Emotions, such as anger and anxiety, play a central role in political behavior and are extensively studied by political scientists. However, political science has largely adopted psychological theories of emotions without empirically testing their core assumptions in political contexts.In this paper, we focus on cognitive appraisal theory and test whether political emotions follow distinct appraisal patterns, and whether the underlying theoretical models accurately explain how discrete emotions emerge in political contexts. We conducted two surveys in the U.S. in 2022 and 2023. Participants recalled emotional experiences from either the personal or political domain, labeled their emotions, and rated the event along 18 cognitive appraisal dimensions. We then trained several models to predict the emotion label based on the reported appraisals.In non-political contexts, we can predict emotions based on the reported appraisals with high accuracy and discrete emotions align with theoretical appraisal patterns. However, in political contexts, negative emotions (anger, anxiety, despair) have overlapping appraisal profiles, and models perform consistently worse when trying to predict these emotions.These findings challenge the assumption that emotions function similarly in political and personal domains and suggest that existing appraisal-based models do not sufficiently capture political emotions. Our results highlight the need for revised theoretical frameworks that account for contextual differences in emotional processes within political science.
Prompt-based language models like GPT4 and LLaMa have been used for a wide variety of use cases such as simulating agents, searching for information, or for content analysis. For all of these applications and others, political biases in these models can affect their performance. Several researchers have attempted to study political bias in language models using evaluation suites based on surveys, such as the Political Compass Test (PCT), often finding a particular leaning favored by these models. However, there is some variation in the exact prompting techniques, leading to diverging findings, and most research relies on constrained-answer settings to extract model responses. Moreover, the Political Compass Test is not a scientifically valid survey instrument. In this work, we contribute a political bias measured informed by political science theory, building on survey design principles to test a wide variety of input prompts, while taking into account prompt sensitivity. We then prompt 11 different open and commercial models, differentiating between instruction-tuned and non-instruction-tuned models, and automatically classify their political stances from 88,110 responses. Leveraging this dataset, we compute political bias profiles across different prompt variations and find that while PCT exaggerates bias in certain models like GPT3.5, measures of political bias are often unstable, but generally more left-leaning for instruction-tuned models. Code and data are available on: https://github.com/MaFa211/theory_grounded_pol_bias
This paper reviews research literature on Diamond Open Access (DOA) journals - sometimes also called Platinum Open Access - that was produced after this journal segment started to become a priority in European research policy around 2020. It contextualizes the current science policy debate, critically examines different understandings of DOA, and reviews studies on the role of such journals in scholarly communication. Most existing research consists of quantitative studies focusing on aspects such as the number of DOA journals, their publication output, the diversity of the landscape in terms of subject areas, languages, publishing entities, indexing in major databases, awareness and perception among scholars, cost analyses, as well as insights into the internal operations of DOA journals. The review shows that research on DOA journals is partly influenced by the science policy discourse in at least two ways: first, through the normativity inherent in that discourse, and second, through the temporality of policy-driven research of practical relevance, which leaves important aspects of the phenomenon understudied. Moreover, research on the DOA journal landscape has implications beyond understanding this particular journal segment, as it also challenges established views of the global system of scholarly communication.
The field of Computer science (CS) has rapidly evolved over the past few decades, providing computational tools and methodologies to various fields and forming new interdisciplinary communities. This growth in CS has significantly impacted institutional practices and relevant research communities. Therefore, it is crucial to explore what specific research values, known as basic and fundamental beliefs that guide or motivate research attitudes or actions, CS-related research communities promote. Prior research has manually analyzed research values from a small sample of machine learning papers. No prior work has studied the automatic detection of research values in CS from large-scale scientific texts across different research subfields. This paper introduces a detailed annotation scheme featuring ten research values that guide CS-related research. Based on the scheme, we build value classifiers to scale up the analysis and present a systematic study over 226,600 paper abstracts from 32 CS-related subfields and 86 popular publishing venues over ten years.
Resumo: O objetivo deste artigo é analisar como o rodoviarismo tornou-se um elemento nevrálgico no conjunto da política brasileira na primeira parte do chamado período de democratização, entre a queda do Estado Novo, em outubro de 1945, e o término do governo provisório de Nereu Ramos, em 1956. Ancorado na teoria de Nunes ( 1997 ) das novas gramáticas políticas nas relações entre Estado e sociedade a partir do Estado Novo (1937-1945) e em farta pesquisa empírica, procura-se demonstrar que a força política adquirida pelos agentes do rodoviarismo dependeu, em última instância, do papel assumido pelo Departamento Nacional de Estradas de Rodagem (DNER), que a todo custo buscou manter um grau substancial de “insulamento burocrático” diante da conturbada conjuntura política da época.
