Category: Research Lines (Page 2 of 2)

Description

This project is an effort to extend and adapt basic evolutionary concepts to the study of cities.  It starts from the proposition that urbanites are a city’s way of making another city.  Cities encode information about how to make new versions of themselves.  This information contains implicit instructions for the types of uses and users that would recreate the city, or more specifically the various features and forms that comprise it.  But this code cannot run itself, it requires facilitating conditions that can process it: urbanites.  In running the urban script, urban dwellers are recruited into making tomorrow’s city resemble today’s.  As this takes place in a shifting, uncertain, competitive, and complex environment, this is far from a static or deterministic process. The genetic code of cities is constantly evolving through mutations, selective pressures of various forms, differential replication, and related processes.

Taking this statement seriously orients the Urban Genome Project.  A first and major theoretical challenge is to transform this intuition into a tractable model that can inform research.  The goal is to fashion a structured yet flexible vocabulary for formulating and exploring hypotheses about urban genetics.  This model is not created anew from whole cloth.  Rather, it joins elements and ideas from diverse fields of urban and related research into a synthetic framework.  Nor does it seek to determine a priori all relevant variables and how they should be stratified. Yet it does aim to provide a vocabulary for evaluating and comparing potential variables, and guiding questions about how these variables might fit together. 

We pursue this theoretical project along a number of related fronts.  A first step is to articulate a formal definition of the urban genome and the interconnected elements that sustain and change it.   These all cohere in what we term the “Signature.”  

Sig(c, t, F, L, S, E, w)

The Signature encodes, for some spatial area c, at time point or interval t, the physical form, plus information about its intended or implied uses or activities, and intended or implied users or groups (F).  Information about F is transmitted via some signal (S), and reproduced by agents through L which specifies the actual activities performed by actual groups of people, plus the resources available to the groups to perform activities. All of this takes place within a broader macro-environment (E). Finally, w represents a “world” in which the signature exists. In most cases, we will omit this parameter, but when we need to compare alternative signatures for the same space c and time t, w will be used to distinguish them (i.e., alternative worlds).

A second step builds out this model to show how it can be used to articulate processes of recoding.  Recoding occurs when the urban genome (F in the Signature) is changed.  We elaborate several ways that this can happen, for instance through changes in the Environment (Environmentally Induced Recoding), in the activity patterns and identities of agents (L induced recoding), or in the nature and reach of Signals that convey information about the genome (Signal Induced Recoding).

A third step moves from recoding to replication, and introduces the concept of the formeme.  Formemes are urban versions of memes — small bits of urban form that replicate, such as the cul-de-sac, the bohemian neighbourhood, streetscape design, or public art.  Adapting concepts from population genetics, we develop models for the study of population formetics, which examine changes in the formetic diversity of urban populations.  Key processes that shift formetic diversity include migration, mutation, and selection.  As formemes spread and adapt, they form lineages and are subject to differential survival rates, generating the basis for evolving urban species.

Last we develop concepts for studying more complex evolutionary processes, in which multiple genomes, signatures, and formemes combine into larger complexes that in turn create distinct ecologies.  Examples of such processes include seeding, scaling, and niche construction.  

Description

Scaling is a basic process that characterizes many forms of life.  It refers to the fact that key features of entities strongly depend upon their size, and that in many respects larger versions of life-forms are scaled up versions of smaller ones.  For example, while elephants and mice have very different heart rates, their hearts beat about the same number of times over the course of a lifetime.  Likewise, many features of cities — such as the number of gas stations or patents — can be reliably predicted simply based upon their population size.  According to this view,  developed by Geoffrey West, Luis Bettencourt, and colleagues, larger urban forms are scaled up versions of smaller ones.

This parallel between basic features of organic and urban life has spawned a robust yet recent research tradition devoted to the study of urban scaling laws.  Central to this research is the observation that entities may scale superlinearly, sublinearly, and linearly, often referred to as “scaling regimes.” This means that a feature may increase faster (super), slower (sub), or at the same pace of the city size.  Sub-linear scaling represents economies of scale, whereas super-linear scaling is associated with increasing returns to interaction (which may result in higher crime rates or greater innovation).  Some observers see scaling in terms of innovation cycles and the evolutionary theory of urban systems – superlinear regimes characterize innovative sectors, whereas sublinear regimes result from the diffusion of innovations throughout the system. 

Our research problematizes a key assumption of this tradition: that scaling regimes depend upon the definition of the city in question, in particular its geographic borders.  Rather than search for the ‘true’ definition of the city’s boundaries, however, we instead suggest viewing cities as operating simultaneously at multiple scopes and scales.  For example, New York’s financial services industry on Wall Street may have a much wider scope than a gas station on the same street.

Building on this insight, we develop a series of techniques to identify and understand the scope at which various local features scale.  In particular, we deploy a search algorithm that finds for any feature (e.g. business types) the geographic area in which it reliably scales with population.  These scopes vary widely.  Second, we use these measures of scope to propose a new way to differentiate cities, in terms of size and variety of the scope of experience they offer.  In some cities we exist in large and diverse scopes, in others most scopes are small and similar.  Third, we examine how scope varies across the urban system, and fourth how it has evolved over time.  Overall, this research develops a more complex notion of cities as complex systems of features operating and interacting at many different scales. 

Description

Extending the basic simulation framework developed in “Dynamic Models of Urban Segregation,” this research seeks to develop an explicitly evolutionary model based on concepts derived from “Darwin’s Dangerous Idea of a City.”  Adapting the style of simulation research from Maynard-Smith to Axelrod, we assign “strategies” to venues.  Strategies are various ways in which a venue may seek to optimize its ability to attract and sustain participants.  As some strategies succeed and fail, cities evolve in more or less stable ways.