Stefano Civelli, Pietro Bernardelle, Gianluca Demartini
While pretraining language models with politically diverse content has been shown to improve downstream task fairness, such approaches require significant computational resources often inaccessible to many researchers and organizations. Recent work has established that persona-based prompting can introduce political diversity in model outputs without additional training. However, it remains unclear whether such prompting strategies can achieve results comparable to political pretraining for downstream tasks. We investigate this question using persona-based prompting strategies in multimodal hate-speech detection tasks, specifically focusing on hate speech in memes. Our analysis reveals that when mapping personas onto a political compass and measuring persona agreement, inherent political positioning has surprisingly little correlation with classification decisions. Notably, this lack of correlation persists even when personas are explicitly injected with stronger ideological descriptors. Our findings suggest that while LLMs can exhibit political biases in their responses to direct political questions, these biases may have less impact on practical classification tasks than previously assumed. This raises important questions about the necessity of computationally expensive political pretraining for achieving fair performance in downstream tasks.
The value of time management lies in the fact that people have too many tasks they need to do but not enough time for the things that they want to do. The study therefore, examined time management and employee productivity in government institutions in Delta State. The study adopted Time Management Quadrant theory. The study utilized secondary source of data. The study revealed that effective time management not only affects the productivity of employees, but also helps to cope with stress, conflicts and pressure more efficiently. It also helps them maintain a healthy work-life balance and keeps them motivated. The recommended that time should be set for the accomplishment of all activities by government at all levels including the core ministries. Adequate provisions should be made for the attainment of the goals set, among others.
Ahana Biswas, Yu-Ru Lin, Yuehong Cassandra Tai
et al.
Elected officials have privileged roles in public communication. In contrast to national politicians, whose posting content is more likely to be closely scrutinized by a robust ecosystem of nationally focused media outlets, sub-national politicians are more likely to openly disseminate harmful content with limited media scrutiny. In this paper, we analyze the factors that explain the online visibility of over 6.5K unique state legislators in the US and how their visibility might be impacted by posting low-credibility or uncivil content. We conducted a study of posting on Twitter and Facebook (FB) during 2020-21 to analyze how legislators engage with users on these platforms. The results indicate that distributing content with low-credibility information attracts greater attention from users on FB and Twitter for Republicans. Conversely, posting content that is considered uncivil on Twitter receives less attention. A noticeable scarcity of posts containing uncivil content was observed on FB, which may be attributed to the different communication patterns of legislators on these platforms. In most cases, the effect is more pronounced among the most ideologically extreme legislators. Our research explores the influence exerted by state legislators on online political conversations, with Twitter and FB serving as case studies. Furthermore, it sheds light on the differences in the conduct of political actors on these platforms. This study contributes to a better understanding of the role that political figures play in shaping online political discourse.
As modern large language models (LLMs) become integral to everyday tasks, concerns about their inherent biases and their potential impact on human decision-making have emerged. While bias in models are well-documented, less is known about how these biases influence human decisions. This paper presents two interactive experiments investigating the effects of partisan bias in LLMs on political opinions and decision-making. Participants interacted freely with either a biased liberal, biased conservative, or unbiased control model while completing these tasks. We found that participants exposed to partisan biased models were significantly more likely to adopt opinions and make decisions which matched the LLM's bias. Even more surprising, this influence was seen when the model bias and personal political partisanship of the participant were opposite. However, we also discovered that prior knowledge of AI was weakly correlated with a reduction of the impact of the bias, highlighting the possible importance of AI education for robust mitigation of bias effects. Our findings not only highlight the critical effects of interacting with biased LLMs and its ability to impact public discourse and political conduct, but also highlights potential techniques for mitigating these risks in the future.
The release of ChatGPT in November 2022 prompted a massive uptake of generative artificial intelligence (GenAI) across higher education institutions (HEIs). HEIs scrambled to respond to its use, especially by students, looking first to regulate it and then arguing for its productive integration within teaching and learning. In the year since the release, HEIs have increasingly provided policies and guidelines to direct GenAI. In this paper we examined documents produced by 116 US universities categorized as high research activity or R1 institutions to comprehensively understand GenAI related advice and guidance given to institutional stakeholders. Through an extensive analysis, we found the majority of universities (N=73, 63%) encourage the use of GenAI and many provide detailed guidance for its use in the classroom (N=48, 41%). More than half of all institutions provided sample syllabi (N=65, 56%) and half (N=58, 50%) provided sample GenAI curriculum and activities that would help instructors integrate and leverage GenAI in their classroom. Notably, most guidance for activities focused on writing, whereas code and STEM-related activities were mentioned half the time and vaguely even when they were (N=58, 50%). Finally, more than one half of institutions talked about the ethics of GenAI on a range of topics broadly, including Diversity, Equity and Inclusion (DEI) (N=60, 52%). Overall, based on our findings we caution that guidance for faculty can become burdensome as extensive revision of pedagogical approaches is often recommended in the policies.
