Hasil untuk "Political Science"

M. Strathern

In the most original and ambitious synthesis yet undertaken in Melanesian scholarship, Marilyn Strathern argues that gender relations have been a particular casualty of unexamined assumptions held by Western anthropologists and feminist scholars alike. The book treats with equal seriousness - and with equal good humor - the insights of Western social science, feminist politics, and ethnographic reporting, in order to rethink the representation of Melanesian social and cultural life. This makes "The Gender of the Gift" one of the most sustained critiques of cross-cultural comparison that anthropology has seen, and one of its most spirited vindications.

Nir Grinberg, K. Joseph, Lisa Friedland et al.

Finding facts about fake news There was a proliferation of fake news during the 2016 election cycle. Grinberg et al. analyzed Twitter data by matching Twitter accounts to specific voters to determine who was exposed to fake news, who spread fake news, and how fake news interacted with factual news (see the Perspective by Ruths). Fake news accounted for nearly 6% of all news consumption, but it was heavily concentrated—only 1% of users were exposed to 80% of fake news, and 0.1% of users were responsible for sharing 80% of fake news. Interestingly, fake news was most concentrated among conservative voters. Science, this issue p. 374; see also p. 348 A small proportion of voters share and are exposed to the majority of online fake news. The spread of fake news on social media became a public concern in the United States after the 2016 presidential election. We examined exposure to and sharing of fake news by registered voters on Twitter and found that engagement with fake news sources was extremely concentrated. Only 1% of individuals accounted for 80% of fake news source exposures, and 0.1% accounted for nearly 80% of fake news sources shared. Individuals most likely to engage with fake news sources were conservative leaning, older, and highly engaged with political news. A cluster of fake news sources shared overlapping audiences on the extreme right, but for people across the political spectrum, most political news exposure still came from mainstream media outlets.

L. Winner

In controversies about technology and society, there is no idea more pro vocative than the notion that technical things have political qualities. At issue is the claim that the machines, structures, and systems of modern material culture can be accurately judged not only for their contributions of efficiency and pro ductivity, not merely for their positive and negative environmental side effects, but also for the ways in which they can embody specific forms of power and authority. Since ideas of this kind have a persistent and troubling presence in discussions about the meaning of technology, they deserve explicit attention.1 Writing in Technology and Culture almost two decades ago, Lewis Mumford gave classic statement to one version of the theme, arguing that "from late neo lithic times in the Near East, right down to our own day, two technologies have recurrently existed side by side: one authoritarian, the other democratic, the first system-centered, immensely powerful, but inherently unstable, the other man-centered, relatively weak, but resourceful and durable."2 This thesis stands at the heart of Mumford's studies of the city, architecture, and the his tory of technics, and mirrors concerns voiced earlier in the works of Peter Kropotkin, William Morris, and other nineteenth century critics of industrial ism. More recently, antinuclear and prosolar energy movements in Europe and America have adopted a similar notion as a centerpiece in their arguments. Thus environmentalist Denis Hayes concludes, "The increased deployment of nuclear power facilities must lead society toward authoritarianism. Indeed, safe reliance upon nuclear power as the principal source of energy may be possible only in a totalitarian state." Echoing the views of many proponents of appropri ate technology and the soft energy path, Hayes contends that "dispersed solar sources are more compatible than centralized technologies with social equity, freedom and cultural pluralism."3 An eagerness to interpret technical artifacts in political language is by no means the exclusive property of critics of large-scale high-technology systems. A long lineage of boosters have insisted that the "biggest and best" that science and industry made available were the best guarantees of democracy, freedom, and social justice. The factory system, automobile, telephone, radio, television, the space program, and of course nuclear power itself have all at one time or another been described as democratizing, liberating forces. David Lilienthal, in T.V.A.: Democracy on the March, for example, found this promise in the phos 121

D. Abson, J. Fischer, J. Leventon et al.

M. Bošnjak, I. Ajzen, P. Schmidt

This editorial gives a brief introduction to the articles included in the thematic section of Europe's Journal of Psychology, which is devoted to selected recent advances and applications of the theory of planned behavior (TPB). The five contributions address two thematic streams: (1) adjustments and extensions of the original theory and (2) applications of the TPB in public health and the political sciences.

Jennifer McCoy, Tahmina Rahman, M. Somer

Thomas J. Leeper, S. Hobolt, James Tilley

Conjoint analysis is a common tool for studying political preferences. The method disentangles patterns in respondents’ favorability toward complex, multidimensional objects, such as candidates or policies. Most conjoints rely upon a fully randomized design to generate average marginal component effects (AMCEs). They measure the degree to which a given value of a conjoint profile feature increases, or decreases, respondents’ support for the overall profile relative to a baseline, averaging across all respondents and other features. While the AMCE has a clear causal interpretation (about the effect of features), most published conjoint analyses also use AMCEs to describe levels of favorability. This often means comparing AMCEs among respondent subgroups. We show that using conditional AMCEs to describe the degree of subgroup agreement can be misleading as regression interactions are sensitive to the reference category used in the analysis. This leads to inferences about subgroup differences in preferences that have arbitrary sign, size, and significance. We demonstrate the problem using examples drawn from published articles and provide suggestions for improved reporting and interpretation using marginal means and an omnibus F-test. Given the accelerating use of these designs in political science, we offer advice for best practice in analysis and presentation of results.

Stacy Alaimo

Ronald D. Anderson

W. Riker

R. D'amico

Douglas P. Murray

P. Bourdieu

Moritz Laurer, Wouter van Atteveldt, Andreu Casas et al.

