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Misogynoir Transformed is a pioneering work by Moya Bailey that offers a groundbreaking analysis of misogynoir and the transformative strategies for social change in contemporary digital society. Through careful analysis of media representations, web series, and social media platforms, Bailey reveals how Black women and Black nonbinary, agender, and gender-variant folks encounter and resist damaging narratives. Bailey also introduces the conceptual framework of digital alchemy to conceptualize the praxis that Black women employ to transform harmful everyday media into valuable social justice media, which functions to reduce the negative effects of misogynoir and create their own safe and inclusive community. This transformative activity highlights the dual effects of visibility—it is empowering but also precarious. Bailey's work is evidence of how digital platforms have the positive power to reduce misogynoir and reshape the discourse on gender diversity and social justice.

China is confronted with three intrinsic dilemmas related to farmland conversion: (1) conserving farmland for national food security versus converting farmland to boost local government income; (2) protecting farmland to ensure the basic living conditions of vulnerable farmers versus developing farmland to encourage farmers' transition toward urban livelihoods; (3) preserving farmland by exercising national regulatory controls versus managing farmland through localised negotiations among the concerned stakeholders. This paper analyses three cases based on interview data collected from Shanghai, Guizhou, and Henan between 2009 and 2012. Each case consists of an informal local resolution to one of the three farmland dilemmas, and involves a variety of actors—local entrepreneurs, ethnic minority farmers, and village committee members—who act as 'barefoot planners'. On the basis of these findings, this paper makes a series of policy recommendations and calls for more flexible, spontaneous, and place-based farmland planning in China through social learning.

Justice: From Mystery to Openness -- Development of Contemporary China's Judicial Openness System -- The Rationale Behind Judicial Transparency -- Methodologies for Researching Judicial Transparency -- The Overall Situation of China's Judicial Transparency -- Status Quo of Judicial Transparency in Various Fields -- Promoting More Transparent Justice.

"Big data is increasingly regarded as a new approach for understanding urban informatics and complex systems. Today, there is unprecedented data availability, with detailed remote-sensed data on the built environment, and rich mineable web-based sources in the form of social media, web mapping, information services and other sources of unstructured "big data". This book brings together a group of international contributors to consider the geographical implications of mobility, wellbeing and development within and across Chinese cities through location-based big data perspectives. The degree of urban sprawl, productive density, and vibrancy can be reflected from location-based social media big data. The challenge is to identify, map, and model these relationships to develop cities at different places in the urban hierarchical system that are more sustainable. This edited book aims to tackle these issues through two inter-related geographical scales: inter-city level and intra-city level. The text is designed for graduate courses in planning, geography, public policy and administration, and for international researchers who are involved in urban and regional economics and economic geography"--

: The article is devoted to the problem of substantiating the hyphenation
of the noun контр-адмирал in diachrony and modern writing. The purpose of the
article is to establish the usual and codified spelling norms of this lexeme and to
trace their dynamics. The usage is established by sampling on the material placed
in the National Corpus of the Russian Language. In addition, the material of grammars and dictionaries of the 18th and 19th centuries is used: The Dictionary of the
Russian Academy of the turn of the 18th–19th centuries in two editions, Dictionary
of the Church Slavonic and Russian Language (1847), grammars by N.I. Grech (1827),
A.Kh. Vostokov (1831), the Academic Grammar of 1849. Nouns beginning with
контр- are not codified strongly enough in this period, but the tendency to hyphenate such words develops in the next century and persists to the present day. Obviously, it was originally supported by the tradition of using capital letters in the
composition of words such as контр-адмирал. As the uppercase letters were
eliminated here, the authors of the 1956 Rule put forward the idea of the semantic
separateness of the hyphenated use of контр-, as opposed to the normative confluent use. In the 2020s, the newest academic IPS resource "Spelling Comments on the
Russian Dictionary" made an unsuccessful attempt to explain the peculiarities of
the spelling of the word контр-адмирал with the meaning 'low', which is not confirmed by dictionary data. Obviously, the retention of the hyphenated form of
контр-адмирал is due to the orthographic tradition and the desire to isolate morphemes in writing.