Manuel Octavio del Campo Villares, Eladio Jardón Ferreiro, Karla Ladrón de Guevara Marín
et al.
The purpose of this document is to identify which actions in the Equal Opportunities Plan 2023–2026 of the Ourense Provincial Council have the potential to increase equality of opportunity between women and men in positions of similar status, with respect to an analysis of the objectives of the First Equality Plan of (2017–2021). The methodology for measuring the achievements of these strategic objectives consisted of a descriptive comparative study, where the changes in the stated objectives were analyzed, and a quantitative functional study was undertaken to determine the relationship between the typology and functionality of each position. A clear distinction was made between the goals achieved and those requiring more decisive intervention in future. In addition, it recognizes that women are very underrepresented in the most desirable positions at Ourense Provincial Council.
Political institutions and public administration (General), Public law
The article is devoted to the consideration and transformation of social and administrative problems of municipalities with low initiative of citizens. The empirical basis was the data of sociological research (surveys), conducted by the author in the urban district of Krasnoturinsk (Sverdlovsk region) before and after the announcement of partial mobilization. In the course of the study the social problems of the territory, the level of trust in the local authorities, interaction with them, as well as the dynamics of changes in these aspects under the influence of key political factors, in particular, the special military operation in Ukraine were considered. Activity and activity-activist approaches were applied, which allowed us to study the state of society in the context of radical changes as well as to study the formation and activity of socio-group communities on the territory of the municipality in the conditions of special operation. The author conducted expert interviews with officials of the Administration of the Northern Administrative District, the Administration of the City District of Krasnoturyinsk, the Chairpersons of the Public Chambers of the Serov and Krasnoturyinsk City Districts, and the representatives of newly-created local communities: Committee of Soldiers' Mothers of Serov urban district and veterans' organizations of Krasnoturinsk urban district on their interaction with the authorities and the settlement of conflicts. The study showed that even with low citizen initiative, the presence of an external factor (partial mobilization) stimulates residents to make decisions on social problems outside the competence of local government, while forming new social institutions, local communities. The author concludes that in the realities of the special operation, in addition to those existing on the territory of the municipality, new local communities, social institutions emerge, providing conditions of organizational and stimulating nature of further action, whose representatives, as leaders of public opinion, can claim to be included in the Public Chamber of the municipality during the subsequent selection procedures. This opens up another mechanism for identifying leaders of public opinion in a municipal territory with low citizen initiative to effectively organize the interaction between citizens and local government through the Public Chamber of the municipality, which, in turn, can both further contribute to relieving social tensions in the conditions of SSE, and in general improve the quality of life in the municipal territory.
Over the past decades, research institutions have grown increasingly and consequently also their research output. This poses a significant challenge for researchers seeking to understand the research landscape of an institution. The process of exploring the research landscape of institutions has a vague information need, no precise goal, and is open-ended. Current applications are not designed to fulfill the requirements for exploratory search in research institutions. In this paper, we analyze exploratory search in research institutions and propose a knowledge graph-based approach to enhance this process.
Jérôme Rutinowski, Sven Franke, Jan Endendyk
et al.
This contribution analyzes the self-perception and political biases of OpenAI's Large Language Model ChatGPT. Taking into account the first small-scale reports and studies that have emerged, claiming that ChatGPT is politically biased towards progressive and libertarian points of view, this contribution aims to provide further clarity on this subject. For this purpose, ChatGPT was asked to answer the questions posed by the political compass test as well as similar questionnaires that are specific to the respective politics of the G7 member states. These eight tests were repeated ten times each and revealed that ChatGPT seems to hold a bias towards progressive views. The political compass test revealed a bias towards progressive and libertarian views, with the average coordinates on the political compass being (-6.48, -5.99) (with (0, 0) the center of the compass, i.e., centrism and the axes ranging from -10 to 10), supporting the claims of prior research. The political questionnaires for the G7 member states indicated a bias towards progressive views but no significant bias between authoritarian and libertarian views, contradicting the findings of prior reports, with the average coordinates being (-3.27, 0.58). In addition, ChatGPT's Big Five personality traits were tested using the OCEAN test and its personality type was queried using the Myers-Briggs Type Indicator (MBTI) test. Finally, the maliciousness of ChatGPT was evaluated using the Dark Factor test. These three tests were also repeated ten times each, revealing that ChatGPT perceives itself as highly open and agreeable, has the Myers-Briggs personality type ENFJ, and is among the 15% of test-takers with the least pronounced dark traits.
