Month: December 2022

“Complex causal structures of neighbourhood change” is published!

One key way that evolutionary processes occur is via feedback loops. A classic way to model such feedback loops is in functional terms. Arthur Stinchcombe articulated the elemental structure of functional explanations in his 1968 book, Constructing Social Theories. In our recently published article, “Complex causal structures of neighbourhood change,” we try to revive this model and demonstrate its value for studying the evolution of cities.

The above figures shows Stinchcombe’s model on the left, and our reformulation of the model for neighbourhood evolution. It codified the causal structure of a complete functional explanation in terms of four core elements:

  1. The consequence that tends to be maintained, which also functions indirectly as a cause of the behaviour or social arrangement to be explained. This is H, the “Homeostatic” variable. Though H may tend to be stable empirically, its stability is maintained against pressures to change it, such as in the case of body temperature.
  2. The social arrangement or behaviour that impacts H, the explanandum. This is S, the “Structure.” In a functional model, Structures tend to maintain Homeostasis. For example, sweat glands tend to maintain body temperature.
  3. Tensions that tend to upset Homeostasis, unless Structures maintain it. This is T, the “tension” variable. If physical activity or air temperature did not alter body temperature, there would likely be no structure to counteract the tensions they create.
  4. Processes that reinforce or select for the S’s (structures) that maintain H (homeostasis). When H is threatened or pressured, these forces increase the activity of S when T (tensions) are higher and decrease when H is maintained. For example, sweat glands generate more sweat (S) when body temperature (H) is not maintained at normal levels due to a certain phenomenon (T). Since this structure helps to maintain H in equilibrium, it will tend to be selected or reinforced.

Stinchcombe’s diagram may be intuitively mapped onto familiar neighbourhood dynamics. For example, we may treat as Homeostatic (H) variables neighbourhood character, style, or scene (such as distinctive shops, restaurants, venues, or groups), Tension (T) variables as pressures to change that character (from, for example, new groups with divergent tastes), and Structure (S) variables as activities that maintain that character (such as Business Improvement Association sponsored festivals, political advocacy, or increased participation in venues and activities distinctive to that scene).

Based on this simple representation, we formulate an initial set of propositions regarding the presence and strength of 1) a functional relationship and 2) a homeostatic response, which can be seen in the paper in more detail.

The key value of such models from the point of considering urban evolution is that treat both persistence and change as a dynamic process. Urban forms of life are retained when there exist structures that preserve them when new challenges. If such structures respond effectively to tensions, there is a tendency for them to be selected and reinforced over time, generating both a pattern of structural retention and possible evolutionary histories of such structures. This idea is scarred further in Part III of “Towards a Model of Urban Evolution,” in our discussion of “retention hypotheses.”

Using data drawn from, we find considerable evidence that the sort of functional process envisaged in the model is a common feature of urban evolution. And in the process we develop novel methods for using data from Yelp and similar sources for such analyses.

We see great potential for using these models and methods for characterizing neighbourhoods in new ways. In contrast to the typical approach, which does so primarily by their demographics or built form, our proposed functionalist approach would identify neighbourhoods with more or less latent potential to resist tensions. In this way, neighbourhoods that look otherwise similar could be shown to have very different probabilities of maintaining their identity over time, thereby allowing planners and policymakers to take these latent functional capacities into account.

While incorporating novel data sources and methods would, to some extent, be challenging, doing so would be in line with parallel proposals. Indeed, local jurisdictions routinely use big data in multiple ways: traffic demand management (using GPS and sensor data), land use (using remotely sensed data), public health (COVID sewage testing), commercial health (using payments data), and more. Our methods could be used in a similar way to monitor tendencies toward neighbourhood change.

From the point of view of social science research more generally, perhaps the biggest result of our study is the possibility of reviving interest in functional explanation. While functional explanation has been characterized as “what any science does,” it has largely fallen out of favour in social science. We review common criticisms, and show that they do not apply to a properly specific functional model of the sort we propose.

At the same time, we find considerable evidence that functionalist motifs are commonplace in neighborhood change research. Researchers typically appeal to functionalist motifs when they discuss for example the capacity of local groups to push back against tensions or challenges as a key mechanism producing continuity or change.  However, we found no examples in the neighbourhood change literature where an author who utilized a functionalist motif articulated the motif in an explanatory model that would render it testable. Instead, much neighbourhood change research remains largely descriptive, mapping types and directions of change across a range of variables.

We hope one result of our study is to illustrate a path for remedying this situation, which in turn would help to more formally incorporate evolutionary thinking into urban research.

Toronto Urban Evolution Model Paper Series Published!

A central theoretical goal of the Urban Genome Project has been to articulate a model of urban evolution. We develop the model in four papers, recently published together in Urban Science. The paper series is called “Towards a Model of Urban Evolution,” because its central task is to elaborate a rich yet rigorous formal language capable of formulating propositions about the evolution of cities.