This paper aims to examine the complex interplay between migration, human rights, and security, focusing on the recent trends in state responses to refugee protection and the implications for international human rights standards. A qualitative analysis of current literature, policy documents, and case studies was conducted to assess the evolving political dynamics surrounding migration. The study also evaluates the roles of international organizations, such as the United Nations High Commissioner for Refugees (UNHCR), and non-governmental organizations (NGOs) in shaping refugee protection norms. Results: The findings reveal a significant rollback in state commitments to refugee protection, driven by rising nationalism and security concerns. This regression has resulted in the implementation of restrictive migration policies that prioritize national interests over humanitarian obligations, leading to increased vulnerability for displaced populations. The analysis highlights the critical role of NGOs and international bodies in advocating for refugee rights, despite facing challenges from state-centric approaches and power imbalances. Conclusions: The paper concludes that addressing the challenges at the intersection of migration, human rights, and security requires a concerted effort among states, civil society, and international organizations. By fostering collaboration and recognizing the human rights implications of migration, it is possible to develop more inclusive and compassionate policies that uphold the dignity and well-being of refugees and asylum seekers in a rapidly changing global context. give a great title for this article
This study aimed to examine an assumption that generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We compared the performance of ChatGPT and GPT-4 on 2019 NAEP science assessments with students by cognitive demands of the items. Fifty-four tasks were coded by experts using a two-dimensional cognitive load framework, including task cognitive complexity and dimensionality. ChatGPT and GPT-4 responses were scored using the scoring keys of NAEP. The analysis of the available data was based on the average student ability scores for students who answered each item correctly and the percentage of students who responded to individual items. Results showed that both ChatGPT and GPT-4 consistently outperformed most students who answered the NAEP science assessments. As the cognitive demand for NAEP tasks increases, statistically higher average student ability scores are required to correctly address the questions. This pattern was observed for students in grades 4, 8, and 12, respectively. However, ChatGPT and GPT-4 were not statistically sensitive to the increase in cognitive demands of the tasks, except for Grade 4. As the first study focusing on comparing GAI and K-12 students in problem-solving in science, this finding implies the need for changes to educational objectives to prepare students with competence to work with GAI tools in the future. Education ought to emphasize the cultivation of advanced cognitive skills rather than depending solely on tasks that demand cognitive intensity. This approach would foster critical thinking, analytical skills, and the application of knowledge in novel contexts. Findings also suggest the need for innovative assessment practices by moving away from cognitive intensity tasks toward creativity and analytical skills to avoid the negative effects of GAI on testing more efficiently.
I report here a comprehensive analysis about the political preferences embedded in Large Language Models (LLMs). Namely, I administer 11 political orientation tests, designed to identify the political preferences of the test taker, to 24 state-of-the-art conversational LLMs, both closed and open source. When probed with questions/statements with political connotations, most conversational LLMs tend to generate responses that are diagnosed by most political test instruments as manifesting preferences for left-of-center viewpoints. This does not appear to be the case for five additional base (i.e. foundation) models upon which LLMs optimized for conversation with humans are built. However, the weak performance of the base models at coherently answering the tests' questions makes this subset of results inconclusive. Finally, I demonstrate that LLMs can be steered towards specific locations in the political spectrum through Supervised Fine-Tuning (SFT) with only modest amounts of politically aligned data, suggesting SFT's potential to embed political orientation in LLMs. With LLMs beginning to partially displace traditional information sources like search engines and Wikipedia, the societal implications of political biases embedded in LLMs are substantial.
Predicting roll call votes through modeling political actors has emerged as a focus in quantitative political science and computer science. Widely used embedding-based methods generate vectors for legislators from diverse data sets to predict legislative behaviors. However, these methods often contend with challenges such as the need for manually predefined features, reliance on extensive training data, and a lack of interpretability. Achieving more interpretable predictions under flexible conditions remains an unresolved issue. This paper introduces the Political Actor Agent (PAA), a novel agent-based framework that utilizes Large Language Models to overcome these limitations. By employing role-playing architectures and simulating legislative system, PAA provides a scalable and interpretable paradigm for predicting roll-call votes. Our approach not only enhances the accuracy of predictions but also offers multi-view, human-understandable decision reasoning, providing new insights into political actor behaviors. We conducted comprehensive experiments using voting records from the 117-118th U.S. House of Representatives, validating the superior performance and interpretability of PAA. This study not only demonstrates PAA's effectiveness but also its potential in political science research.