This paper mainly studies the market nonlinearity and the prediction model based on the intrinsic generation mechanism (chaos) of Bitcoin's daily return's volatility from June 27, 2013 to November 7, 2019 with an econophysics perspective, so as to avoid the forecasting model misspecification. Firstly, this paper studies the multifractal and chaotic nonlinear characteristics of Bitcoin volatility by using multifractal detrended fluctuation analysis (MFDFA) and largest Lyapunov exponent (LLE) methods. Then, from the perspective of nonlinearity, the measured values of multifractal and chaos show that the volatility of Bitcoin has short-term predictability. The study of chaos and multifractal dynamics in nonlinear systems is very important in terms of their predictability. The chaos signals may have short-term predictability, while multifractals and self-similarity can increase the likelihood of accurately predicting future sequences of these signals. Finally, we constructed a number of chaotic artificial neural network models to forecast the Bitcoin return's volatility avoiding the model misspecification. The results show that chaotic artificial neural network models have good prediction effect by comparing these models with the existing Artificial Neural Network (ANN) models. This is because the chaotic artificial neural network models can extract hidden patterns and accurately model time series from potential signals, while the benchmark ANN models are based on Gaussian kernel local approximation of non-stationary signals, so they cannot approach the global model with chaotic characteristics. At the same time, the multifractal parameters are further mined to obtain more market information to guide financial practice. These above findings matter for investors (especially for investors in quantitative trading) as well as effective supervision of financial institutions by government.

AbstractThe debate on the vitality of the commons remains unsettled, but the attempt by the Chinese state to develop a marketized property rights system to address the so‐called tragedy of the commons has backfired. In Shanghai and other major Chinese cities, the economic transformation has led to an ambiguous property rights system that creates complex and uncertain property relations between the state and private land developers. The resulting ineffective uses and conflicts in the commons are well known, but how to address them is contested. Can privatization drive better use of urban land in China? How do the ambiguous property relations between the state and the private sector affect the spatial design, management, use, and quality of the urban commons in Chinese cities? This article addresses these questions by engaging theoretical debates on how the commons should be held, analyzing the origin and key features of the ambiguous property relation in China, and drawing on a property rights approach to investigate the empirical case of a specific privately owned and managed urban park in Shanghai. The results show that not only does the commodification of property create inherently pervasive ambiguity in the land market, marketization also denies citizens their rights to public space. These findings raise fundamental questions about the idea that marketizing land is a sure tonic to address social problems. The article puts the case for reconsidering the institutionalization of the urban commons.

In this paper, we demonstrate an integrated spatio-social network analysis to measure the degree of segregation within a Chinese urban neighborhood in terms of the everyday activities by rural migrants and local urban residents at such routine venues as restaurants, grocery stores, barber shops, etc. Our data were collected in May 2014, through an integrated geographical and social survey conducted within an inner-city neighborhood around Kecun in south China's Guangzhou Municipality. Although Kecun features a highly condensed and mixed dwelling pattern between the rural migrants and indigenous urban population, we find that within our sample of 110 local and 132 migrant residents, the former tend to socialize more inwardly with their peer locals and visit neighborhood amenities more often such as pubs, stadia, and public kindergartens. In contrast, the migrants tend to attend local roadside food stalls, outdoor recreation facilities, small clinic shops, grocery malls, and private ( minban) kindergartens more often. Overall, only a modest degree of social interaction between the locals and migrants appears to exist in Kecun. On top of the methodological implications of our study, we argue that urban segregation in China is both socially and spatially different from its Anglo-American counterpart. More empirical research is needed to understand and assess social segregation underlying the everyday urban life in Chinese cities.