This article analyzes the implications of Russia’s invasion of Ukraine for the diversification of logistics and connectivity in Central Asia from an international political perspective. Due to its landlocked geography and structurally constrained geopolitical environment, logistics diversification constitutes a critical issue for regional actors and represents an important determinant of the foreign policy orientations of Central Asian states. The central research question addressed in this study is whether the war in Ukraine has fundamentally transformed – or has the potential to transform – the region’s existing patterns of logistical connectivity. The findings indicate that while policy-driven efforts to diversify logistics networks and promote the so-called “Middle Corridor” have intensified, these emerging routes are unlikely to replace established transit corridors in the short term. This outcome is largely attributable to the preferences and cost – benefit calculations of corporate actors, who remain the primary agents of logistics flows and exhibit limited interest in the Middle Corridor. Moreover, evidence drawn from open-source materials and field research underscores persistent structural constraints in Central Asia, particularly in terms of infrastructure, institutional capacity, and limited attractiveness for global markets and freight forwarders. Nevertheless, the activation of the Middle Corridor and broader trends toward logistics diversification appear to be advancing in a path-dependent yet increasingly irreversible manner. As such, the gradual diversification of cargo flows and its implications for the foreign economic and political relations of Central Asian states call for sustained medium- to long-term analysis.
Political institutions and public administration - Asia (Asian studies only), Social sciences and state - Asia (Asian studies only)
The Asia-Pacific remains a region of strategic importance, where nations compete for power and influence, despite rising exclusionism that undermines the international order. Unlike prevailing literature on geopolitics and security, this article examines the current dynamics and trends shaping the US–China geoeconomic competition. It also explores how Donald Trump’s tariff war would impact China’s and the Asia-Pacific’s multidimensional fields beyond the immediate economic effects on trade balance. It concludes with policy recommendations for Asia-Pacific countries to ease the geoeconomic tensions between the two superpowers.
Political institutions and public administration - Asia (Asian studies only), Political science (General)
Our infrastructure systems enable our well-being by allowing us to move, store, and transform materials and information given considerable social and environmental variation. Critically, this ability is shaped by the degree to which society invests in infrastructure, a fundamentally political question in large public systems. There, infrastructure providers are distinguished from users through political processes, such as elections, and there is considerable heterogeneity among users. Previous political economic models have not taken into account (i) dynamic infrastructures, (ii) dynamic user preferences, and (iii) alternatives to rational actor theory. Meanwhile, engineering often neglects politics. We address these gaps with a general dynamic model of shared infrastructure systems that incorporates theories from political economy, social-ecological systems, and political psychology. We use the model to develop propositions on how multiple characteristics of the political process impact the robustness of shared infrastructure systems to capacity shocks and unequal opportunity for private infrastructure investment. Under user fees, inequality decreases robustness, but taxing private infrastructure use can increase robustness if non-elites have equal political influence. Election cycle periods have a nonlinear effect where increasing them increases robustness up to a point but decreases robustness beyond that point. Further, there is a negative relationship between the ideological sensitivity of candidates and robustness. Overall, the biases of voters and candidates (whether they favor tax increases or decreases) mediate these political-economic effects on robustness because biases may or may not match the reality of system needs (whether system recovery requires tax increases).
The 2008 global financial crisis marked the beginning of a decade dominated by fiscal austerity policies in much of the developed world. This paper presents a qualitative narrative review of an extensive collection of academic literature to synthesize evidence on the multifaceted effects of austerity. Following a thematic approach inspired by PRISMA guidelines, the economic, social, and political consequences of these measures are examined. The analysis reveals a majority consensus regarding the recessive effects of austerity, especially when implemented during economic crises, with negative fiscal multipliers that often exacerbate GDP contraction. Socially, austerity is associated with rising inequality, negative impacts on public health, disproportionate gender consequences, and a weakening of social safety nets. Politically, evidence links austerity to the erosion of trust in institutions, a rise in populism, and electoral instability. Despite the political narrative presenting austerity as an inevitable necessity for fiscal sustainability, academic literature underscores its high costs and questionable efficacy, advocating for more contextualized and equitable economic policy approaches.
