Redfame Publishing: E-Journals
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Utilising Facebook as a Digital Tool for Social Change: Jordanian Women’s Experiences in Addressing Violence Against Women
Full text linkFacebook remains a dominant platform for civic engagement, public discourse, and social activism across the Arab world. In Jordan, where entrenched cultural norms and societal expectations often restrict women’s ability to voice experiences of gender-based violence (GBV), Facebook has emerged as a critical digital space for resistance and social transformation. It enables women to share personal narratives, foster solidarity, and challenge patriarchal silence. Despite its significance, limited scholarly attention has been devoted to Facebook’s role in addressing GBV within the Jordanian context. This study examines how Jordanian women utilise Facebook to promote social change and resist gender-based violence. Employing a qualitative approach, the research draws on face-to-face interviews with six purposively selected participants, supplemented by secondary data from academic literature and policy documents. Thematic analysis, guided by Social Mobilisation Theory, revealed that Facebook serves as a safe space for storytelling, emotional resilience, and collective mobilisation. It contributes to individual empowerment, enhances public awareness, and supports advocacy efforts to challenge patriarchal norms and promote institutional responsiveness. Nonetheless, structural impediments, including economic constraints, social stigma, and institutional inertia, continue to limit the full potential of digital activism. This study highlights the importance of improving digital literacy, developing context-sensitive online protection mechanisms, and fostering strategic partnerships between civil society organisations and social media platforms. These insights help policymakers, activists, and scholars understand the impact of digital platforms in conservative societies. Future research should examine the link between online and offline activism across Arab contexts
Modeling Reserve-Currency Attrition: A Bayesian Neural Framework for U.S. Dollar Reserve Holdings
No full textThis study develops a hybrid Bayesian modeling framework to estimate the probability of large-scale foreign divestment from U.S. Treasury securities and to assess the stability of the U.S. dollar’s reserve-currency status. The model integrates a Mixture Density Network (MDN) with Hamiltonian Monte Carlo (HMC) sampling to approximate the conditional distribution of reserve holdings given observed macroeconomic fundamentals and an inferred latent variable representing geopolitical alignment. Principal component analysis and hierarchical regularization are applied to ensure parsimony and mitigate overfitting in a small-sample environment. The empirical hazard rate is defined as the annual probability of a 10 percent contraction in foreign U.S. Treasury holdings—a threshold consistent with historical reserve reallocations during the sterling’s decline and central-bank portfolio adjustment behavior. Results indicate an estimated 6–12 percent annual probability at a 95 percent confidence interval, implying that a 10 percent drawdown could occur roughly once every 8–16 years under current macro-financial conditions. While Gaussian mixture components likely understate extreme tail risks, the findings highlight the resilience of U.S. reserve status and suggest that any future transition would be gradual, multi-decade, and contingent on structural geopolitical realignments rather than cyclical shocks
Coding Cultural Capital: A Sociolinguistic Analysis of Indonesian Regional Dialects and Audience Engagement on TikTok
Full text linkThis study investigates how Indonesian regional dialects function as digital capital in the TikTok cultural communication ecosystem. Using a multi-case study approach with an exploratory design, we analyzed five TikTok videos from creators representing four major Indonesian dialects: Sundanese, Batak Medan, Minangkabau, and Javanese. Data collection included quantitative engagement metrics (views, likes, comments, shares, engagement rate) and qualitative linguistic analysis through full transcription and dialect coding. The research employed descriptive analysis, comparative cross-case analysis, qualitative content analysis, and digital ethnography. The results revealed significant findings: (1) dialect variation manifests strategically across lexical, phonological, syntactic, and pragmatic dimensions, with creators adapting usage for specific communicative purposes; (2) an exploratory correlation analysis (r=0.64) suggests a tentative positive trend between dialect intensity and engagement levels, although these findings are interpreted as indicative rather than confirmatory due to the limited sample size; (3) creators employ a variety of communication strategies-nostalgia, humor, education, promotion, and call-to-action-by integrating dialect variations to maximize cultural resonance; (4) cultural values dominate the lexical distribution (frequency=15, priority score=75), indicating the centrality of cultural themes in communication strategies. This study shows that regional dialects serve as symbolic capital in the digital space, enhancing emotional connection and cultural identity while creating an engagement paradox: authentic cultural content attracts higher levels of interaction despite its lower reach. The findings contribute to digital sociolinguistic theory and provide practical insights for language policy, content creation, and cultural preservation initiatives in the digital age
Framing the Chinese Government during the COVID-19 Pandemic: A Comparative Analysis of BBC and CNN’s Digital Video News Coverage
Full text linkThis study examines how BBC and CNN portrayed the Chinese government in COVID-19 digital video news. Using quantitative content analysis, 724 videos published between December 2019 and December 2020 (BBC = 189; CNN = 535) were coded for tone (positive/neutral/negative) and five generic news frames (responsibility, conflict, human interest, economic consequences, morality). Two trained coders double-coded 20% of the sample (Cohen’s κ = 0.85). Results show that both outlets overwhelmingly relied on the responsibility frame (BBC: 91.5%; CNN: 90.4%). BBC used human-interest framing more frequently (41.1%) than CNN (6.5%), whereas CNN employed economic consequences framing more often (9.5%). Tone was predominantly neutral in both outlets (BBC: 69.84%; CNN: 73.46%), with moderate negative coverage and minimal positive portrayals. A chi-square test indicated no significant difference in tone distribution between BBC and CNN (χ²(2, N = 724) = 2.290, p = .318). The findings suggest convergent accountability-centered framing of China’s pandemic response in Western digital video news
