30 research outputs found
(Un)filial daughters and digital feminisms in China: The stories of awakening, resisting, and finding comrades
This thesis sets out to understand Chinese feminist struggles in a so-called digital era by looking at the experiences and practices of an emerging generation of digital feminists that came into light in Chinese feminist movements. Conceptually and methodologically, this research took inspirations from an interdisciplinary body of literature including feminist theory, sociology, media and cultural studies, girlhood studies and gender studies. Inspired by online ethnography and feminist participatory methodologies, it combined an online tracking of feminist events on Weibo with semi-structured interviews and social media diary study with 21 Chinese girls and young women.
This thesis explores the embedded and embodied experiences of these participants as they discover and learn about feminism, resist and challenge gender and sexual inequalities, and try to build connections with like-minded people within and beyond the digital sphere. By charting feminist responses and resistance to familial discourses and norms around girlhood and young femininity, I show the emergence of feminist subjectivities of (un)filial daughters that arises from but also comes to reconfigure gender and sexuality within a neoliberal and postsocialist context of patriarchal familism in China. I build upon the concepts of networked counterpublics and networked affects to explore how these (un)filial daughters are networked to carve out spaces for feminist discussion in social media. Employing an affective-discursive analysis, I also tune into how networked feminist resistance and alliances are formed not merely on the basis of how women and feminists talk about these issues but also how they feel
Big data in education and organizational change: Evidence from private K12 schools in China
China is a time-honored civilization with a long history of private education. In China, private education has played an important role in preserving Chinese civilization.
At the end of the 20th century, private education in China began to develop thanks to government support. As such, remarkable progress was made during the past decade. Due to specific conditions within the education industry, however, the administration of private edu-cation - and basic education, in particular - has remained rudimentary compared with other more mature service industries. To address the many problems in basic education, such as rig-id teaching methods, heavy teacher workloads and long, repetitive working hours, it is imper-ative in this information era to conduct innovative explorations with the help of the “internet of things” (IoT), big data and other scientific and technological means to carry out organiza-tional reform in schools and to establish contemporary organizational structures and manage-ment modes. Doing so will comprehensively improve the administration of basic education, which will in turn promote the quality of education and teaching.
This thesis examines Tianli Education Group, a typical example of private, basic educa-tion in China. By adopting experimental research methods, the behavior of students and teachers in Tianli’s schools were experimentally analyzed. IoT technology was employed to collect data about student behavior at school. Likewise, after collecting and analyzing big data on the behavior of teachers at school, the content and processes of their work were analyzed.
Based on these experiments, this thesis explores a new 5G era-appropriate mode of stu-dent selection and training that makes use of big data technology. It outlines the standard work scenario for teachers and improves both their work efficiency and salaries by “trimming staff and streamlining administration,” thus rekindling enthusiasm among teachers for their work. Finally, as a part of this thesis, a series of organizational changes were implemented at Tianli Education Group and its schools to boost organizational vitality, improve overall levels of education, teaching and operational efficiency, raise teachers’ salaries and enhance student happiness.A China é uma civilização muito antiga, com uma longa história de educação privada. A educação privada desempenhou um papel importante na preservação da civilização chinesa. No final do século 20, a educação privada na China começou a desenvolver-se com o apoio do governo. Nos últimos dez anos, devido ao apoio concedido temos assistido a um grande progresso. Contudo e em virtude das condições específicas da indústria da educação, a administração da educação privada – a educação básica em particular – permaneceu rudimentar quando comparada com outras indústrias de serviços. Para resolver os muitos problemas da educação básica, tais como os métodos rígidos de ensino, as cargas de trabalho pesadas e horas de trabalho repetitivas, torna-se imperativo nesta era da informação realizar pesquisas inovadoras com a ajuda da “Internet das Coisas”, do “Big Data” e meios científicos e tecnológicos que nos permitam realizar a reforma nas escolas e estabelecer estruturas organizacionais e métodos de gestão adaptados aos tempos em que vivemos. Os resultados destas pesquisas irão contribuir para melhorar de uma forma abrangente a administração da educação básica, o que por sua vez promoverá a qualidade da educação e do ensino.
