Metrics and methods for social distance

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 171-189).Distance measures are important for scientists because they illustrate the dynamics of geospatial topologies for physical and social processes. Two major types of distance are generally used for this purpose: Euclidean Distance measures the geodesic dispersion between fixed locations and Cost Distance characterizes the ease of travel between two places. This dissertation suggests that close inter-place ties may be an effect of human decisions and relationships and so embraces a third tier of distance, Social Distance, as the conceptual or physical connectivity between two places as measured by the relative or absolute frequency, volume or intensity of agent-based choices to travel, communicate or relate from one distinct place to another. In the spatial realm, Social Distance measures have not been widely developed, and since the concept is relatively new, Chapter 1 introduces and defines geo-contextual Social Distance, its operationalization, and its novelty. With similar intentions, Chapter 2 outlines the challenges facing the integration of social flow data into the Geographic Information community. The body of this dissertation consists of three separate case studies in Chapters 3, 4 and 5 whose common theme is the integration of Social Distance as models of social processes in geographic space. Each chapter addresses one aspect of this topic. Chapter 3 looks at a new visualization and classification method, called Weighted Radial Variation, for flow datasets. U.S. Migration data at the county level for 2008 is used for this case study. Chapter 4 discusses a new computational method for predicting geospatial interaction, based on social theory of trip chaining and communication. U.S. Flight, Trip and Migration data for the years 1995-2008 are used in this study. Chapter 5 presents the results of the tandem analysis for social networks and geographic clustering. Roll call vote data for the U.S. House of Representatives in the 111th Congress are used to create a social network, which is then analyzed with regards to the geographic districts of each congressperson.by Clio Andris.Ph.D

Contextual and Ethical Issues with Predictive Process Monitoring

This thesis addresses contextual and ethical issues in the predictive process monitoring framework and several related issues. Regarding contextual issues, even though the importance of case, process, social and external contextual factors in the predictive business process monitoring framework has been acknowledged, few studies have incorporated these into the framework or measured their impact. Regarding ethical issues, we examine how human agents make decisions with the assistance of process monitoring tools and provide recommendation to facilitate the design of tools which enables a user to recognise the presence of algorithmic discrimination in the predictions provided. First, a systematic literature review is undertaken to identify existing studies which adopt a clustering-based remaining-time predictive process monitoring approach, and a comparative analysis is performed to compare and benchmark the output of the identified studies using 5 real-life event logs. This curates the studies which have adopted this important family of predictive process monitoring approaches but also facilitates comparison as the various studies utilised different datasets, parameters, and evaluation measures. Subsequently, the next two chapter investigate the impact of social and spatial contextual factors in the predictive process monitoring framework. Social factors encompass the way humans and automated agents interact within a particular organisation to execute process-related activities. The impact of social contextual features in the predictive process monitoring framework is investigated utilising a survival analysis approach. The proposed approach is benchmarked against existing approaches using five real-life event logs and outperforms these approaches. Spatial context (a type of external context) is also shown to improve the predictive power of business process monitoring models. The penultimate chapter examines the nature of the relationship between workload (a process contextual factor) and stress (a social contextual factor) by utilising a simulation-based approach to investigate the diffusion of workload-induced stress in the workplace. In conclusion, the thesis examines how users utilise predictive process monitoring (and AI) tools to make decisions. Whilst these tools have delivered real benefits in terms of improved service quality and reduction in processing time, among others, they have also raised issues which have real-world ethical implications such as recommending different credit outcomes for individuals who have an identical financial profile but different characteristics (e.g., gender, race). This chapter amalgamates the literature in the fields of ethical decision making and explainable AI and proposes, but does not attempt to validate empirically, propositions and belief statements based on the synthesis of the existing literature, observation, logic, and empirical analogy

Multivariate spatial interaction models as applied to China's inter-provincial migration, 1982-1990