Professional Learning Communities and Classroom Management Practices: Evidence from the Implementation of the Standards-Based Curriculum
No full textThis study examined the influence of Professional Learning Communities (PLCs) on teachers’ classroom management practices within the context of implementing the Standards-Based Curriculum (SBC). A quantitative research approach was adopted, using a descriptive cross-sectional design. The population comprised 293 senior high school teachers from which a sample of 233 were selected using a multi-stage sampling technique. Data were collected using a structured questionnaire and analysed with partial least squares structural equation modelling (PLS-SEM) using smartPLS. The results revealed that continuous improvement had a statistically significant positive effect on classroom management practices, whereas shared mission, vision, values and goals, collaboration, collective inquiry, action orientation, and results orientation did not significantly predict classroom management. The study concluded that PLCs enhance classroom management when grounded in continuous professional growth rather than episodic collaboration. It is recommended that school leaders and policymakers should prioritise structured, reflective and improvement-focused PLC practices to support teachers’ classroom management under the SBC
AI Adoption, Ethical Software Testing, and Academic Research Excellence in State-Owned Universities in Delta State
No full textThis study investigated the effect of AI adoption, ethical software testing, and academic research excellence in four (4) state-owned universities in Delta State: Delta State University, Abraka; Southern Delta University, Ozoro; Dennis Osadebay University, and University of Delta, Agbor using the multi-stage sampling technique. Data were collected through a structured questionnaire designed in line with the study objectives. Meanwhile, both descriptive and inferential statistics were employed for data analysis. A total of 180 respondents were drawn from the sampled universities. However, 165 copies of questionnaire were filled properly. The study reported that, ChatGPT and Quillbot were the most regularly used AI tools. Again, paraphrasing/theft through paraphrasing, data falsification, conflict of authorship, data privacy breaches and algorithmic bias are the key ethical issues impending AI usage and ethical software testing. Additionally, ethical awareness (β = 0.416, t-value=6.721, and p=0.000) is the strongest ethical AI tool testing predictor, next to institutional policies (β = 0.339, t-value= 5.840 and p-value=0.000) and access to AI training (β = 0.270, t-value= 0.270 and p-value =0.000). Lastly, the result affirmed that junior (graduate assistant and assistant lecturers) and mid-level academic staff (lecturer 11 and lecturer 1) are more willing to use AI tools in research activities than upper level academic staff (Senior lecturer to Professors). Thus, the study concludes that strict adherence to ethical standards and software testing protocols are essential for achieving academic excellence. Consequently, Nigerian university managements and the National Universities Commission (NUC) need to develop clear, concise, and African context-specific institutional policies and structured ethical software testing frameworks targeted at validating AI solution before deployment and at the same time provide rank-sensitive training programs for all academic staff
Use of Innovative Educational Technologies Based on Artificial Intelligence to Train Specialists in Higher Education Institutions for the Implementation of Sustainable Development Goals
No full textIn view of comprehensive access to information and the expansion of the impact of artificial intelligence (AI), there is a need for a deep rethinking of the role of higher education in achieving the sustainable development goals (SDGs) of humanity. The aim of the study is to determine the impact of innovative AI-based educational technologies on the development of key competencies for sustainable development in higher school students. The study employed empirical research methods. The content analysis using the MeetGeek tool revealed the teachers’ key concerns related to the use of AI in educational activities. The survey assessed the impact of AI tools on the quality of the educational process and the development of key sustainability competencies. Case analysis contributed to the identification and systematization of effective pedagogical approaches. Statistical analysis provided comprehensive processing and interpretation of the obtained data. A total of 217 teachers of the humanities of higher education institutions (HEIs) of Ukraine participated in the survey. The results showed that AI-based educational technologies contribute to improving the quality of learning. The respondents highlighted the interactivity, flexibility, and practical orientation of learning using AI tools as key advantages of their integration into the educational process. Of them, 68.1% of teachers agreed that AI-assisted learning promotes the development of key sustainability competencies. Critical thinking (78.7%), Systems Thinking (75.5%), and the Integrated Problem-Solving (72.7%) are most affected. Anticipatory Thinking (69.1%), Strategic Thinking (66.4%), and Collaborative Ability (64.0%) are moderately affected. The student’s value orientation (60.8%), self-awareness and reflexivity (57.5%) are least affected. The results of the study showed that AI-based educational practices should be organized using scientifically based methods of developing thinking and innovative pedagogical approaches. Special emphasis should be placed on the implementation of continuous problem-oriented project-based learning approaches that support the principles of sustainable development, ethical, socially oriented and critical thinking
Industrial Policy and Effective Availability in Strategic Supply Chains: Empirical Evidence from Semiconductor Trade