Esta tese estuda o Tianli Education Group, que consideramos um bom exemplo do ensino privado na educação básica na China. Adoptando métodos experimentais de pesquisa, o comportamento dos estudantes e professores das escolas Tianli foram analisados. Aplicamos a tecnologia da “Internet das Coisas” para recolher informações sobre comportamento dos alunos na escola. Da mesma forma, após a recolha e análise dos dados sobre o comportamento dos professores na escola, efetuamos a análise do conteúdo e dos processos do seu trabalho. Tendo por base estas experiências, esta tese explora na nova era 5G, um modo apropriado para seleção e formação dos alunos. Esta tese descreve o cenário padrão de trabalho para professores e melhora não somente a eficiência do trabalho como também os seus salários ao “reduzir o pessoal e simplificar a administração”, reacendendo assim o entusiasmo dos professores pelo seu trabalho.
Finalmente, como parte desta tese, uma série de mudanças organizacionais foram implementadas nas escolas do grupo Tianli Education Group com a finalidade de impulsionar a vitalidade organizacional, melhorar todos os níveis gerais de educação, aumentar a eficiência operacional e de ensino, aumentar os salários dos professores e aumentar a felicidade dos alunos
Blockchain-Based Digitalization of Logistics Processes—Innovation, Applications, Best Practices
Blockchain technology is becoming one of the most powerful future technologies in supporting logistics processes and applications. It has the potential to destroy and reorganize traditional logistics structures. Both researchers and practitioners all over the world continuously report on novel blockchain-based projects, possibilities, and innovative solutions with better logistic service levels and lower costs. The idea of this Special Issue is to provide an overview of the status quo in research and possibilities to effectively implement blockchain-based solutions in business practice. This Special Issue reprint contained well-prepared research reports regarding recent advances in blockchain technology around logistics processes to provide insights into realized maturity
Image Understanding by Socializing the Semantic Gap
Several technological developments like the Internet, mobile devices and Social Networks have spurred the sharing of images in unprecedented volumes, making tagging and commenting a common habit. Despite the recent progress in image analysis, the problem of Semantic Gap still hinders machines in fully understand the rich semantic of a shared photo. In this book, we tackle this problem by exploiting social network contributions. A comprehensive treatise of three linked problems on image annotation is presented, with a novel experimental protocol used to test eleven state-of-the-art methods. Three novel approaches to annotate, under stand the sentiment and predict the popularity of an image are presented. We conclude with the many challenges and opportunities ahead for the multimedia community
Social Media and Public Health: Opportunities and Challenges
Social media has the potential to provide rapid insights into unfolding public health emergencies such as infectious disease outbreaks. They can also be drawn upon for rapid, survey-based insights into various health topics. Social media has also been utilised by medical professionals for the purposes of sharing scholarly works, international collaboration, and engaging in policy debates. One benefit of using social media platforms to gain insight into health is that they have the ability to capture unfiltered public opinion in large volumes, avoiding the potential biases introduced by surveys or interviews. Social media platforms can also be utilised to pilot surveys, for instance, though the use of Twitter polls. Social media data have also been drawn upon in medical emergencies and crisis situations as a public health surveillance tool. A number of software and online tools also exist, developed specifically to aide public health research utilising social media data. In recent years, ethical issues regarding the retrieval and analysis of data have also arisen
Enhancing Free-text Interactions in a Communication Skills Learning Environment
Learning environments frequently use gamification to enhance user interactions.Virtual characters with whom players engage in simulated conversations often employ prescripted dialogues; however, free user inputs enable deeper immersion and higher-order cognition. In our learning environment, experts developed a scripted scenario as a sequence of potential actions, and we explore possibilities for enhancing interactions by enabling users to type free inputs that are matched to the pre-scripted statements using Natural Language Processing techniques. In this paper, we introduce a clustering mechanism that provides recommendations for fine-tuning the pre-scripted answers in order to better match user inputs