Engaging in political discussions is crucial in democratic societies, yet many individuals remain politically disinclined due to various factors such as perceived knowledge gaps, conflict avoidance, or a sense of disconnection from the political system. In this paper, we explore the potential of personal narratives-short, first-person accounts emphasizing personal experiences-as a means to empower these individuals to participate in online political discussions. Using a text classifier that identifies personal narratives, we conducted a large-scale computational analysis to evaluate the relationship between the use of personal narratives and participation in political discussions on Reddit. We find that politically disinclined individuals (PDIs) are more likely to use personal narratives than more politically active users. Personal narratives are more likely to attract and retain politically disinclined individuals in political discussions than other comments. Importantly, personal narratives posted by politically disinclined individuals are received more positively than their other comments in political communities. These results emphasize the value of personal narratives in promoting inclusive political discourse.
Public policy shapes the economic landscape, influencing everything from corporate behavior to individual investment decisions. For Environmental, Social, and Governance (ESG) investors, these policy shifts can create opportunities and challenges as they navigate an ever-changing regulatory environment. The contrast between the Trump and Biden administrations offers a striking example of how differing political agendas can affect ESG investments. Trump's first term was marked by deregulation and policies favoring fossil fuels, which created an uncertain environment for sustainable investments. When Biden assumed office, his focus on climate action and clean energy reinvigorated the ESG sector, offering a more stable and supportive landscape for green investments. However, with Trump's return to power in his second term, these policies are being reversed again, leading to further volatility. This paper explores how such dramatic shifts in public policy influence economic strategies and directly impact ESG investors' decisions, forcing them to constantly reassess their portfolios in response to changing political climates.
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.
We present closed analytical approximations for the pricing of Asian basket spread options under the Black-Scholes model. The formulae are obtained by using a stochastic Taylor expansion around a log-normal proxy model and are found to be highly accurate for Asian and spread options in practice. Unlike other approaches, they do not require any numerical integration or root solving.
The review was devoted to the monograph by E. A. Gunaev (Kalmyk Scientific Center of the Russian Academy of Sciences) “National Autonomies of the South of Russia in the Soviet period: Territorial Structure and Management System (on the example of Kalmykia)” (Elista: KalmSC RAS, 2022. 400 p.). The monograph was written on the basis of a wide range of sources and literature, including 30 files from 6 funds of 3 state archives, 425 publications of documents and research. E.A. Gunaev identified three stages in changing the administrative-territorial structure and management system in the national autonomies of the South of Russia: 1920–1943, 1944–1976, 1977–1991. Each stage is presented in a separate chapter of the monograph. The author proposed a historical and legal analysis of the problems under consideration with an emphasis on the study of regulatory aspects. Of significant interest is the study of the problem of legal succession between national autonomies, recreated after the rehabilitation of repressed peoples, and their national-state formations before forced eviction. E.A. Gunaev distinguishes between the categories of continuity, legal continuity and succession, and analyzes the possibilities of their use within the framework of the issue under consideration.
History of Asia, Political institutions and public administration - Asia (Asian studies only)
Violence-provoking speech -- speech that implicitly or explicitly promotes violence against the members of the targeted community, contributed to a massive surge in anti-Asian crimes during the pandemic. While previous works have characterized and built tools for detecting other forms of harmful speech, like fear speech and hate speech, our work takes a community-centric approach to studying anti-Asian violence-provoking speech. Using data from ~420k Twitter posts spanning a 3-year duration (January 1, 2020 to February 1, 2023), we develop a codebook to characterize anti-Asian violence-provoking speech and collect a community-crowdsourced dataset to facilitate its large-scale detection using state-of-the-art classifiers. We contrast the capabilities of natural language processing classifiers, ranging from BERT-based to LLM-based classifiers, in detecting violence-provoking speech with their capabilities to detect anti-Asian hateful speech. In contrast to prior work that has demonstrated the effectiveness of such classifiers in detecting hateful speech ($F_1 = 0.89$), our work shows that accurate and reliable detection of violence-provoking speech is a challenging task ($F_1 = 0.69$). We discuss the implications of our findings, particularly the need for proactive interventions to support Asian communities during public health crises. The resources related to the study are available at https://claws-lab.github.io/violence-provoking-speech/.
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/.
This study seeks to identify and quantify biases in simulating political samples with Large Language Models, specifically focusing on vote choice and public opinion. Using the GPT-3.5-Turbo model, we leverage data from the American National Election Studies, German Longitudinal Election Study, Zuobiao Dataset, and China Family Panel Studies to simulate voting behaviors and public opinions. This methodology enables us to examine three types of representation bias: disparities based on the the country's language, demographic groups, and political regime types. The findings reveal that simulation performance is generally better for vote choice than for public opinions, more accurate in English-speaking countries, more effective in bipartisan systems than in multi-partisan systems, and stronger in democratic settings than in authoritarian regimes. These results contribute to enhancing our understanding and developing strategies to mitigate biases in AI applications within the field of computational social science.
