Africa has been fighting against colonialism and Eurocentrism for a long time in an attempt to reverse the regime of oppression and socio-economic marginalization and exploitation, and take back control of its cultural identity and right to self-determination. This adventure requires the recognition and revitalisation of indigenous arts, culture, and law—all of which have been subjugated and ignored during colonial rule. Ironically, the situation has not improved much by the dominating presence of post-independent neo-colonial structures and perpetuated Eurocentric phenomenon that have been ingrained into the socio-cultural and economic fabrics of the African state. This research explores the critical need for integrating science on African indigenous arts, culture, and legal systems, as a way of globalizing as well as revitalizing these elements, towards the ultimate emancipation of the continent from the vestiges of colonialism and Eurocentricism. Relying on the postcolonial, and indigenous knowledge systems theoretical frameworks, the study engages the ethnographic, collaborative and interdisciplinary research approaches, subjecting data obtained to thematic analysis. Underscoring the profound interconnectedness of science, indigenous arts, and cultural heritage, the study argues that combining scientific methods with indigenous African epistemology provides a powerful framework for advancing Africa’s true independence from the protracted legacies of colonialism and Eurocentrism. The research concludes that a holistic integration of these elements therefore, is indispensable for fostering a decolonized and inclusive approach to knowledge production, self-determination and sustainable development, against the background of the rich insights and sustainable practices embedded within the African cultural traditions. Ultimately, the research recommends that embracing and integrating science on indigenous epistemologies can propel Africa towards an emancipated, truly independent, and culturally affirming future, transcending the enduring legacies of colonialism and Eurocentrism.
This paper models 54,559 Chinese news items about education industry and scientific industry by machine learning during the COVID-19 epidemic to build China’s increased scientific research policy (ISRP) index. The result of interrupted time series analysis indicates that, the ISRP has an emphatic positive causality on the education industry advancement and promotes the development of the education industry. The ISRP also has a remarkable positive causality on the development of the scientific industry. Moreover, the result of causal network indicates that, a virtuous circle within the ISRP, the education industry and the scientific industry has been formed, which has promoted the sustainable development of the education chain.
The purpose of the study is to create proposals and recommendations to improve the system evaluating the quality of governance and efficient use of budget funds in order to improve public welfare and sustainable development. The research methodology included application of statistical methods to review scientific articles, legislative acts and other documents, study models for evaluating the quality of governance and efficient use of budget funds. Mathematical modeling and forecasting methods were also used to assess aspects of governance and predict the results when changes are made, including building a trend model and determining the forecast values of accrued taxes and mandatory payments for 2024–2026. The conclusions highlight there is a positive correlation between the accrued taxes and mandatory payments to the budget of the Republic of Kazakhstan, and an economic growth and changes in tax legislation. The key factors influencing the quality of governance and efficient use of budget funds were identified. Recommendations were developed to improve the quality assessment system and governance of budget funds in order to increase efficiency and responsibility in financial management. The results of the study can be used by public administration bodies and financial institutions to optimize the governance of budget funds.
Improving the practical skills of Science, Technology, Engineering and Mathematics (STEM) students at a historically black college and university (HBCU) was done by implementing a transformative teaching model. The model was implemented on undergraduate students of different educational levels in the Electrical Engineering (EE) Department at HBCU. The model was also extended to carefully chosen high and middle schools. These middle and high school students serve as a pipeline to the university, with a particular emphasis on fostering growth within the EE Department. The model aligns well with the core mission of the EE Department, aiming to enhance the theoretical knowledge and practical skills of students, ensuring that they are qualified to work in industry or to pursue graduate studies. The implemented model prepares students for outstanding STEM careers. It also increases enrolment, student retention, and the number of underrepresented minority graduates in a technology-based workforce.
This article presents an analysis of Russia’s outward foreign direct investment based on the balance of payments. The country has been affected by the “Dutch disease,” characterized by a heavy reliance on the mining industry and revenues from oil and gas exports. The financial account reveals a consistent outflow of capital from Russia, surpassing inflows. A significant portion of domestic investment goes abroad, often to offshore destinations. This capital outflow has not been fully offset by foreign capital inflows. These findings underscore the challenges faced by Russia in managing its financial position, including the need to address capital outflows, diversify the economy, and reduce dependence on raw material exports. Furthermore, this article aims to identify the presence of Russian capital in OECD countries by comparing data from the Central Bank of Russia and the OECD. The analysis reveals significant discrepancies between the two datasets, primarily due to unavailable or confidential information in the OECD dataset. These variations can also be attributed to differences in methodology and the specific nature of Russian outward direct investments, particularly those involving offshore jurisdictions. As a result, accurately determining the extent of Russian capital in OECD countries based on the available data becomes a challenging task (including for the tourism industry as well).
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