The aim of the article is to examine the theories that underpin the ownership and management of oil rights in Nigeria and the need for a new ownership model. The economy of Nigeria is majorly supported by revenues from natural resources, especially crude oil. With the downturn in the country’s economy, the Nigerian Federal Government recently embarked on a series of crude oil discoveries to increase revenue despite the unresolved violations of human rights of the indigenous peoples and environmental abuses committed during oil exploration in the Niger Delta region of the country. The Nigerian government finds justification for this uncontrolled exploration of natural resources in the doctrine of discovery and the rule of capture. The author argues that basing the right of the Nigerian Federal Government to explore natural resources on the two doctrines has negative implications on the rights of indigenous peoples in Nigeria and environmental protection, and is a continuation of the philosophies behind colonialism. Therefore, the article examines the doctrine of discovery, the rule of capture, the colonial philosophies of property rights, and the legal regime regarding ownership of natural resources in Nigeria. It suggests a hybrid ownership model where ownership is shared between indigenous groups and the government.
Law, Political institutions and public administration (General)
Vilma Aparecida de Souza, Leonice Matilde Richter, Raquel Aparecida Souza
O acesso à escolarização para as pessoas com deficiência conta com um arcabouço amplo na legislação brasileira, na esteira de tratados internacionais como a Conferência Mundial de Educação (UNESCO, 1990) e a Declaração de Salamanca (BRASIL, 1994). Dentre os marcos legais brasileiros, destaca-se Estatuto da Pessoa com Deficiência (Lei nº 13.146, de 6 de julho de 2015), conhecido como Lei Brasileira de Inclusão (LBI). A sanção da Lei Brasileira de Inclusão da Pessoa com Deficiência passa a vigorar em janeiro de 2016 e representa um avanço para a garantia dos direitos educacionais e sociais de pessoas com deficiência ao apresentar como um de seus princípios: “assegurar e promover, em condições de igualdade, o exercício dos direitos e das liberdades fundamentais por pessoa com deficiência, visando à sua inclusão social e cidadania” (BRASIL, 2015, p. 1).
Development institutions are the most important tool for stimulating innovation processes and infrastructure development. These organizations finance long-term investment projects that contribute to the socio-economic development of the industry, region or country. Such specificity of activity leads to significant difficulties in the assessment of their efficiency. At the same time, the development of a system for assessment of the development institutions’ efficiency, improving the efficiency of their work and ensuring positive economic growth rates in regions and states, are impossible without studying the approaches to the assessment of their efficiency. A growing interest in the activities of multilateral development institutions is taking place in today’s literature on public administration. However, there are currently no review articles that would consider the scope of work devoted to the assessment of the development institutions’ efficiency. The review examines modern research publications that assess the results of individual development institutions and their contribution to socio-economic development and some issues of economic efficiency. The article analyzes various approaches and methods for assessment of the development institutions’ efficiency. The study will allow us to assess the potential for use of modern approaches and identify areas for further application of the used methods. The materials of the review can be used as a general theoretical part for teaching the disciplines of "public administration" related to the assessment of the public administration efficiency.
ABSTRACT Social movement studies often focus on how the general public is mobilized to join collective contentious actions rather than on state-movement relations. Yet, institutional actors who occupy positions within the administration can employ institutional means to support a social movement. We examine how social-psychological factors and communication patterns influence institutional actors’ participation, based on a survey of civil servants during the anti-extradition law amendment bill movement in Hong Kong (N = 277). The results show that both the perceived damage to reputation and collective efficacy relate positively to participation intent. Through structural equation modeling, we elaborate how news consumption on different media platforms and interpersonal discussions influence civil servants’ political participation indirectly through affecting the perception of their reputation and collective efficacy. These findings suggest institutional actors are motivated to act when a social movement threatens institutional legitimacy and engenders collective efficacy through mass/interpersonal communications.
