Highlighted Selections from:

The New Quantitative Revolution

DOI: 10.1177/2043820614525732

Wyly, E. “The New Quantitative Revolution.” Dialogues in Human Geography 4.1 (2014): 26–38. Web.

p.27: The ferment of ideas was fierce; hypotheses were tested, paradigms traded, models proposed, theories suggested, explanations offered, systems simulated, and laws sorely sought after ... reality was ransacked in search of theory. -Neil Smith (1979: 356) -- Highlighted apr 4, 2014

p.27: Johnston et al. analyze the pervasive misrepresentations of quantitative analysis that undermine the coherence of human geography as well as its role ‘in the formation of an informed citizenry in data-driven, evidence-based policy societies’ (2014: 4) -- Highlighted apr 4, 2014

p.28: As an alternative, therefore, I’ll offer a cautionary note based on the broader context of the important curricular principles advanced by Johnston et al. Contemporary political economy and the mobilization of powerful institutions seeking to transform the role of education in society are driving a new ‘quantitative revolution’. The revolution is advancing most rapidly in those political circumstances where elite coalitions have been most successful in using the friendly language of ‘evidence-based policy’ to conceal the true emphasis on policy-driven evidence manufacturing (Slater, 2009). After 40 years of neoliberalization and commodification has transformed ‘policy’ into the more sophisticated evasions of ‘governance’, the co-optation is now entering a quickening phase of consolidated automation. New curricula for spatial science and quantitative analysis are being written in code, enmeshed in the application programming interfaces of neoliberal digital capitalism. As big data neoliberalism and ‘cognitive–cultural capitalism’ (Scott, 2011a, 2011b) transform education, you, me, and every other human geographer suddenly find ourselves on the wrong side of the River Alpheus in an automated reenactment of geography’s Augean Period (Gould, 1979). -- Highlighted apr 4, 2014

p.28: The logic is compelling: Disciplinary fragmentation has given rise to misrepresentation of the history of spatial science, obscuring the contemporary possibilities of quantitative geographies informed by critical social theory to engage wider publics of ‘an informed citizenry’ in ‘data-driven, evidence-based policy societies’ (p. 4). -- Highlighted apr 4, 2014

p.29: The infusion of competitive market metrics, technocratic instrumental rationality, and neoliberal axioms of consumer choice are transforming education at an accelerating pace. One of the central elements of the neoliberalization of knowledge production involves ‘a ubiquitous quantification of every aspect of teaching, research, and service’ and ‘the forced crunching of all intellectual activity into a number’ (Smith, 2010). -- Highlighted apr 4, 2014

p.29: In one sense, Johnston et al.’s contribution is a clarion call for geographical expertise: Every professional geographer can instantly recognize the desperate societal need for careful, critical appreciation of the distinctive essence of spatial data, the art and science of cartographic communication, and the inferential challenges of spatial analysis. -- Highlighted apr 4, 2014

p.30: Indeed, in those parts of the world shaped by the most advanced developments in the evolutionary trajectories of neoliberalization, it is almost impossible to distinguish ‘public’ data by the criterion of public, democratic control over content, production, and usage. -- Highlighted apr 4, 2014

p.30: The second dimension of the new quantitative revolution involves a process best understood as data mobilization: The simultaneous acceleration of (a) the circulation of data among individuals and institutions in place wherever they happen to be and (b) the production of data streams representing humans in motion. -- Highlighted apr 4, 2014

p.31: Johnston et al. (p. 10) are correct to emphasize that ‘a secure background in quantitative analyses is necessary for an informed citizenry in a society heavily driven by numbers’ and ‘data do not “just exist”’ but are created and performed through evolving social and institutional practice. Mobilization has profound implications for Johnston et al.’s curriculum proposals, as public institutions and social scientists scramble to follow private corporations and the military into the new frontiers of big data. As more public and private institutions become informational enterprises, the tough theoretical questions of previous generations (Abler et al., 1971; Curry, 1996; Harvey, 1969; Turing, 1950) become banal shocks of everyday performativity, exacerbating dilemmas of law and ethics. -- Highlighted apr 4, 2014

p.32: Let the data mining routines find correlations unburdened by theory, we are told:

Society will need to shed some of its obsession for causality in exchange for simple correlations: not knowing why, but only what. This overturns centuries of established practices and challenges our most basic understanding of how to make decisions and comprehend reality. (Mayer-Schönberger and Cukier, 2013: 7)

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p.32: Not only does big data erode the dichotomy between production and consumption, billions of consumers (willing or not) produce the valuable data assets of a handful of large technology companies—as the enterprise reworks the relations between action and observation and subject/object duality. -- Highlighted apr 4, 2014

p.32: Yet there is a simultaneous threat of dehumanization: The stunning efficiencies of automation and code require far fewer human geographers than yesteryear’s quantitative revolution, while the infrastructure of algorithms, laws, and servers enables greater autonomy for digital individuals (Curry, 1997):

Brute efficiencies and inarticulate consummations as soon as they can be spoken of are liberated from local and accidental contexts, and are eager for naturalization in any non-insulated communicating part of the world. Events when once they are named lead an independent and double life. In addition to their original existence, they are subject to ideal experimentation: their meanings may be infinitely combined and re-arranged in imagination, and the outcome of this inner experimentation—which is thought—may issue forth in interaction with crude or raw events ... Where communication exists, things in acquiring meaning thereby acquire representatives, surrogates, signs and implicates, which are infinitely more amenable to management, more permanent and accommodating than events in their first estate. (Dewey, [1925] 1938: 386)

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p.35: Human trust is under siege replaced by an expanding universe of surveillance. -- Highlighted apr 4, 2014

p.35: Compared with spatial science ‘as pioneered 50 years ago’, (p. 17) today’s quantitative revolution takes place in a context that is at once strikingly new, and yet all too familiar. Just as progressive quantitative geographers in the 1960s struggled to find emancipatory possibilities in the war-machine quantification tools deployed by the ‘IBM machine with legs’ (the phrase used by Barry Goldwater to praise U.S. Defense Secretary Robert McNamara, UPI (United Press International), 1962: 22), today’s progressive geographers must work in the shadow of spatial science as co-opted by Obama’s kill-list drones, the exponentiated networks of the NSA’s ‘hop analysis’ surveillance and the pervasive new data ecologies of private marketing firms in an increasingly unstable era of cognitive–cultural capital accumulation. -- Highlighted apr 4, 2014

p.36: From another perspective, Trevor Barnes (2013, p. 4) reminds us of the humanist critics of the quantifiers in the 1970s, who ‘argued geographical context is frequently left out in quantitative studies because it cannot be expressed in numerical form ... what is often lost is context, which cannot be put into an equation’. -- Highlighted apr 4, 2014

p.36: Algorithms are colonizing the inherently human legacy of geographers’ debates during the heady blend of political struggle and methodological innovation that defined the quantitative revolution of the 1960s. Today, we’re forced into a race, as we teach a generation of spatial scientists in an age when more and more of their professional skills are coded into networked expert systems. -- Highlighted apr 4, 2014