Reconceptualizing geography

The following is an excerpt from a critique I wrote for our first-year philosophy of science course. It gives my perspective on the field of geography, as someone who entered a highly-regarded doctoral program in geography having never taken a geography course.

Like many of my colleagues within the cohort of UCSB geography doctoral students, I’m not a geographer in a traditional sense. My background spans multiple disciplines, including—but not restricted to–microbiology, public health, computer science, and more recently, network science. Naturally then, my perception of space is colored by these experiences; and by virtue of having the considerable fortune to dedicate a life to scholarship, I’m afforded the time and intellectual resources to ponder about ‘space’, ‘region’, and ‘place’. This piece is mainly a meditation on ‘region’ and how it should be conceptualized given the context of our times. Here, I will humbly suggest some alternative definitions for ‘region’, while reflecting on how my prior learning, life-experiences, and personal philosophies give rise to these insights. I propose an alternative frame onto which space–and its constituent components–can be modeled.

Unlike biological classification–which rests on a system of taxonomy that funnels living beings into categories of genera and species–geographical classification is noticeably more nebulous. Is a taxonomy of ‘place’ a conceiveable possibility? If geographers attempt to emuluate biological taxonomy as a classification model, would it be possible to define spatial entities that are divorced from the influence of politics and society?

Geographical researchers strive hard to claim legitimacy within the scientific community as a ‘hard’ science. Spatial science is the answer to geography’s perpetual goal to establish itself as legitimate, objective, and free from the shackles of culture and other unquantifiables that have colored the field of geography. However, the fundamental units of geography–place, region, and space–are deeply intertwined with political, cultural, and historical contexts. Therefore, I argue that region should not be removed from its social context. The quantitive methods of spatial science can be used to analyze phenomena that are subjective, social, political, and cultural.

Given today’s dizzying slew of technological and computational tools, mathematical and statistical models have been constructed to simulate and predict human behavior, social dynamics, and even cultural dynamics. For instance, ‘culturomics’ is a burgeoning branch of sociology that uses Big Data techniques to analyze tomes of cultural records. Some notable studies describe examining large corpora of digitized literature to track the development of the English language through history; or using a computational technique called topic modeling to extract contextual meanings from text. The common thread of these studies lie in their use of Big Data, graph theory, and stochastic modeling to find patterns within collections of digitized human artifacts.

My own work rests within the realm of models, and other mathematical and statistical descriptors that aim to distill biological and social behavior into their most salient components. As a trained microbiologist and public health worker, I’m conditioned to view phenomena as tiny interacting entities that progressively affect larger systems–starting from the organism itself, to the organism it ails (usually the human host), to the affected community. When I conceptualize ‘space’, I think similarly. I’m advocating conceptualizing space and its constituent components from a relational perspective. Spatial entities can be modeled as nodes in a network. Relationships, symbolized through edges, can mean that two entities are close in physical proximity or related given a comparison of nodal attributes. Networks can multi-layered, dynamic, and temporal, with entities of many related networks interacting. By design, this network model can be as simple or as complex as the researcher desires.

The concept of space is changing. Vidal’s region and Hawthorne’s chorology are no longer sufficient descriptors of space and place. In this age of computation, it would be a folly to ignore the power of graph models and data science in our conceptualization of space.