This definitive contribution to social science literature describes German's general theory of authoritarianism in modem society, and applies it to authoritarian movements and regimes likely to merge out of the social mobilization of the middle and lower classes. Germani analyzes the nature, conditions, and determinants of authoritarianism in the context of Latin American political and social developments and compares it to European fascist movements.
ABSTRACT Research in Political Science is increasingly based on qualitative and interpretative methods. Based on concrete experiences in a comprehensive qualitative interpretative study, this article discusses general challenges of interpretative methodologies and their application in Political Science. It fills a gap in the current methods literature by concretely explaining how the methodological presumptions of interpretative research are to be carried out in such a way that they lead to substantial findings, irrespective of the material, cases and method one choses. To do so, it is core to analyse not only the ‘what’, but also the ‘how’ and the ‘why’ in the material. A classical qualitative content analysis consists in analysing the ‘what’ in a text, a field, or a visual, that is, utterances, arguments, or concepts that are used in it. Beyond this, in a qualitative interpretative project, the second part of analysis targets the ‘how’ and ‘why’ of constructing meanings, narratives, arguments, topoi, or (mental) images. Analysing the ‘how’ and ‘why’ requires specific analytical and interpretative steps which are, however, barely discussed in the methods literature. Based on the experiences in a concrete research project, the article explains how to structure analytical steps for researching the ‘how’ and the ‘why’.
Abstract The Quadruple Helix Model of innovation recognizes four major actors in the innovation system: science, policy, industry, and society. In keeping with this model, more and more governments are prioritizing greater public involvement in innovation processes. The goal of this study was to identify desirable and productive forms of interaction between the scientific community and the public. Our analysis focuses on the point of view of societal actors, which has so far been largely neglected in scientific literature and political discourse. To this end, we interviewed 50 laypersons with participatory research and innovation experience in Germany to document their opinions of the value of such interaction, the goals it should pursue, and the forms it should take. Rather than preferring the democratization of science in general, interviewees expressed the desire for more extensive opportunities to introduce scientific and technological considerations as part of bidirectional exchanges between academia and society. This paper proposes a layperson typology intended to help design participatory processes that facilitate such exchanges and includes the differences in opinions between men and women.
Serious concerns about public distrust of scientific experts and the spread of misinformation are growing in the US and elsewhere. To gauge ideological and psychological variability in attitudes toward science, we conducted an extensive analysis of public opinion data based on a nationally representative survey of U.S. adults (N = 1,500) and a large replication sample (N = 2,119). We estimated the unique effects of partisanship, symbolic and operational forms of political ideology, right-wing authoritarianism (RWA), social dominance orientation (SDO), and general system justification (GSJ), after adjusting for demographic factors. Multiverse analyses revealed that (a) conservatism and SDO were significant predictors of distrust of climate science in > 99.9% of model specifications, with conservatism accounting for 80% of the total variance; (b) conservatism, RWA, religiosity, (male) sex, (low) education, (low) income, and distrust of climate science were significant predictors of skepticism about science in general (vs. faith) in > 99.9% of model specifications; (c) conservatism, RWA, (low) education, and distrust of climate science were significant predictors of trust in ordinary people (over scientific experts) > 99.9% of the time; and (d) GSJ was a significant predictor of trust in scientific experts (over ordinary people) 81% of the time, after adjusting for all other demographic and ideological factors. Implications for the role of science in democratic society are discussed.
The attainment of adequate electoral participation in a democratic setting is essential to maintain legitimacy, credibility, and stability since democracy is about popular representation. However, from available data worldwide, voter participation is gradually on the decline. The study aimed to ascertain the reasons, nature and implication of voter abstention for Nigeria’s democratic development. This study thus surveyed the perceptions of Nigerians on the factors influencing low-level participation of eligible voters in the Nigerian electoral process. The study adopted the mixed model research design. A sample of 1,200 respondents was chosen from the selected local government areas of the six zones using the stratified random sampling technique. The simple percentages and Pearson’s Correlation Coefficient statistical technique were used to test and determine the degree of association intrinsic in the stated research questions for the quantitative data. The descriptive-analytical technique was adopted to analyze the qualitative aspect of the data. The findings from the study showed that the failure of elected political officers to fulfill electoral promises, electoral fraud, and violence, are responsible for voter alienation in Nigeria. Consequently, the following suggestions are made: The elected political officials should ensure good governance based on meeting the needs of the citizenry; fraudulent practices during elections should be penalized with appropriate sanctions and the governments at all levels should put on modalities to mitigate the incidences of violence during elections. Achieving a credible, free, fair and effective electoral process would, therefore, require the partnership of all stakeholders in the Nigerian democratic project.
