Highlighted Selections from:

Big Data, Little History

DOI: 10.1177/2043820613514323

Barnes, T J. “Big Data, Little History.” Dialogues in Human Geography 3.3 (2013): 297–302. Web.

p.300: The first is that computational techniques and the avalanche of numbers become ends in themselves, disconnected from what is important. That is, techniques and numbers become fetishized, put on a pedestal, prized for what they are rather than for what they do. -- Highlighted mar 13, 2014

p.300: Even by the early 1970s David Harvey (1972: 6) thought: [Geography’s] quantitative revolution has run its course and diminishing marginal returns are apparently setting in as ... [it] serve[s] to tell us less and less about anything of great relevance ... There is a clear disparity between the sophisticated theoretical and methodological framework which we are using and our ability to say anything really meaningful about events as they unfold around us. -- Highlighted mar 13, 2014

p.300: Francis Galton, the Victorian inventor of regression analysis, famously said, ‘Whenever you can, count’. That injunction has been raised to a significant power in the current regime of big data. The corollary is that if it can’t be counted, it can’t be included. Specifically, what is often lost is context, which cannot be put into an equation (Boyd and Crawford, 2012: 671). -- Highlighted mar 13, 2014

p.301: Anderson writes, ‘Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all’ (2008). This is data determinism with a vengeance. -- Highlighted mar 13, 2014

p.301: For Sayer, numbers are never innocent, speaking for themselves, but always come marked by prior theorization: they are theory laden. Numbers do not speak for themselves but speak only for the assumptions that they embody. Numbers emerge only from particular social institutions, arrangements and organizations mobilised by power, political agendas and vested interests. -- Highlighted mar 13, 2014

p.301: The problem, then, was that because past data on spatial interaction was used to determine the locations of Swedish public social service and health facilities, the old sociospatial order was reproduced. Inequalities of the past were revisited on the present. This was not deliberate. Administrators had the best intentions. But the very techniques that they used unintentionally led them to uphold prior inequalities. -- Highlighted mar 13, 2014