This study examines how gendered media framing shapes public perceptions of female political leadership in Indonesia, focusing on Khofifah Indar Parawansa during the 2024 East Java gubernatorial election. Although women’s political participation has increased through affirmative action and the growing visibility of female leaders, gender stereotypes continue to influence political communication. Using Robert Entman’s framing theory and a qualitative content analysis of news reports published by Mediaindonesia.com, this research identifies the dominant frames used to portray Khofifah’s leadership. Four key frames emerged: competence, religiosity, domesticity, and personal traits. The competence and religiosity frames emphasize administrative experience, policy achievements, and moral credibility, enhancing her legitimacy as a regional leader. Conversely, the domesticity and personal traits frames highlight nurturing qualities, emotional sensitivity, and maternal identity, revealing the persistence of gendered expectations that shape interpretations of female leadership. These combined narratives demonstrate an ambivalent pattern in which media coverage simultaneously strengthens women’s political visibility while reinforcing traditional gender norms. The study contributes to discussions on gendered mediation in Southeast Asian political communication and underscores the need for more gender-sensitive reporting practices to support equitable representation in regional executive elections.

The Five-Factor Model (FFM) is the most widely used framework for understanding personality, typically assessed through self-report inventories such as the IPIP-NEO-120. Although these tools show strong psychometric properties, reliance on self-reports introduces vulnerabilities to bias, including social desirability, response distortion, and faking, particularly in high-stakes contexts like personnel selection. To address such limitations, researchers have increasingly explored behavior-oriented measures, notably Situational Judgment Tests (SJTs). When analyzed using Cognitive Diagnostic Models (CDMs), SJTs can yield multidimensional mastery profiles that offer a nuanced representation of personality. However, limited evidence exists regarding the convergence between CDM-based SJT profiles and traditional self-reports. This study applied Robust Canonical Correlation Analysis (RCCA) with a Spearman rank correlation matrix to examine structural alignment between CDM-based SJT scores and IPIP-NEO-120 domain scores in a sample of 289 participants. RCCA was chosen to handle common violations of multivariate assumptions, such as non-normality and outliers. Results showed a moderate canonical correlation in the first root, supporting convergent validity while highlighting distinct trait representations across methods. Subsequent roots yielded weaker and less stable associations. Overall, findings indicate that RCCA is a viable approach for evaluating cross-method validity and emphasize the complementary insights of situational and self-report approaches in personality assessment.

The ongoing study investigates the impact of TikTok’s “info cocoon,” an algorithm-driven feature, on the negative emotions experienced in different generations. Grounded on theories underpinning filter bubbles, “algorithmic culture,” and “generational identity,” the study investigated the implications of TikTok’s recommendation algorithm on different emotions for different generations. Applying the case study research method, an indepth investigation was made on exemplars from the following generation groups: adolescents, young people, and elderly audiences in the Western environment and mainland China ecosystem, respectively. The findings from the study made it clear that vulnerable individuals, with a particular concern for academic-related anxiety and body image, are mainly affected by political divisiveness and economic insecurity, but also senior adults who feel fear and distrust, mainly because health-related misinformation is included in sensationalised content. Of much more concern is the position played by the information cocoon in each group on TikTok: it is an amplifier for affectively rich information, thus being an element in the construction of “affective echo chambers,” in which exposure is reduced to largely negative experiences. The research argues that these implications serve only to increase intergenerational rifts in addition to trust in institutions, thereby evidencing the commoditization of emotional vulnerability in the cultural construction of digital technology.

Macao faces a critical demographic challenge with the world’s lowest total fertility rate (TFR) of 0.582 in 2024. This threatens its long-term economic and social stability. This study investigates the multifaceted causes of Macao’s ultra-low fertility, relying on systematic data from 2001–2024, international comparisons, and a thorough policy assessment. Employing a mixed-methods approach, we identify key factors including prohibitive housing costs (9.1/10), significant education expenses (8.6/10), and persistent gender role conflicts. Findings reveal a distinct four-phase fertility decline, positioning Macao below South Korea (0.750). This demographic transition has led Macao to become an aged society, with its elderly population (14.5%) now exceeding the child population (12.5%). Despite these trends, current policies demonstrate limited effectiveness. The study proposes a comprehensive six-pillar policy framework emphasizing housing reform, childcare expansion, work-life balance, financial support, gender equality, and long-term monitoring. Implementation is structured across three phases (2025-2035) to stabilize the TFR, foster recovery to 1.0, and eventually approach the replacement level. This research provides the first systematic analysis of an extreme fertility case and offers evidence-based policy recommendations for small economies facing similar challenges.

This study investigated the level of trust in artificial intelligence feedback among second language learners and its influencing factors, involving 50 undergraduate students majoring in Linguistics at a university in China. it was found that learners generally trust AI feedback, with the degree of trust influenced by language learning experience and the quality of AI tools. Learners with higher levels of trust exhibited greater frequency in using AI tools, more active learning engagement, and lower levels of anxiety. The study suggested enhancing learner trust by improving AI tool quality and developing personalised feedback mechanisms. These findings offer valuable insights for the development of AI educational tools and provide practical recommendations for second language teaching practice.

