Iterating ‘addiction’: Residential relocation and the spatio-temporal production of alcohol and other drug consumption patterns

Addiction is generally understood to be characterised by a persistent pattern of regular, heavy alcohol and other drug consumption. Current models of addiction tend to locate the causes of these patterns within the body or brain of the individual, sidelining relational and contextual factors. Where space and place are acknowledged as key factors contributing to consumption, they tend to be conceived of as static or fixed, which limits their ability to account for the fluid production and modulation of consumption patterns over time. In this article we query individualised and decontextualised understandings of the causes of consumption patterns through an analysis of accounts of residential relocation from interviews undertaken for a large research project on experiences of addiction in Australia. In conducting our analysis we conceptualise alcohol and other drug consumption patterns using Karen Barad's notions of intra-action and spatio-temporality, which allow for greater attention to be paid to the spatial and temporal dimensions of the material and social processes involved in generating consumption patterns. Drawing on 60 in-depth interviews conducted with people who self-identified as experiencing an alcohol and other drug addiction, dependence or habit, our analysis focuses on the ways in which participant accounts of moving enacted space and time as significant factors in how patterns of consumption were generated, disrupted and maintained. Our analysis explores how consumption patterns arose within highly localised relations, demonstrating the need for understandings of consumption patterns that acknowledge the indivisibility of space and time in their production. In concluding, we argue for a move away from static conceptions of place towards a more dynamic conception of spatio-temporality, and suggest the need to consider avenues for more effectively integrating place and time into strategies for generating preferred consumption patterns and initiating and sustaining change where desired

Experiencing space–time: the stretched lifeworlds of migrant workers in India

In the relatively rare instances when the spatialities of temporary migrant work, workers’ journeys, and labour-market negotiations have been the subject of scholarly attention, there has been little work that integrates time into the analysis. Building on a case study of low-paid and insecure migrant manual workers in the context of rapid economic growth in India, we examine both material and subjective dimensions of these workers’ spatiotemporal experiences. What does it mean to live life stretched out, multiplyattached to places across national space? What kinds of place attachments emerge for people temporarily sojourning in, rather than moving to, new places to reside and work? Our analysis of the spatiotemporalities of migrant workers’ experiences in India suggests that, over time, this group of workers use their own agency to seek to avoid the experience of humiliation and indignity in employment relations. Like David Harvey, we argue that money needs to be integrated into such analysis, along with space and time. The paper sheds light on processes of exclusion, inequality and diff erentiation, unequal power geometries, and social topographies that contrast with neoliberalist narratives of ‘Indian shining

Human mobility from theory to practice: Data, models and applications

The inclusion of tracking technologies in personal devices opened the doors to the analysis of large sets of mobility data like GPS traces and call detail records. This tutorial presents an overview of both modeling principles of human mobility and machine learning models applicable to specific problems. We review the state of the art of five main aspects in human mobility: (1) human mobility data landscape; (2) key measures of individual and collective mobility; (3) generative models at the level of individual, population and mixture of the two; (4) next location prediction algorithms; (5) applications for social good. For each aspect, we show experiments and simulations using the Python library "scikit-mobility" developed by the presenters of the tutorial

Routine pattern discovery and anomaly detection in individual travel behavior

Discovering patterns and detecting anomalies in individual travel behavior is a crucial problem in both research and practice. In this paper, we address this problem by building a probabilistic framework to model individual spatiotemporal travel behavior data (e.g., trip records and trajectory data). We develop a two-dimensional latent Dirichlet allocation (LDA) model to characterize the generative mechanism of spatiotemporal trip records of each traveler. This model introduces two separate factor matrices for the spatial dimension and the temporal dimension, respectively, and use a two-dimensional core structure at the individual level to effectively model the joint interactions and complex dependencies. This model can efficiently summarize travel behavior patterns on both spatial and temporal dimensions from very sparse trip sequences in an unsupervised way. In this way, complex travel behavior can be modeled as a mixture of representative and interpretable spatiotemporal patterns. By applying the trained model on future/unseen spatiotemporal records of a traveler, we can detect her behavior anomalies by scoring those observations using perplexity. We demonstrate the effectiveness of the proposed modeling framework on a real-world license plate recognition (LPR) data set. The results confirm the advantage of statistical learning methods in modeling sparse individual travel behavior data. This type of pattern discovery and anomaly detection applications can provide useful insights for traffic monitoring, law enforcement, and individual travel behavior profiling