Large language models have exhibited significant proficiency in languages endowed with extensive linguistic resources, such as English and Chinese. Nevertheless, their effectiveness notably diminishes when applied to languages characterized by limited linguistic resources, particularly within the Southeast Asian linguistic landscape, such as Indonesian. The scarcity of linguistic resources for these languages presents challenges associated with inadequate training, restricted vocabulary coverage, and challenging evaluation processes. In response to these exigencies, we have introduced CompassLLM, a large multilingual model specifically tailored for Southeast Asian languages, with the primary aim of supporting the developmental requirements of Shopee. Our methodology encompasses several key strategies. To progressively enhance multilingual proficiencies, we implemented a multi-stage pre-training strategy integrated with curriculum learning, gradually intensifying the focus on low-resource languages. Concurrently, to better accommodate low-resource human instructions, we curated and generated a repository of high-quality multilingual human instructions, culminating the CompassLLM-SFT model through supervised instruction fine-tuning. Finally, to reinforce the model's alignment with human preference behaviors, we have embraced the principle of Direct Preference Optimization (DPO) to obtain CompassLLM-DPO model. Preliminary evaluation of the CompassLLM model yields promising results, with our model surpassing benchmark models like Vicuna-7b-v1.5, Sealion, Falcon and SeaLLM, across diverse evaluation tasks, as verified through both automated and human-driven assessments. Notably, our model exhibits its superior performance in South-east Asia languages, such as Indonesian language.
Recently, there has been significant attention on online political incivility. While previous research suggests that uncivil political comments lead people to be less willing to see more comments on the same issue, two critical questions have received limited exploration: (1) Are people exposed to uncivil political comments less willing to see other comments from the person who posted the uncivil comment?; (2) Are people exposed to uncivil political comments less willing to see comments from people who have different thoughts than them? To address these questions, the present study conducted a preregistered online survey experiment targeting Japanese citizens, focusing on the pro- vs anti-Kishida cabinet conflict in Japan. The results show that the participants were less willing to see other comments by the person who posted the comment when the comment was uncivil than when it was civil. In addition, the anti-Kishida participants were less willing to see political opinions posted online by people who have different thoughts than them when the comment was uncivil than when it was civil, while the participants in the other subgroups did not show a similar tendency. These findings suggest that uncivil expressions in online political communication might prompt people to avoid reading opinions from those who have different thoughts than them, which might promote political echo chambers.
Public administration is the largest part of the democratic state and a key consideration in understanding its legitimacy. Despite this, democratic theory is notoriously quiet about public administration. One exception is deliberative systems theories, which have recognized the importance of public administration and attempted to incorporate it within their orbit. This article examines how deliberative systems approaches have represented (a) the actors and institutions of public administration, (b) its mode of coordination, (c) its key legitimacy functions, (d) its legitimacy relationships, and (e) the possibilities for deliberative intervention. It argues that constructing public administration through the pre-existing conceptual categories of deliberative democracy, largely developed to explain the legitimacy of law-making, has led to some significant omissions and misunderstandings. The article redresses these issues by providing an expanded conceptualization of public administration, connected to the core concerns of deliberative and other democratic theories with democratic legitimacy and democratic reform.
Dalam beberapa esainya, Benedict Anderson menyebut politik Indonesia terbentuk oleh cara berpikir Jawa. Hal ini ditandai bagaimana politik Indonesia yang sangat jawa-sentris dalam pelaku politik, cara bermain, bahkan penggunaan bahasa panggung politik. Dan wayang mendapatkan peran penting dalam menentukan peta politik jawa yang kemudian berimplikasi pada gimik politik negeri ini.. Wayang adalah jagad kompleks untuk mendedah sekian idealitas dan realitas hidup manusia. Politik menjadi bab primer dalam wayang dengan pelbagai tafsir dan realisasi. Wayang itu politik. Pembacaan dan penafsiran atas wayang dalam ranah politik memang kerap mengejutkan tapi itu kelumrahan dalam biografi politik Indonesia.