By using spatial interaction models (SIMs) to estimate place-to-place migration, it usually means that we employ some known information to estimate migration flow patterns. The conventional spatial interaction modelling of migration has been questioned for its lack of explanatory power. The present study takes a new perspective that has not been attempted before; that is, multiple socioeconomic variables can be included in the conventional SIMs. Models based on this new approach are termed Multivariate Spatial Interaction Models (MSIMs). In this particular study, it involves using the two additional variables, the average total annual investment and migrant stock, together with total out-migrants of each province and a distance matrix, to estimate China's province-to-province migration flows. The fundamental idea behind this new perspective is to weigh the socioeconomic importance of each province, so that migration flows will not only be accounted for by the traditional spatial distance but also be accounted for by socioeconomic conditions of provinces. The proposed MSIMs are derived under the framework of the information minimisation principle. MSIMs are successfully calibrated utilising the 1982-87 and 1985-90 province-to-province migration data for the 28 provinces of China. The models are calibrated by iterative procedures written in FORTRAN 77. The MSIMs are further extended to estimate the origin-specific migration flows. The importance of the two additional variables is evaluated in terms of the relative contribution to the performance of the models. The original contribution of the present research can be understood to lie in the new proposed MSIMs, in the extension to modelling origin-specific flows, which have not attempted before, and in the successful empirical application of the models to the Chinese inter-provincial migration data. The empirical results illustrate that all the MSIMs produce better results than the conventional SIMs. In other words, all models with the additional variable(s) are capable of replicating migration flows with a much-improved degree of accuracy, in comparison with the conventional model. The calibration has therefore provided empirical support for the validity and utility of the multivariate approach to the spatial interaction modelling of migration. However, the results do not necessarily imply that more variables included in the model would result in a corresponding improvement in model performance. Furthermore, a comparison of performance level between the MSIMs and origin-specific MSIMs indicates that the estimation of origin-specific migration flows can further improve the degree of accuracy in replicating the observed migration. Major forces that influence China's inter-provincial migration are represented by the two additional variables [three quarters] migrant stock and total annual investment. These two variables are appropriate in that they reflect both migration policy change and economic development strategy. The empirical results also imply that selecting appropriate variables is crucial in calibrating migration flows within the proposed framework, because variable selection must be based on the specific country or areal contexts, on the one hand, and is also dependant upon the availability of data, on the other

An agent-based approach to model farmers' land use cover change intentions

Land Use and Cover Change (LUCC) occurs as a consequence of both natural and human activities, causing impacts on biophysical and agricultural resources. In enlarged urban regions, the major changes are those that occur from agriculture to urban uses. Urban uses compete with rural ones due among others, to population growth and housing demand. This competition and the rapid nature of change can lead to fragmented and scattered land use development generating new challenges, for example, concerning food security, soil and biodiversity preservation, among others. Landowners play a key role in LUCC. In peri-urban contexts, three interrelated key actors are pre-eminent in LUCC complex process: 1) investors or developers, who are waiting to take advantage of urban development to obtain the highest profit margin. They rely on population growth, housing demand and spatial planning strategies; 2) farmers, who are affected by urban development and intend to capitalise on their investment, or farmers who own property for amenity and lifestyle values; 3) and at a broader scale, land use planners/ decision-makers. Farmers’ participation in the real estate market as buyers, sellers or developers and in the land renting market has major implications for LUCC because they have the capacity for financial investment and to control future agricultural land use. Several studies have analysed farmer decision-making processes in peri-urban regions. These studies identified agricultural areas as the most vulnerable to changes, and where farmers are presented with the choice of maintaining their agricultural activities and maximising the production potential of their crops or selling their farmland to land investors. Also, some evaluate the behavioural response of peri-urban farmers to urban development, and income from agricultural production, agritourism, and off-farm employment. Uncertainty about future land profits is a major motivator for decisions to transform farmland into urban development. Thus, LUCC occurs when the value of expected urban development rents exceeds the value of agricultural ones. Some studies have considered two main approaches in analysing farmer decisions: how drivers influence farmer’s decisions; and how their decisions influence LUCC. To analyse farmers’ decisions is to acknowledge the present and future trends and their potential spatial impacts. Simulation models, using cellular automata (CA), artificial neural networks (ANN) or agent-based systems (ABM) are commonly used. This PhD research aims to propose a model to understand the agricultural land-use change in a peri-urban context. We seek to understand how human drivers (e.g., demographic, economic, planning) and biophysical drivers can affect farmer’s intentions regarding the future agricultural land and model those intentions. This study presents an exploratory analysis aimed at understanding the complex dynamics of LUCC based on farmers’ intentions when they are faced with four scenarios with the time horizon of 2025: the A0 scenario – based on current demographic, social and economic trends and investigating what happens if conditions are maintained (BAU); the A1 scenario – based on a regional food security; the A2 scenario – based on climate change; and the B0 scenario – based on farming under urban pressure, and investigating what happens if people start to move to rural areas. These scenarios were selected because of the early urbanisation of the study area, as a consequence of economic, social and demographic development; and because of the interest in preserving and maintaining agriculture as an essential resource. Also, Torres Vedras represents one of the leading suppliers of agricultural goods (mainly fresh fruits, vegetables, and wine) in Portugal. To model LUCC a CA-Markov, an ANN-multilayer perceptron, and an ABM approach were applied. Our results suggest that significant LUCC will occur depending on farmers’ intentions in different scenarios. The highlights are: (1) the highest growth in permanently irrigated land in the A1 scenario; (2) the most significant drop in non-irrigated arable land, and the highest growth in the forest and semi-natural areas in the A2 scenario; and (3) the greatest urban growth was recognised in the B0 scenario. To verify if the fitting simulations performed well, statistical analysis to measure agreement and quantity-allocation disagreements and a participatory workshop with local stakeholders to validate the achieved results were applied. These outcomes could provide decision-makers with the capacity to observe different possible futures in ‘what if’ scenarios, allowing them to anticipate future uncertainties, and consequently allowing them the possibility to choose the more desirable future