The exploration of human activity zones using geo-tagged big data during the COVID-19 first lockdown in London, UK

Exploring the human activity zones (HAZs) gives significant insights into understanding the complex urban environment and reinforcing urban management and planning. Though previous studies have reported the significant human activity shifting at the city-level in global metropolises due to COVID-19 containment policies, the dynamic of human activity across urban areas at space and time during such an ever-changing socioeconomic period has not been examined and discussed hitherto. In this study, we proposed an analysis framework to explore the human activities zones using geo-tagged big data in London, UK. We first utilised the activity- detection method to extract visits/stops at space and time as the human activity metric from the mobile phone GPS trajectory data. Then, we characterised HAZs based on the homogeneity of hourly human activity footfalls on the middle layer super output areas (MSOAs). The results show the HAZs not only exhibit declines in human activity but are strongly associated with urban land-use and population variables during the COVID-19 pandemic

Discovering Latent Patterns of Urban Cultural Interactions in WeChat for Modern City Planning

Cultural activity is an inherent aspect of urban life and the success of a modern city is largely determined by its capacity to o er gen- erous cultural entertainment to its citizens. To this end, the optimal allocation of cultural establishments and related resources across urban regions becomes of vital importance, as it can reduce nan- cial costs in terms of planning and improve quality of life in the city, more generally. In this paper, we make use of a large longitudinal dataset of user location check-ins from the online social network WeChat to develop a data-driven framework for culture planning in the city of Beijing. We exploit rich spatio-temporal representations on user activity at cultural venues and use a novel extended version of the traditional latent Dirichlet allocation model that incorporates temporal information to identify latent patterns of urban cultural interactions. Using the characteristic typologies of mobile user cul- tural activities emitted by the model, we determine the levels of demand for di erent types of cultural resources across urban areas. We then compare those with the corresponding levels of supply as driven by the presence and spatial reach of cultural venues in local areas to obtain high resolution maps that indicate urban re- gions with lack or oversupply of cultural resources, and thus give evidence and suggestions for further urban cultural planning and investment optimisation.Cambridge Trus

Entrepreneurship, Development, and the Spatial Context Retrospect and Prospect

Entrepreneurship has been a topical issue in the business administration literature, but in the past decade a wave of interest can be observed on the role of entrepreneurship in the economic growth literature. This paper aims to highlight the various contributions to the entrepreneurship literature from the perspective of regional economic development. After a broad overview, particular attention is given to the regional action space of entrepreneurs, including their social and spatial network involvement. The paper concludes with a future research agenda.entrepreneurship, regional growth, action space, networks, SME, virtual organization, innovation

Time-based Solutions for Gender Just Low Carbon, Sustainable Urban Transformation – Learning from European Time-Planning Practises

The European feminist planning community (including the authors) has been addressing the challenge of a gender-just transition to climate neutral cities offering high quality living conditions for all users for decades. The planning model of a “City of proximity” – originally postulated by feminist planners– has recently evolved to the model of the “15-Minute-City”. It is time to revisit 50 years of European urban time policies underlying this planning model and the theoretical ground for a temporal just city (“zeitgerechte Stadt”). The research project “DraussenDaheim” (=At Home Outside) puts this into practice. The project aims to develop a methodology and toolbox which not only serves the participatory assessment of urban public spaces and their complex spatio-temporal use patterns, but also the co-creative simulation-based design of different planning scenarios. Taking into account a gender- and group-specific perspective, the focus is particularly on the development of less “gender-blind” participation tools that serve the analysis, assessment and co-planning of public open spaces. The target group-specific application of a digitally supported tool mix is described on the basis of two use cases and its added value for the key elements of a temporal just city, procedural and distributional justice, is shown. By making public spaces and vulnerable user groups a focus for the participatory implementation of temporally and spatially just urban transition, this will help to ensure that the transformation is inclusive, responsive to community needs, environmentally sustainable and socially just. As the core of this paper, examples from European city-regions on time-planning practices as well as from the use cases of the DraussenDaheim project are presented with the purpose of informing gender-responsive participation and planning tools. The conclusions highlight both the potentials and pitfalls of time-planning approaches in collaboratively assessing urban public spaces. Moreover, they anticipate a crucial endeavor: enhancing the adaptability and usability of these spaces for care-givers and care dependents. This task is a crucial step towards a more inclusive and gender just urban transformation