Hate speech in higher education institutions is a pressing issue that threatens democratic values and social cohesion. This research explores student perspectives on hate speech within the university setting, examining its forms, causes, and impacts on democratic principles such as freedom of expression and inclusivity. This research is extended to determine the debates and theories elaborated from different perspectives qualitative and quantitative analysis of data collected from 108 participants at Higher Education in Kosovo. From the communication standpoint, analyzing hate speech in the media and social media is key to understanding the type of message used, its emitter, how the message rallies supporters, and how they interpret message. The findings highlight the need for proactive policies and educational interventions to mitigate Research on hate speech in higher education in Kosovo is crucial for fostering social cohesion and inclusivity in its diverse society. Hate speech undermines the academic environment, negatively affecting students' mental health, learning outcomes, and overall well-being, necessitating efforts to create safer educational spaces. The study aligns with Kosovo's aspirations for European integration, emphasizing adherence to human rights and anti-discrimination principles. Despite the issue's significance, there is a lack of empirical data on hate speech in Kosovo's higher education, making this research vital for evidence-based policymaking. With a youth-centric focus, the study aims to educate and empower young people as future leaders to embrace respect and inclusivity. By addressing hate speech's local challenges and global relevance, the research supports institutional reforms and offers valuable insights for post-conflict and multicultural societies. Hate speech while fostering a culture of mutual respect and democratic engagement.

This study aimed to examine the impact of Environmental, Social, and Corporate Governance (ESG) scores and Country Governance Indicators (CGI) on companies’ value. The study procedures were carried out by creating a linear empirical model where the dependent variable was companies’ value. In addition, the variables of interest in the model were ESG scores and CGI. Analysis was carried out on annual data from 278 non-financial Asian companies spanning 11 years from 2011–2021. The feasible generalized least squares (FGLS) method was used for estimation due to the presence of serial correlation and heteroscedasticity in the data obtained. The results showed the presence of a positive relationship and correlation between ESG scores and companies’ value. Meanwhile, CGI had a negative impact, revealing the potential difficulties caused by country governance framework. This study also found a positive correlation between CGI and ESG on company value. These findings have important practical contributions emphasizing the significance of ESG factors in improving companies’ value and the complex relationship between country governance and corporate valuation.

The article is devoted to the issues of political and legal regulation of climate adaptation in the regions of the Russian Federation. Against the background of the adopted federal national adaptation plan, regions are tasked with identifying key areas of activity taking into account natural-climatic, demographic, environmental and technological specifics. The authors focus on the similarities and differences of the presented adaptation plans, emphasizing that work to improve this system continues within the framework of Russia’s international obligations. The Arctic regions deserve special attention, as they also differ from each other both in the selected climate adaptation activities (from ecology to energy saving) and in their number. This review provides a clear picture of how the federal ecological system can develop.

Managing the spread of “disinformation” is becoming an increasingly difficult task of our time, with an emphasis on digital marketing and its influence on organizational reputation. This paper aims to analyze the phenomenon of disinformation, with emphasis on the role of digital marketing and the consequent effect on organizational image. Thus, using the systematic literature review methodology, the study defines and categorizes different types of disinformation, namely fake news, misinformation, and propaganda, and how they are spread across different channels. Using the research, it is possible to conclude that digital marketing is more effective in spreading disinformation than traditional media and word-of-mouth; social media management and content marketing are the most effective. The work also evaluates the catastrophic impact of disinformation on an organization’s image, fiscal health, and the trust of its stakeholders. Using the Chi-Square Test for Independence and Logistic Regression, the study determines the factors likely to lead to severe consequences of disinformation campaigns. Last but not least, the paper also suggests ways of preventing the spread of disinformation, which include improved education on the use of digital platforms, better fact-checking systems, and an improved code of ethics in digital marketing.

The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.

This research investigates the relationship between the variables of public service reform (PSR) and bureaucratic revitalization and the relationship between digital leadership (DL) and bureaucratic revitalization. The research method used in this research is quantitative survey research which aims to determine the relationship between two or more variables. The research method for this research is quantitative associative, the population of this study is senior immigration officers. The data analysis method uses structural equation modeling (SEM) partial least squares (PLS), the respondents for this study were 634 senior immigration office employees who were determined using the simple random sampling method—non probability sampling, the questionnaire was designed to contain statement items using a 7 point Likert scale. A closed questionnaire is a list of questions or statements that are equipped with multiple answer choices expressed in scale form. The Likert scale used in this research is (1) strongly disagree, (2) disagree, (3) quite disagree, (4) neutral, (5) quite agree, (6) agree, (7) strongly agree. Data processing in this research used SmartPLS software. The independent variables of this research are digital leadership and public service reform and the dependent variable is bureaucratic revitalization. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research show that public service reform has a positive and significant relationship to bureaucratic revitalization and digital leadership has a positive and significant relationship to bureaucratic revitalization. This research implies that leaders focus on engaging, using, and handling the uncertainty of emerging technologies, digital tools, and data, leaders to support bureaucratic revitalization, the immigration department must implement digital leadership, immigration leaders should encourage the use of digital platforms in their organizations, support and facilitate digital transformation. The immigration department should increase the revitalization of the bureaucracy, the immigration department should carry out public service reforms. Public services are to be good if they fulfill several principles of public interest, legal certainty, equal rights, balance of rights and obligations, professionalism, participativeness, equality of treatment/non-discrimination, openness, accountability, facilities and special treatment for vulnerable groups, timeliness, speed, convenience and affordability.