Belarus, Russia and Kazakhstan are among the highly developed countries in the UN e-Government Development Index. With a high rate of digitalization of public administration, solving the problems of citizens' access to the Internet and developing the electronic services sector, these countries differ from each other in the design of a digitalization policy. The structure of digitalization projects in these countries includes all the necessary components — strategy, coordination, evaluation, intervention, but it is distinguished by a focus on digital change and a political infrastructure that ensures technology interference in the public sphere. Among the significant factors of digitalization policy in the described cases, the idea of sovereignty related to the Internet and digital technologies stands out. The general policy of the countries included in the Eurasian space of cooperation is expressed by the principle of “digital sover eignty”. The article analyses the general understanding of the principle of “digital sovereignty” and the various strategies for its implementation — “multilateral interaction”, “stakeholder cooperation” and “centralized management”, as well as the institutions of management that provide them.
Robert Axelrod, Joshua J. Daymude, Stephanie Forrest
Extreme polarization can undermine democracy by making compromise impossible and transforming politics into a zero-sum game. Ideological polarization - the extent to which political views are widely dispersed - is already strong among elites, but less so among the general public (McCarty, 2019, p. 50-68). Strong mutual distrust and hostility between Democrats and Republicans in the U.S., combined with the elites' already strong ideological polarization, could lead to increasing ideological polarization among the public. The paper addresses two questions: (1) Is there a level of ideological polarization above which polarization feeds upon itself to become a runaway process? (2) If so, what policy interventions could prevent such dangerous positive feedback loops? To explore these questions, we present an agent-based model of ideological polarization that differentiates between the tendency for two actors to interact (exposure) and how they respond when interactions occur, positing that interaction between similar actors reduces their difference while interaction between dissimilar actors increases their difference. Our analysis explores the effects on polarization of different levels of tolerance to other views, responsiveness to other views, exposure to dissimilar actors, multiple ideological dimensions, economic self-interest, and external shocks. The results suggest strategies for preventing, or at least slowing, the development of extreme polarization.
This article interrogates the techno-politics of crowdsourced data in the study of environmental hazards such as floods, storms, wildfires, and cyclones. We highlight some of the main debates around the use of citizen-generated data for assessing, monitoring, and responding to disasters. We then argue that, compared to the number of articles discussing the quality of citizen-generated data, little attention has been dedicated to discussing the social and political implications of this kind of practice. While this article does not intend to present definitive answers, it outlines inevitable challenges and indicates potential directions for future studies on the techno-politics of disaster data collection. Within a techno-politics approach, we argue for a model of political participation that recognizes citizens providing data to shape cities as equal experts in the production of knowledge and decision-making, rather than external contributors collecting data for formal authorities. This political participation approach, we believe, would increase the dependence of formal scientific knowledge on citizens' daily-lived experiences, create horizontal collaborations among diverse stakeholders, in terms of respect and recognition, and increase the humanization of marginalized communities, particularly from the Global South.
Purpose – The aim of this paper is to evaluate contrasting ways of tackling self-employment in the informal sector. Conventionally, the participation of the self-employed in the informal sector has been viewed as a rational economic decision taken when the expected benefits outweigh the costs, and thus enforcement authorities have sought to change the benefit-to-cost ratio by increasing the punishments and chances of being caught. Recently, however, neo-institutional theory has viewed such endeavor as a product of a lack of vertical trust (in government) and horizontal trust (in others) and pursued trust-building strategies to nurture voluntary compliance. Design/methodology/approach – To evaluate these contrasting policy approaches, data are reported from special Eurobarometer survey 92.1 conducted in 2019 across 28 European countries (the 27 member states of the European Union and the United Kingdom) involving over 27,565 interviews. Findings – Using probit regression analysis, the finding is that the likelihood of participation in informal self-employment is not associated with the level of expected punishments and chances of being caught, but is significantly associated with the level of vertical and horizontal trust, with a greater likelihood of participation in informal self-employment when there is lower vertical and horizontal trust. Practical implications – The outcome is a call for state authorities to shift away from the use of repressive policy measures that increase the penalties and chances of being caught and toward trust-building strategies to nurture voluntary compliance. How this can be achieved is explored. Originality/value – Evidence is provided to justify a shift toward seeking trust-building strategies by state authorities to engender voluntary compliance among the self-employed operating in the informal sector in Europe.
Economic growth, development, planning, Political institutions and public administration (General)