Paper I is “Context.” It proceeds in four major sections. First, we review prior adumbrations of an evolutionary model in urban theory, noting their potential and their limitations. Examples include Chicago School Ecology, stage theories, and theories of cities as complex adaptive systems. Second, we turn to the general sociocultural evolution literature to draw inspiration for a fresh and more complete application of evolutionary theory to the study of urban life. Third, building upon this background, we outline the main elements of our proposed model, with special attention to elaborating the value of its key conceptual innovation, the “formeme”. A formeme is a specific encoding of urban space as a combination of physical features and the groups and activities toward which they are oriented.

In turn we discuss the value of the model, highlighting its extension of the basic inferential logic of population genetics and evolutionary ecology into the urban domain, including the goal of replacing essentialist with distributional thinking, group and development thinking with tree and network ideas. Last, we conclude with a discussion of what types of research commitments the overall approach does or does not imply. Among other things, we note that an evolutionary model of the sort we develop is neither reductive nor deterministic, nor is it necessarily progressivist or teleological. We conclude by suggesting that an evolutionary approach suggests embracing new metaphors for the role of the planner: the planner less as an engineer pulling the levers of a well-tuned machine and more as a gardener in a forest, seeking to cultivate a rich ecosystem while remaining sensitive to processes unfolding through their own dynamics.

Type of DependenceSummaryExample
Principles Related to Form Features
ScopeFormemes with wider niches will tend to attract more resources. Formemes with wider niche width will have a relativity higher probability of survival when the environment is changing, specialized forms will be favored under stable conditionsMcDonalds has a wider niche width than a vegan, organic hamburger stand.McDonalds is more likely to survive a 30% increase in the local minimum wage or a pandemic than the local hamburger stand.
ContentThe viability of a formeme will be influenced by its proximity to groups with a preference for or against the substantive content of its activities or the group affiliation it affirms.Ethnic shops will tend to proliferate in areas where members of that ethnicity reside; satanic book stores will have low survival rates nearby Evangelical Christian populations.
Distance Propagation of a formeme depends on how physically close it is to other iterations of the same formeme.The franchise of a successful operation will be more viable at some ideal physical distance from the original 
Principles related to environmental features
DensityPropagation of a formeme depends on density of competitors in the environmentNeopolitan pizza thrives when there is a glut of pizza restaurants
FrequencyPropagation of a formeme depends on the size of the formeme’s populationThe 28,000th Starbucks location propagates at a different rate and in different places than the first.
Principles Governing the Evolution of Urban Form

Paper II elaborates the formal model. It defines the Signature of an urban space, comprised of the information encoded in that space. This information consists of: an urban genome, which captures ideas regarding the groups (i.e., users) and activities (i.e., uses) to which a space’s physical forms are oriented; ideas among human actors regarding who (users) and how (uses) to utilize the space and its forms; and the signals that are communicated within and among urban spaces. Central to the model is the notion of the formeme, which provides the building blocks for a Signature. Formemes are units of urban information regarding physical forms, groups, and activities, which may be encoded in physical artifacts, signals, or human actors, and circulate among them. We then show how various metrics can define an urban area based on its Signature, and that these metrics can be used to measure similarity of urban spaces. The Signature, and its underlying formemes capture the sources of variations in urban evolution.

Paper III, “Rules of Evolution,” illustrates how to use the model to formulate propositions about urban evolution. It highlights (1) sources of variations; (2) principles of selection; and (3) mechanisms of retention. More specifically, regarding (1) it defines local and environmental sources of variation and identifies some of their generative processes, such as recombination, migration, mutation, extinction, and transcription errors. Regarding (2), it outlines a series of selection processes as part of an evolutionary ecology of urban forms, including density dependence, scope dependence, distance dependence, content dependence, and frequency dependence. Regarding (3), it characterizes retention as a combination of absorption and restriction of novel variants, defines mechanisms by which these can occur, including longevity, fidelity, and fecundity, and specifies how these processes issue in trajectories define by properties such as stability, pace, convergence, and divergence.

Paper IV, “Evolutionary (Formetic) Distance” provides an application of the model, using data from It demonstrates how the Toronto Urban Evolution Model (TUEM) can be used to encode city data, illuminate key features, showing how formetic distance can be used to discover how spatial areas change over time, and identify similar spatial areas within and between cities. In this application, each Yelp review can be interpreted as a formeme where the category of the business is a form, the reviewer is a group, and the review is an activity. Yelp data from neighbourhoods in both Toronto and Montreal are encoded in this way. A method for aggregating reviewers into groups with multiple members is introduced. Specifically, we use the Apriori algorithm to aggregate reviewers by the types of venues they visit. Performing group aggregation using a level-wise search, this algorithm abstracts groups based on the forms they conducted reviewing activities for. Building on this basis, longitudinal analysis is performed for all Toronto neighbourhoods. Transversal analysis is performed between neighbourhoods within Toronto and between Toronto and Montreal. Similar neighbourhoods are identified validating formetic distance.