Amir Hossein Shaddel, Mohammad Saeid Taslimi, Mohammad Ali Lessani Fesharaki
Objective
This study aims to identify the organizational responsibilities of managers in providing employees with “commands” and its related derivatives by examining the verses of the Holy Quran.
Methods
The methodology used in this study to explore the role of command in organizational culture in the light of the Holy Quran is the subjective research method within the Holy Quran. Hadiths, interpretive, translation, and lexical sources were also utilized to enrich the research. Thematic axes were designed, and the extracted concepts were organized under them.
Results
Competent managers issue commands by assessing the situation and considering various conditions to ensure their successful implementation. These conditions include adherence to organizational rules and regulations, clear communication of rules and commands, continuous development and self-improvement of managers, fostering an organizational environment that resembles a family where managers pay attention to employees as if they were family members, implementing an employee meal plan, managing based on individual employee characteristics, encouraging organizational participation of employees, managing the organization with trust in God (a vital value that affects all managerial duties), and employing a system of encouragement and punishment.
Conclusion
The responsibilities of managers in commanding employees within organizations encompass three distinct phases: pre-commanding, commanding, and post-commanding, each involving various components.
Political institutions and public administration (General)
The causal relationship between human interference in both climate change and decrease in biodiversity is unquestionable. This fact supports the need to act effectively against those illegal activities affecting wildlife. Hungary is also involved in wildlife crimes, but there is a noticeable deficit in the processes of uncovering these actions, gathering proof and punishing those responsible. In this study the Authors examine what role forensics may play in the fight against wildlife crime.
Aim: Present the characteristics of wildlife crimes and outline the main features of wildlife forensics.
Methodology: The current national and international legal background and norms and guidelines for professional conduct are surveyed. The Authors also reviewed the most important relevant Hungarian and international scientific literature.
Findings: One of the most important and vital tasks of modern civilization is the preservation and protection of the environment – with an emphasis on life on Earth. As part of this process there is a place for law enforcement to detect, punish and prevent further criminal activity connected with illegal activities involving wildlife. In Hungary the major barriers to effective punishment of those responsible for wildlife crimes are primarily: the lack of forensic technicians with sufficient specialized knowledge and practice; missing specialized standard operational protocols; insufficient knowledge of biology within law enforcement; insufficient funding of non-human genetic laboratories and the lack of adequate non-human (genetic) databases.
Value: For the first time in Hungary, the Authors outline the basic characteristics of wildlife forensics.
Political institutions and public administration (General)
While sanctions in political and economic areas are now part of the standard repertoire of Western countries (not always endorsed by UN mandates), sanctions in science and culture in general are new. Historically, fundamental research as conducted at international research centers such as CERN has long been seen as a driver for peace, and the Science4Peace idea has been celebrated for decades. However, much changed with the war against Ukraine, and most Western science organizations put scientific cooperation with Russia and Belarus on hold immediately after the start of the war in 2022. In addition, common publications and participation in conferences were banned by some institutions, going against the ideal of free scientific exchange and communication. These and other points were the topics of an international virtual panel discussion organized by the Science4Peace Forum together with the "Natural Scientists Initiative - Responsibility for Peace and Sustainability" (NatWiss e.V.) in Germany and the journal "Wissenschaft und Frieden" (W&F) (see the Figure). Fellows from the Hamburg Institute for Peace Research and Security Policy (IFSH), scientists collaborating with the large physics research institutes DESY and CERN, as well as from climate and futures researchers were represented on the panel. In this Dossier we document the panel discussion, and give additional perspectives. The authors of the individual sections present their personal reflections, which should not be taken as implying that they are endorsed by the Science4Peace Forum or any other organizations. It is regrettable that some colleagues who expressed support for this document felt that it would be unwise for them to co-sign it.