An Evolutionary Theory of the City
As cities become the form of settlement for an increasing majority of human beings, understanding their basic structures and functions becomes increasingly important. Across a number of fields, researchers are converging on the task of building a new Science of Cities that can take account of cities' physical, social and cultural features, as well as their natural environment. This working group is devoted to gathering interdisciplinary-minded scholars interested in collectively exploring what a science of cities for the 21st century could be. While this is an open-ended task, we are especially interested in pursuing ecological and evolutionary concepts.
The Urban Genome Project is funded by U of T's Connaught Global Challenge Award
- Dan Silver, Sociology (UTSC)
- Mark Fox, Industrial Engineering and Computer Science
- Patrick Adler, Rotman School of Management
- Rob Wright, Landscape architecture
- Scott Sanner, Industrial Engineering
- Ultan Byrne, Daniels Faculty of Architecture, Landscape and Design
- Fabio Dias, Industrial engineering postdoctoral student
- Marion Blute (Emeritus), Sociology
- Shoshanna Saxe, Civil Engineering
- Noga Keidar, Sociology graduate student
- Olimpia Bidian, Sociology PhD student
- Fernando Calderon, Sociology, PhD student
- Alex Olson, PhD student
- Isabel Zhang
- Ronen Yakubov, Industrial Engineering undergraduate
April 2019: Urban Genome Project I
This paper develops a model of socio-spatial neighborhood evolution, using Toronto, Canada as our case study. Building on neighborhood change research and complexity theories of cities, we address three research questions: 1) What are the main types of neighborhoods in the city and how are they organized, both spatially and hierarchically? 2) What are the main patterns of neighborhood change over time, and how are they inflected by space? 3) How are these trends likely to unfold in the future, and how might they change under certain urban planning scenarios? Cluster analysis reveals three major neighborhood types, which we term “creative city,” “suburban,” and “marginalized,” along with sub-types in which various occupational and ethnic groups tend to predominate or mix. Markov models of transition patterns prove to be highly accurate, successfully predicting the final distribution of neighborhood types with an average RMSE of 0.008. Counterfactual scenarios empirically demonstrate urban complexity: small initial changes reverberate throughout the system, and unfold differently depending on their initial geographic distribution. These scenarios show the value of complexity as a framework for interpreting data and guiding scenario-based planning exercises.
Download article here: Markov Model of Urban Evolution 2 - Dan Silver.pdf
Synthesizing and extending multiple literatures, this article develops a new approach for exploring the spatial articulation of urban political cleavages. We pursue three questions: (1) To what extent does electoral conflict materialize between rather than within neighborhoods? (2) How salient are group, place, and location in defining urban cleavages? (3) How do these sources inflect one another? To answer these questions, the article analyzes a novel longitudinal database of neighborhood-scale mayoral voting in Chicago, Toronto, and London. We find strong evidence of spatially articulated cleavages: in each city, voting patterns are equally or more geographically concentrated than the non-White population, income, and poverty. While group-based interests define Chicago’s cleavage structure, place and location are paramount in Toronto and London. We conclude by proposing a research agenda for investigating the spatiality of urban politics and advancing a preliminary typology of urban political cleavages and the conditions under which they may arise.
This article proposes a novel method for data‐driven identification of spatiotemporal homogeneous regions and their dynamics, enabling the exploration of their composition and extents. Using a simple network representation, the method enables temporal regionalization without the need for geographical harmonization. To allow for a transparent corroboration of our method, we use it as a basis for an interactive and intuitive interface for the progressive exploration of the results. The interface guides the user through the original data, enabling both experts and non-experts to characterize broad patterns of stability and change and identify detailed local processes. The proposed methodology is suitable for any region‐based data, and we validate our method with illustrative scenarios from Chicago and Toronto, with results that match the established literature. The system is publicly available, with demographic data for over forty regions in the USA and Canada between 1970 and 2010.
Social media makes available vast amounts of data for various types of analyses. Cities have the opportunity to explore this new data source to study urban dynamics and complement traditional data used for urban planning. We investigate Untappd social media data in the context of urban planning in Curitiba, Brazil. We analyze the project to create a Craft Beer Street, recently announced by the municipality to promote local beers in Curitiba, in order to study the potential of exploring social media data to support the planning of this project. Our results indicate that social media data could have helped to guide the decision of the Beer Street creation and can potentially become a strategic urban planning tool.