No full textStrategic supply chains have become a central concern for economic policy as geopolitical fragmentation, export controls, and industrial subsidies reshape global trade. This study evaluates how recent U.S. trade and industrial policies have affected the effective availability of semiconductor inputs—a critical determinant of productivity, innovation, and economic resilience. Using detailed bilateral trade data from UN Comtrade (2020–2024), the paper constructs a CES-based import aggregator that adjusts observed trade flows for tariffs, export controls, and geopolitical risk. The empirical results show that while nominal semiconductor imports recovered after the pandemic, policy-adjusted effective availability experienced significant volatility following the introduction of import controls and targeted tariffs. Dependence on East Asian suppliers—particularly Japan, South Korea, and the Netherlands—remains structurally high, especially for advanced equipment and lithography inputs. However, diversification toward allied and regional partners partially offset policy-induced access constraints by 2024. The findings highlight three applied insights. First, industrial policy can stabilize supply access without full reshoring when substitution elasticities are sufficiently high. Second, targeted restrictions impose short-run costs on effective availability but may accelerate long-run diversification. Third, resilience depends more on supplier substitutability and policy coordination than on import volume alone. These results inform ongoing debates on industrial policy effectiveness, strategic trade management, and supply-chain resilience in advanced and emerging economies
Artificial Intelligence Adoption Drivers and Accounting and Banking and Finance Students’ Performance in Dennis Osadebay University, Nigeria
No full textThe emergence of artificial intelligence (AI) has transformed the educational sector globally. However, most Nigerian Universities are yet to fully integrate AI into their curriculum. Succinctly, this research examines the effect of five key AI adoption drivers on accounting and finance students’ performance. Emphasis was placed on the extent to which app intuitiveness, peer group pressure, institutional leadership readiness, external support, and student adaptability influence accounting and finance students’ performance. The study surveyed 390 male and female accounting and banking and finance students at Dennis Osadebay University, Asaba. This study adopts a quantitative research design. The drafted questionnaire was given to two (2) accounting and finance experts to review using the Index of Item-Objective Congruence (IOC) method. Meanwhile, a pilot test with 40 accounting and finance students confirmed that the survey instrument is reliable. The data were analysed by using Structural Equation Modelling (SEM). The findings indicate that peer group pressure, institutional readiness, and student adaptability significantly influence AI adoption, while app intuitiveness and external support do not. In like manner, AI adoption strongly affects the performance of accounting and banking and finance students. This study provides valuable insights that can drive policy formulation in the global university system. Also, the study provide rich insight on how ethical usage of AI can be achieved in the Nigerian context by emphasising the roles of peer group pressure, institutional readiness, and student adaptability in improving students ‘academic performance
Mapping the Landscape of Sociocultural Factors on English Learning (2020-2024)
No full textBackground: In recent years, English language education has increasingly shifted from cognitive-oriented paradigms to socially situated and culturally mediated perspectives grounded in Vygotsky’s Sociocultural Theory (SCT). This framework emphasizes interaction, mediation, identity negotiation, and collaborative meaning-making as core mechanisms of language learning. While sociocultural research in English education has expanded rapidly, a systematic bibliometric synthesis focusing specifically on undergraduate English language learning remains limited.Purpose: This bibliometric analysis aims to map and analyze global research trends on the sociocultural impact on undergraduates’ English language learning between 2020 and 2024, identifying intellectual structures, key contributors, and emerging thematic directions, thereby offering a clearer understanding of the field’s development and informing future research and practice.Materials and Methods: This bibliometric analysis was conducted using the Dimensions AI database, focusing on articles published between 2020 and 2024. Following PRISMA guidelines, 352 open-access, peer-reviewed articles were selected using the keywords “Sociocultural” and “English study”. Data were analyzed through performance analysis, bibliographic coupling and co-occurrence keyword mapping in VOSviewer to uncover conceptual linkages and thematic clusters including top authors, influential documents, prominent sources, and emerging thematic clusters.Results: Findings indicate a steady growth of publications and citations during the 2020-2024 period, reflecting the expanding influence of sociocultural perspectives in English language education. Three major thematic clusters emerged: (1) Sociocultural Agency and Identity Construction, emphasizing multilingual identity, learner agency, and contextual negotiation; (2) Pedagogical Innovation and Cultural Interaction, focusing on interaction, development, digital mediation, and culturally responsive teaching; and (3) Global Perspectives on Linguistic Diversity, addressing English as a lingua franca, cross-cultural communication, and internationalized English learning environments. Leading contributors included the United Kingdom, China, and the United States, demonstrating strong cross-regional engagement.Conclusion: The results collectively signify a shift in pedagogical paradigms ranging from traditional cognitive frameworks to sociocultural embedded approaches that foreground learner participation, collaborative meaning-making, and cultural mediation. By mapping these developments, the study provides conceptual and empirical foundations for advancing future research, innovative curriculum design, and informed policy formulation, establishing sociocultural perspectives as a cornerstone of contemporary English language education