Supervised machine learning is an increasingly popular tool for analyzing large political text corpora. The main disadvantage of supervised machine learning is the need for thousands of manually annotated training data points. This issue is particularly important in the social sciences where most new research questions require new training data for a new task tailored to the specific research question. This paper analyses how deep transfer learning can help address this challenge by accumulating “prior knowledge” in language models. Models like BERT can learn statistical language patterns through pre-training (“language knowl-edge”), and reliance on task-specific data can be reduced by training on universal tasks like natural language inference (NLI; “task knowledge”). We demonstrate the benefits of transfer learning on a wide range of eight tasks. Across these eight tasks, our BERT-NLI model fine-tuned on 100 to 2,500 texts performs on average 10.7 to 18.3 percentage points better than classical models without transfer learning. Our study indicates that BERT-NLI fine-tuned on 500 texts achieves similar performance as classical models trained on around 5,000 texts. Moreover, we show that transfer learning works particularly well on imbalanced data. We conclude by discussing limitations of transfer learning and by outlining new opportunities for political science research.

Bernabé Palacín Sáenz

Objetivos: capacitar a los compradores públicos en el uso de la perspectiva estratégica del contrato y en las competencias no formales para alcanzar una mayor eficiencia en la calidad de la prestación y en la utilización de los fondos públicos. Obtener la máxima complicidad de los operadores económicos, especialmente de las PYME, en los procesos de compra pública. Metodología: análisis clásico de marco normativo, doctrina científica y administrativa y jurisprudencia, así como de competencias no jurídicas, tales como las capacidades de comunicación, negociación, empatía y gestión de proyectos y de riesgos, consustanciales a la buena administración. Resultados: estudio del grado de interiorización de las compras estratégicas y sus áreas de mejora, con ejemplos de clausulado con perspectiva social y medioambiental que incluir en los pliegos de cláusulas administrativas particulares. Conclusiones: la fundamental conclusión de este trabajo es que es posible progresar en la interiorización de la compra pública sociorresponsable dotando a los empleados públicos tramitadores de instrumentos que garanticen la seguridad jurídica y el control material, no formal, de los procesos, y promover una mayor participación de las pymes, mediante la mejora de las aquí denominadas competencias no formales, tales como las capacidades de comunicación, negociación, empatía, gestión de proyectos y flexibilidad de los compradores públicos.

Angelo Arcuri, Lorenzo Giolli, Cosimo Magazzino

Addressing critical challenges such as climate change, environmental degradation, and resource depletion requires a swift transition to efficient and environmentally friendly energy solutions. Among these, geothermal energy is recognized for its dependability, low environmental impact, and versatility. This study investigates the role of geothermal energy in Italy’s business sector, examining its impact on companies and social perception. It specifically evaluates how communicating geological, hydrological, and atmospheric risks associated with geothermal projects influences firms’ likelihood of experiencing social acceptance challenges. Additionally, this research quantifies the impact of geothermal energy adoption on companies’ energy costs and CO₂ emissions. The analysis further explores the long-term implications of expanding the use of this renewable resource through sensitivity analysis, focusing on its effects on emissions and costs. The findings indicate that firms communicating geothermal-related risks are less likely to experience social acceptance challenges compared to those that do not. Moreover, this study shows that the use of geothermal energy positively impacts firms’ business and environmental performance by reducing energy costs and CO₂ emissions. Sensitivity analysis demonstrates that increasing the proportion of geothermal energy usage amplifies these benefits, thereby enhancing firms’ competitiveness. This research provides a comprehensive framework for promoting geothermal energy integration in business operations, offering valuable insights to support the global shift toward sustainable energy systems.

Marcio Pascoal Cassandre

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Amir Mohammad Rezaei, Esmaeil yaghoubi, zahra Omidvar

Despite Iran’s rich biodiversity and recent policy support, the medicinal plants industry still holds a minor share of global markets and remains largely focused on raw-material production. This study aims to design and develop a localized, flexible business model for knowledge-based firms in the medicinal plants domain to help them move from commodity sales toward technology-driven value creation, market development, and exports. An exploratory–sequential mixed-methods approach was used. In the qualitative phase, content analysis of documents and semi-structured interviews with 17 participants—including managers of knowledge-based firms, technology experts, and science and technology park specialists—identified six key dimensions: (1) capital and financial resources, (2) technological linkages and infrastructure, (3) regulation and policy, (4) market and marketing, (5) open innovation and network collaboration, and (6) business model flexibility. Based on these findings, a survey instrument was developed and the quantitative data were analyzed using partial least squares structural equation modeling (PLS-SEM) in SmartPLS 3. Results show that all six dimensions significantly influence the design of business model components—value proposition, customer segments, key resources, and channels—which, in turn, improve firms’ innovation performance, market development, and export capability. Theoretically, the proposed model integrates causation and effectuation perspectives in entrepreneurship while emphasizing open innovation and network interaction, offering a comprehensive, context-specific view of business model development.

J. Lubchenco, K. Grorud‐Colvert

Srijoni Sen, Trishi Jindal

A number of data governance policies have recently been introduced or revised by the Indian Government with the stated goal of unlocking the developmental and economic potential of data. The policies seek to implement standardized frameworks for public data management and establish platforms for data exchange. However, India has a longstanding history of record-keeping and information transparency practices, which are crucial in the context of data management. These connections have not been explicitly addressed in recent policies like the Draft National Data Governance Framework, 2022. To understand if record management has a role to play in modern public data governance, we analyze the key new data governance framework and the associated Indian Urban Data Exchange platform as a case study. The study examines the exchange where public records serve as a potential source of data. It evaluates the coverage and the actors involved in the creation of this data to understand the impact of records management on government departments’ ability to publish datasets. We conclude that while India recognizes the importance of data as a public good, it needs to integrate digital records management practices more effectively into its policies to ensure accurate, up-to-date, and accessible data for public benefit.