Place-based approaches to child and family services

This paper synthesizes the conceptual and empirical literature on place-based approaches to meeting the needs of young children and their families. A specific focus of the paper is on the potential contribution of place-based approaches to service reconfiguration and coordination. Outline The paper begins by outlining the sweeping social changes that have occurred in developed nations over the past few decades and their impact on children, families and communities. It explores the ‘joined up’ problems faced by families and communities in the contemporary world, and highlights the need to reconfigure services to support families more effectively. The paper then focuses on ‘joined up’ solutions, on what we know about how to meet the challenges posed by the complex problems that characterise our society. Next, the paper explores what a place-based approach involves, and what role it can play in supporting families with young children. The rationale underpinning place-based approaches is outlined and the evidence for the effectiveness of the approach is summarised. The paper then looks at what can be learned from efforts to implement place-based initiatives in Australia and overseas, and explores the issues that need to be addressed in implementing this strategy. The ways in which the early childhood service system might be reconfigured are also considered, and the paper ends with a consideration of the policy and implementation implications.&nbsp

Spatial analysis of ethnic migration behavior: A case study of Chinese immigrants in the New York-Newark-Jersey City metropolitan area

The population of Chinese immigrants in the United States has undergone progressive growth in the past 50 years and has reached an epidemic number. As minorities, the Chinese immigrants move into receiving places to adapt and succeed in a new social structure while not losing their own identity. Previous studies highlight the role of local contexts that lead to an internal moving decision. Most of these studies view local contexts as global factors assumed to apply equally over a study area. However, the contextual factors do not disperse evenly across space, nor their relationships with migration behavior. Understanding the spatial variability of factors related to Chinese people's migration in the study area is necessary. Therefore, this dissertation aims to explore the role in which neighborhood context may predict migration behavior, with particular attention to how migration factors and their effects vary across space. This research presents novel applications of two methods: clustering analysis (followed by regression models) and multiscale geographically weighted regression (MGWR) to the Chinese population in the New York-Newark-Jersey City metropolitan statistical area as a case study. Besides regression analysis, this research also provides a detailed examination of relationships between micro-level factors using decision tree analysis. Wages, education, English proficiency, and self-employment status are crucial variables in differentiating movers from non-movers. Having naturalized citizenship has a dual effect on migration behavior. Among the movers, stratifications exist in the immigrant Chinese population. Each subgroup has its particular migration pattern and significant indicators. Spatial variations exist in the study area. Neighborhood type 2 (low in socioeconomic and stable status) is the residential place for immigrants from other states. And neighborhood type 1 (high in socioeconomic and stable status) has more within-state immigrants. Regression models accounting for the population stratification and spatial variations have a vast improvement over the OLS model. Approaches considering data associations in both geographic dimension and non-geographic dimensions could be promising

Location linked information

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003.Pages 98 and 99 blank.Includes bibliographical references (p. 75-81).This work builds an infrastructure called Location Linked Information that offers a means to associate digital information with public, physical places. This connection creates a hybrid virtual/physical space, called glean space, that is owned, managed, and rated by the public, for the benefit of the populace. Initially embodied by an interactive, dynamic map viewed on a handheld computer, the system provides two functions for its urban users: 1) the retrieval of information about their surroundings, and 2) the optional annotation of location for communal benefit. Having the ability to link physical location with arbitrary information is an essential function to building immersive information environments and the smart city. Public computing systems such as Location Linked Information will enhance the urban experience, just as access to transportation dramatically altered the sensation and form of the city.by Matthew William David Mankins.S.M