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The argument is raised that, in an age of the networked, connected society in an information-rich environment with communication possibilities as never before experienced or made possible, the displacement of educational virtues of morality, ethics and the development of all-round human beings, by those of money, labour, power and work are speeding apace, and the disconnect between system and lifeworld is increasing. Drawing initially on the work of Habermas, in which the colonization of the lifeworld occurs by system imperatives of rationalization, labour, money and power, the paper argues that such moves are manifested starkly in discourses of the relation between education and work, and five areas are introduced in which the links operate. The marketization and commodification of education, together with its incorporation into the service of capital and labour, are attested through a short worked example of one small territory within the larger context of China. Then, taking a lead from Sertillanges and Habermas’s later work, the paper argues for: (a) a reaffirmation of the importance of moral, ethical and spiritual dimensions of education; (b) the breaking of a narrowly instrumental, capital-acquisitive view of education as serving the jobs market and social control and towards a liberating view of education as communicative action and the development of being rather than simply behaving; (c) the importance of transcendence and immanence; and, thereby, (d) moves towards the re-integration of system and lifeworld in participating subjects.
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The COVID-19 pandemic spread generated an urgent need for computational systems to model its behavior and support governments and healthcare teams to make proper decisions. There are not many cases of global pandemics in history, and the most recent one has unique characteristics, which are tightly connected to the current society’s lifestyle and beliefs, creating an environment of uncertainty. Because of that, the development of mathematical/computational models to forecast the pandemic behavior since its beginning, i.e., with a restricted amount of data collected, is necessary. This chapter focuses on the analysis of different data mining techniques to allow the pandemic prediction with a small amount of data. A case study is presented considering the data from Wuhan, the Chinese city where the virus was first detected, and the place where the major outbreak occurred. The PNN + CF method (Polynomial Neural Network with Corrective Feedback) is presented as the technique with the best prediction performance. This is a promising method that might be considered in future eventual waves of the current pandemic or event to have a suitable model for future epidemic outbreaks around the world.
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This article presents an insight into one of the regions with the fastest-growing economy, heavily based on an entertainment, gaming and tourism industry, and that is urgently looking for a sustainable model that articulates with complementary sectors within the cultural and creative industries – Macao. Macao is facing a major economic and social challenge; it has grown as a vulnerable economy relying almost exclusively on gaming revenues. Alternative activities to diversify the economy are urgently required to answer the competition risks haunting this industry. The cultural and creative industries could be a complementary activity – a vehicle for economic diversification. However, current public and private stakeholders for the cultural and creative sector might have been neglecting the unique cultural and heritage ecosystem of the territory, focusing on isolate opportunities and overlooking an inclusive and robust strategy. A sustainable model that attends to the local conditions and its people is required for alternative activities to become a meaningful sector for the social and economic development of Macao.
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This paper adopts a political economy perspective in understanding how the country context frames the development of higher education doctoral science, technology, engineering, and mathematics (STEM) programs. We argue that a country's commitment to research and development spending as a strategy to maintain its economic competitiveness creates the market for research labor. This embeddedness of STEM doctoral training programs in the country's science and technology system enlarges differences between STEM and non-STEM doctoral programs. This argument is validated from a survey of doctoral students in leading Pacific Asian universities which shows that STEM doctoral programs have stronger research networks, are better financed, use better facilities, and incorporate a variety of research placements. The embeddedness of STEM programs is further illustrated from the case of Singapore. Singapore-based STEM doctoral students mention enjoying better financial support and receiving better career advice from their supervisors. They depend on collaborative peer learning and cite more varied employment options when asked about their career plans.
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