Investigating the cultural practice of migrant workers in China: ideology, collective identity and resistance

Cultural practice and collective identity formation are crucial dimensions for the expression of agency within labour struggles. Although these have been eroded, alongside the erosion of the glory of the old urban working class in the post-reform era, working-class culture has played a significant role in China’s modern history of revolution and socialist industrialisation. This thesis investigates the cultural practices of Chinese rural-urban migrant workers in relation to history and to collective political struggles in the wave of labour unrest in post-reform China. Based on extended participant observation, fieldnotes and interviews over the course of a year between 2013 and 2014, mainly with two grass-roots labour organisations, my thesis answers the following questions: What kinds of collective identities and working-class/migrant workers’ culture do these new proletarian organisations construct? How do they understand and define the relationship between culture and collective struggle? What kinds of tensions are evidenced in the production of migrant workers’ culture? Focusing on how ideology, culture and collective identity are contested in relation to gender, class and workers’ resistance, the thesis contributes to better understanding of the on-going process of working class formation. My primary findings sustain the thesis that the migrant labour activists have devised a new version of collective identity and culture for migrant workers in order to contest the cultural hegemony of the state and the market, to raise class consciousness, build alliances and potentially mobilise their collective power to challenge the structural inequalities and injustices in contemporary China. They have developed ideological innovation and hybrid methods to communicate and articulate class identity, interests and political agendas both inexplicitly and explicitly. Moreover, through analysis of ethnographic data, I also reveal the dynamic nature and complexity in the process. The politically charged new version of collective identity and culture sometimes encounters difficulties in articulating itself to ordinary workers. The cultural practices of migrant labour 4 activists are constrained by various factors in the surveilled and limited political space in China. In order to mobilise resources to survive and sustain their struggle, various compromises are made in the interaction with other social actors and in turn, these inflect the representation of their cultural practices. Gender also revealed itself as a significant tension within the ongoing cultural practices of working class solidarity and collective identity construction. Solely stressing the axis of class in the construction of ‘new worker’ identity and the migrant worker’s culture, older male worker activists tended to ignore the gendered working class experiences of rural women migrant workers and activists in labour activism. Consequently, even as they sought to counter the hegemony of neoliberal capitalism in China, the cultural practices of the migrant worker organisations rendered women as subjects of resistance and reinforced the hegemony of patriarchy in Chinese society. This entrenched gender and class dilemma was challenged by the practice of women labour activists who proposed intersectional understandings of collective identities, incorporating gendered subjectivities into practice and expanding the struggle to the realm of social reproduction to liberate women worker’s agency in the class struggle and build broader alliances in striving for a more just society for all

Virtual to Real Reinforcement Learning for Autonomous Driving

Reinforcement learning is considered as a promising direction for driving policy learning. However, training autonomous driving vehicle with reinforcement learning in real environment involves non-affordable trial-and-error. It is more desirable to first train in a virtual environment and then transfer to the real environment. In this paper, we propose a novel realistic translation network to make model trained in virtual environment be workable in real world. The proposed network can convert non-realistic virtual image input into a realistic one with similar scene structure. Given realistic frames as input, driving policy trained by reinforcement learning can nicely adapt to real world driving. Experiments show that our proposed virtual to real (VR) reinforcement learning (RL) works pretty well. To our knowledge, this is the first successful case of driving policy trained by reinforcement learning that can adapt to real world driving data

Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing

Existing regression models tend to fall short in both accuracy and uncertainty estimation when the label distribution is imbalanced. In this paper, we propose a probabilistic deep learning model, dubbed variational imbalanced regression (VIR), which not only performs well in imbalanced regression but naturally produces reasonable uncertainty estimation as a byproduct. Different from typical variational autoencoders assuming I.I.D. representations (a data point's representation is not directly affected by other data points), our VIR borrows data with similar regression labels to compute the latent representation's variational distribution; furthermore, different from deterministic regression models producing point estimates, VIR predicts the entire normal-inverse-gamma distributions and modulates the associated conjugate distributions to impose probabilistic reweighting on the imbalanced data, thereby providing better uncertainty estimation. Experiments in several real-world datasets show that our VIR can outperform state-of-the-art imbalanced regression models in terms of both accuracy and uncertainty estimation. Code will soon be available at https://github.com/Wang-ML-Lab/variational-imbalanced-regression.Comment: Accepted at NeurIPS 202

Open data governance in smart mobility: an empirical investigation of Shanghai

Master of Science i global ledelse - Nord universitett 202

Negative and Positive Priming Effects on Global-Local Processing : Chinese Participants Respond to Navon Paradigm with Chinese Characters

Referring to hierarchical visual stimuli consisting of global and local levels，Navon figures are often used within studies of global-local processing. Although previous studies have reported negative priming effects for sequentially presented Navon figures，the results vary across cultures. Western participants exhibit negative priming effects at the local level，while East Asian participants exhibit negative priming effects at the global level. ln contrast to the letters and numbers used in prior studies, the present study used Chinese characters，which possess internal structures of various local features, such as strokes and radicals, and, therefore, may further emphasize global processing. The results revealed a positive priming effect at the local level and a trend for negative priming at the global level. These results suggest that East Asians tend to process both larger contexts and the details，and, thus, only inhibit local, not global, levels of irrelevant information

The Application of the “Three Accordance” Principles in the Translation of Foreign Publicity Texts: Taking the translation of Chinese leaders’ epidemic speech as examples

This paper takes the epidemic speech of Chinese leaders as the research object, analyzes the English translation of the epidemic speech of Chinese leaders in detail based on the “Three Accordance” Principles for External Publicity. The translation techniques of foreign publicity texts are discussed - comparing words with each other, turning images into meanings and adapting to local customs. These three techniques are used in order to show the strengths of China and avoid the prejudice and better publicize Chinese opinions and attitudes