Political institutions and public administration - Asia (Asian studies only)
We explore the understudied area of social payments to evaluate whether or not we can predict the gender and political affiliation of Venmo users based on the content of their Venmo transactions. Latent attribute detection has been successfully applied in the domain of studying social media. However, there remains a dearth of previous work using data other than Twitter. There is also a continued need for studies which explore mobile payments spaces like Venmo, which remain understudied due to the lack of data access. We hypothesize that using methods similar to latent attribute analysis with Twitter data, machine learning algorithms will be able to predict gender and political affiliation of Venmo users with a moderate degree of accuracy. We collected crowdsourced training data that correlates participants' political views with their public Venmo transaction history through the paid Prolific service. Additionally, we collected 21 million public Venmo transactions from recently active users to use for gender classification. We then ran the collected data through a TF-IDF vectorizer and used that to train a support vector machine (SVM). After hyperparameter training and additional feature engineering, we were able to predict user's gender with a high level of accuracy (.91) and had modest success predicting user's political orientation (.63).
The main goal of the upcoming research is to analyze and read a piece of the history of "dominance and change" in Iran in the two decades of 1340 and 1350 AD, which in practice can be said to be a representation or a comprehensive mirror of the totality of state-society relations in the history of Iran. It is contemporary. Investigating the capacity of enforcing “Social control” and finally the ability and will of "social transformation" and the obstacles facing it, based on the theory of “limited State” or government within society" Jul. S. Migdal, is at the center of the discussion of this article. According to Migdal, in order to have a correct and accurate understanding of the government in the third world, one must avoid the transcendental approach and the myth of the "perfect" government desired by the statists, which puts the government in front of the society and is based on the algebraic zero-sum game between the government and society is, he avoided and paid attention to the approach of the government is a part or a piece of society. In clearer words, this view requires changing the focus of analysis from the government as an independent bureaucratic organization (structural view) to a "process oriented" view of the government in society. With this description, the main question of the research is why the politics of Mohammadreza Shah Pahlavi's social transformation in the form of the White Revolution (in the 40's and 50's) did not reach the desired result and finally the second Pahlavi faced a crisis of dominance? The findings of the research show that despite having a relatively high level of social control, the second Pahlavi government could not provide a more attractive and efficient survival strategy for the social forces and the necessary resources to support to mobilize the desired social transformation policy, therefore, it inevitably turned to the survival policy.
Political institutions and public administration (General), Political institutions and public administration - Asia (Asian studies only)
Improving the quality of public services is the responsibility of the government toward stakeholders to create an effective, efficient, and accountable service product. The purpose of this study was to determine the implementation of public services in The Population and Civil Registration Agency (Dinas Kependudukan dan Catatan Sipil – Disdukcapil) of Bandung City, measure the level of public satisfaction with the quality of public services and provide suggestions to improve the quality of public services in the Disdukcapil Bandung. The research method used is a mixed approach /methods with questionnaires, interviews, and documentation studyies as data collection techniques and accidental sampling as sampling technique. Data was analysed using Structural Equation Modeling (SEM) based on Partial Least Square (PLS) for quantitative approach, and qualitatively using Miles and Huberman. The results showed that the quality of public services on public satisfaction in Disdukcapil Bandung was good. This study gave suggestion to improve three aspects, i.e. service time, human resource competency, and the management of complaint handling. The study proposed Disdukcapil to create an integrated one-stop service to overcome the massive queues, that often occur and gave intensive training to improve human resources quality, especially in the service department.
Political institutions and public administration - Asia (Asian studies only)
This study aims to determine the impact of household waste management policies at the Panipahan Rokan Hilir port and the role of the Environmental Service in handling household waste in Rokan Hilir. The data analysis used is a qualitative descriptive analysis recommended by Miles and Huberman: Data Reduction, Presentation of Data, and Summarizing and Verification of Results. Data collection techniques include observations, interviews (structured and in-depth with informants), and documentation. The results of the research show that the Evaluation of Policy Impacts in Household Waste Management in a Case Study of Marine Pollution at Panipahan Rokan Hilir Port With the Theory of Policy Impacts, that are: Household Waste Management Policy (Case Study of Pollution at the Panipahan Rokan Hilir Port, it does not have an individual impact on the Panipahan community, both psychological impacts, environmental impacts, economic impacts, and social and personal impacts. No effect on the community in Panipahan, Rokan Hilir Regency, and has not had an impact on social institutions and systems in Panipahan, Rokan Hilir Regency. have done the Task. Its function is from Environmental Pollution Prevention Services and Management of Household Waste and similar Household Wastes quite well. However, it is still not optimal, and this can be seen from the existence of Pollution in the Panipahan Sea due to household waste and similar types of household waste.
Political institutions and public administration - Asia (Asian studies only)