impactful use of Artificial Intelligence in political science. Our online resource is available at: http://political-llm.org/.

Sophia Hunger, F. Paxton

Abstract Although attention to populism is ever-increasing, the concept remains contested. This paper provides a comprehensive overview of populism research and identifies tendencies to a conflation of host ideologies and populism in political science through a two-step analysis. First, we conduct a quantitative review of 884 abstracts from 2004 to 2018 using text-as-data methods. We show that scholars sit at “separate tables,” divided by geographical foci, methods, and host ideologies. Next, our qualitative analysis of 50 articles finds a common conflation of populism with other ideologies, resulting in the analytical neglect of the former. We, therefore, urge researchers to properly distinguish populism from “what it travels with” and engage more strongly with the dynamic interlinkages between thin and thick ideologies.

J. Lynch

The public's health is intimately linked to politics and policy. But political science has yet to make a major contribution to understanding the political economy of health (as distinct from medical care). In order to advance understanding of the drivers of health in an era of emerging infectious disease and global pandemics, more political scientists must begin to do what we are uniquely well situated to do: analyze in a contextualized way the pathways and mechanisms through which power configurations cause illness and inequity. This article reviews key findings from recent literature about the policy, political, and structural contributors to population health and health equity and sketches what a political economy of health more deeply rooted in political science could look like. Expected final online publication date for the Annual Review of Political Science, Volume 26 is June 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

D. Teele, K. Thelen

Mitchell Linegar, Rafal Kocielnik, R. M. Alvarez

Large Language Models (LLMs) are a type of artificial intelligence that uses information from very large datasets to model the use of language and generate content. While LLMs like GPT-3 have been used widely in many applications, the recent public release of OpenAI's ChatGPT has opened more debate about the potential uses and abuses of LLMs. In this paper, we provide a brief introduction to LLMs and discuss their potential application in political science and political methodology. We use two examples of LLMs from our recent research to illustrate how LLMs open new areas of research. We conclude with a discussion of how researchers can use LLMs in their work, and issues that researchers need to be aware of regarding using LLMs in political science and political methodology.

Michel Waly DIOUF

Cet article examine la réutilisation des coquillages fossiles et décrit en même temps les anomalies ou les déformations observées sur les individus. La démarche adoptée repose en effet sur une combinaison de plusieurs activités allant de la recherche documentaire à l’examen du mobilier coquillier, en passant par les enquêtes ethnographiques, la prospection et les fouilles archéologiques. Nos fouilles effectuées sur le site de Balloum, près du village de Moundé (basSaloum) ont mis au jour des spécimens coquilliers déformés ou réutilisés le plus souvent en des objets de parures ou d’ustensiles. Mots-clés : ,

Rainer Rehak

A lot of business and research effort currently deals with the so called decentralised ledger technology blockchain. Putting it to use carries the tempting promise to make the intermediaries of social interactions superfluous and furthermore keep secure track of all interactions. Currently intermediaries such as banks and notaries are necessary and must be trusted, which creates great dependencies, as the financial crisis of 2008 painfully demonstrated. Especially banks and notaries are said to become dispensable as a result of using the blockchain. But in real-world applications of the blockchain, the power of central actors does not dissolve, it only shifts to new, democratically illegitimate, uncontrolled or even uncontrollable power centers. As interesting as the blockchain technically is, it doesn't efficiently solve any real-world problem and is no substitute for traditional political processes or democratic regulation of power. Research efforts investigating the blockchain should be halted.