Celia Lury

Problem Spaces


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enable us to turn observation and contemplation of the world into a standardized set of knowledge objects: journal articles and monographs’ (2016: 391). 7 In most early uses of the term in the humanities and social sciences, infrastructure was used to refer to whatever assemblage of technologies, procedures, and people (hardware, software and people) was robust, stable or solid enough to facilitate a set of organized practices, but the recognition of the mutability of such assemblages has been gradually built into the working definition. There is now a concern with the doing of infrastructures; that is, with infrastructuring as a material-semiotic practice (Bossen and Markussen 2010; Simone 2015; Michael 2020). 8 Law, Ruppert and Savage (2011) describe this understanding of methods – that is, methods as tools – as ‘the methodological complex’ (presumably in an analogy to the ‘patriarchal- military- capitalist complex’) or ‘the methods machine’. The problem with such an approach they say is the separation it introduces and enforces between theory, substance, and method.

– Part I – Problem Spaces

      Would anything change if sensible things were conceived of as ‘across’ space, rather than ‘in’ space?

      Mel Bochner (2008: 74)

      Five approaches relevant to the elaboration of concept of a problem space are introduced here. A first pairing juxtaposes the methodology proposed by John Dewey, an early twentieth-century advocate of pragmatism with the approach to the ‘artificial sciences’ developed by Herbert Simon, one of the mid-twentieth-century founders of cognitive science. The second pairing is feminist theorist Donna Haraway and French sinologist François Jullien. The fifth approach is that of the anthropologist Arjun Appadurai. These final three authors all write at the end of the twentieth and the beginning of the twenty-first century.

      First, the pragmatist John Dewey, for whom the process of inquiry emerges in the transformation of an indeterminate situation into a problem understood as a unified whole:

      Inquiry is the controlled or directed transformation of an indeterminate situation into one that is so determinate in its constituent distinctions and relations as to convert the elements of the original situation into a unified whole. (1938: 108)

      As Matthew Brown (2012) observes, this is a radical conception of inquiry. Inquiry is not a process of thought that takes place in the mind of an inquirer for Dewey, but a process of transforming a situation. As the Introduction outlined, this emphasis on the transformation of a situation becoming a problem is at the heart of compositional methodology.

      But what does Dewey mean by situation? As Brown notes, there is certainly scope for a range of interpretations (see also Savransky 2016) as is clear from this long extract from Dewey’s Logic: Theory of Inquiry:

      So, for Dewey, the very distinction between object or problem and situation is not to be assumed; instead an object or problem is always part of a situation, a background or surrounding. That situation is not a single object or event; it is a contextual whole. This explication helps, to some degree, but what might Dewey mean by ‘contextual whole’: the immediate surroundings of a phenomenon, or the whole world? The interpretation that is of most relevance for a compositional methodology is that proposed by Brown; that is, for the purposes of inquiry, a situation can be taken to mean those aspects of the surrounding or whole world that preserve the ‘connection and continuity’ present in the experienced world while providing limiting conditions for generalization’ (Dewey 1991: 7–8 in Brown 2012: 269).

      What I take from this is that the establishment of connection and continuity in the process of inquiry should be the aim of compositional methodology, and the basis for the making of claims of epistemological value. Or to put this another way: a process of inquiry informed by compositional methodology aims to transform an indeterminate situation into a determinate situation, preserving connection and continuity while also operating limits for generalization. In the terms introduced in the last chapter, this involves acting on or operating limits, with-in and out-with a problem, to enable generative circulation across a problem space.

      Ideas, Dewey says, are ‘anticipated consequences (forecasts) of what will happen when certain operations are executed under and with respect to observed conditions’ (1991: 109). Neither facts nor ideas are self-sufficient