Mobilizing private capital to develop climate-resilient infrastructure requires effective government communication and cross-sector collaboration, especially in the context of developing countries with fiscal constraints. The success of local governments in enabling private investments depends on transparent communication, coherent political messaging, and alignment with corresponding stakeholders. This paper proposes a practical framework to help assess local government capacity to engage in climate-resilient infrastructure using the Public-Private Partnership (PPPs) scheme. The framework reviews three interconnected enablers: (1) fiscal communication capacity, assessed through publicly accessed financial indicators such as the Debt Service Coverage Ratio (DSCR) used in Indonesia’s availability-payment PPP regulations; (2) political coherence, as seen through legislative support and messaging from executive and legislative leaders; and (3) strategic alignment, reflected in how infrastructure goals are clearly stated in accessible development plans. This framework is applied to the Madiun Regency’s energy-efficient street lighting PPP project, implemented through a DBFMOT model. Madiun’s success stemmed from adequate communication between executive and legislative government officials, engagement with national agencies, and proper disclosure of fiscal capacity and project objectives. The project succeeded in lowering electricity costs, improving safety, and enhancing local business activities. Government guarantees provided through IIGF further strengthened risk allocation thus helping to increase investor confidence. Overall, this study highlights how strengthened communication, internal consensus-building, and aligned strategic narratives can enhance government-owned climate-infrastructure investment

Against the backdrop of deepening reforms in basic education, improving primary school students’ interest in and achievement in mathematics has become a key research topic. Traditional mathematics teaching methods, with their abstract content and monotonous format, can easily instill fear in younger students, dampen their enthusiasm, and negatively impact learning outcomes. Introducing gamification elements such as points, badges, challenges, and narratives into teaching models can stimulate student motivation and foster active participation in class. This paper, through a literature review, systematically examines the mechanisms of gamification in primary school mathematics instruction. It focuses on the impact of different gamification elements (e.g., dynamics, mechanisms, and component elements) and their combinations on mathematical achievement, and analyzes their applicability across different knowledge types, such as number and algebra, and graphs and geometry. Furthermore, this study examines individual differences in the impact of gamification on primary school mathematics achievement. This study aims to provide theoretical and practical insights for improving the design of gamification-based instruction in primary school mathematics and promote its scientific application in basic education.

As reading practices increasingly migrate into short-video environments, platforms such as TikTok and its Chinese counterpart Douyin have reconfigured how books are encountered, interpreted, and emotionally experienced. BookTok has emerged as a prominent site of this transformation, where reading is mediated primarily through audiovisual storytelling rather than direct textual engagement. Drawing on remediation theory, this study conceptualizes videolized reading as a platform-mediated reading practice in which narrative condensation, embodied performance, and algorithmic circulation jointly shape textual meaning and visibility. Using a mixed-methods comparative design, this paper analyzes BookTok content from China and abroad to examine how videolized reading operates across different cultural contexts. The findings reveal that while short-video platforms share similar technical affordances, the remediation of reading is culturally patterned. Chinese BookTok practices tend to emphasize instructional explanation and knowledge-oriented reading functions, whereas international BookTok foregrounds emotional immersion and affective performance. These differences reflect distinct cultural logics of reading that are re-articulated through videolization rather than displaced by it. By theorizing videolized reading and empirically demonstrating its culturally specific forms, this study extends research on media convergence and social reading. It argues that remediation processes in digital reading are not technologically neutral but are shaped by culturally embedded understandings of reading, emotion, and media practice.

The research investigates Indonesia’s Free Nutritious Meals (FNM) program (2025–2029) as a policy-based nation branding initiative which promotes sustainability and inclusivity and innovation through its communication efforts. The research uses qualitative methods to analyze policy documents and media content and conduct stakeholder interviews to study the FNM program’s dual role as welfare support and strategic communication tool. The research applies nation branding theories and green communication and innovative governance frameworks to identify four core brand identity elements of the program which include ecological (local sourcing and environmental education), social (community participation and empowerment), economic (local multiplier effects and digital transparency), and cultural-symbolic (values of gotong royong and national unity). The research compares Indonesia’s FNM program to international models from Finland, Japan, India and Brazil to show its position in the worldwide initiative that connects welfare services with sustainability and soft power development. The program faces reputational threats because operational problems and food contamination incidents create doubts about its ability to deliver care and demonstrate competence. The FNM program will boost Indonesia’s global reputation as a nation that cares and looks toward the future when the program receives proper management and maintains authentic communication and shows both transparency and performance consistency. This study has succeeded in providing an overview of how to convince international parties that the values contained in Indonesian culture can also be incorporated into government programs to provide welfare for its people.

With the deepening application of artificial intelligence (AI) in education, automated evaluation systems have become important aids in English writing instruction. However, disputes persist regarding their scoring accuracy, feedback effectiveness, and user experience. This paper reviews the application of AI automated evaluation systems in English writing instruction, focusing on scoring accuracy, feedback effectiveness, and user experience. Findings show that AI systems perform well in evaluating linguistic forms, demonstrating high consistency with human raters, especially in grammar and vocabulary. Nevertheless, they remain inadequate in assessing content depth, logical structure, and creativity. Regarding feedback, AI systems can enhance students’ writing proficiency if combined with scaffolded designs (e.g., model essays, checklists, multiple rounds of revision). In terms of user experience, students value the immediacy and interactivity of AI feedback but trust it less than teacher feedback on content-related aspects. The conclusion points out that AI systems should be positioned as playing an auxiliary role in formative evaluation, leverage their advantages in efficiency and personalization through human-machine collaboration, and pay attention to teacher training, system optimization, and ethical norms, so as to promote English writing instruction toward a more efficient, inclusive, and human-centered direction.