Abstract
Whether we live in a world of autonomous things, or a world of interconnected processes in constant flux, is an ancient philosophical debate. Modern biology provides decisive reasons for embracing the latter view. How does one understand the practices and outputs of science in such a dynamic, ever-changing world - and particularly in an emergency situation such as the COVID-19 pandemic, where scientific knowledge has been regarded as bedrock for decisive social interventions? We argue that key to answering this question is to consider the role of the activity of reification within the research process. Reification consists in the identification of more or less stable features of the flux, and treating these as constituting stable things. As we illustrate with reference to biological and biomedical research on COVID-19, reification is a necessary component of any process of inquiry and comes in at least two forms: (1) means reification (phenomena-to-object), when researchers create objects meant to capture features of the world, or phenomena, in order to be able to study them; and (2) target reification (object-to-phenomena), when researchers infer an understanding of phenomena from an investigation of the epistemic objects created to study them. We note that both objects and phenomena are dynamic processes and argue that have no reason to assume that changes in objects and phenomena track one another. We conclude that failure to acknowledge these forms of reification and their epistemic role in scientific inquiry can have dire consequences for how the resulting knowledge is interpreted and used.
Highlights
We argue that while reification is a necessary component of any process of inquiry, there are significant consequent risks associated with producing scientific knowledge; and that such risks can be mitigated by explicitly acknowledging the forms of reification involved in research and their potential implications for interpreting scientific findings – in ways that COVID biomedicine, in its haste to inform the pandemic
We lack an adequate philosophical account of how scientific knowledge can inform intervention in a world of constant flux. It is as a step in the direction of such an account that we have proposed the distinction within research practice between means reification (M-Re), the initial construction of epistemic objects, such as models, data, theories or taxonomies, from phenomena, and target reification (T-Re), a specific rendition of the phenomena obtained through the investigation and manipulation of epistemic objects
We conclude with a reflection on the value of process epistemology as a corrective to essentialising views on how empirical knowledge is produced, views which fail to stress the epistemic importance of remaining alert to reification and its consequences; and we draw out some implications of this analysis for our understanding of the nature of knowledge
Summary
A few decades ago it was widely believed that the core problems in the philosophy of science were problems of language. The ways that science connects with these targets of investigations and attempts to capture them, expanded to include not just concepts, but models, data and more, are themselves fluid, developing through scientific activity and changes in scientific context (Rheinberger, 1997, Soler et al, 2014, Leonelli, 2016) It appears that the Putnam/Kripke move was the opposite of the correct one. To understand and intervene in the world, scientists produce models, data and theories that capture how the world is at a specific place and moment in time, and the parameters and criteria they use to represent the world are inherently static (even, as we shall see, when such parameters are geared to capturing dynamic systems, as in the case of adaptive modelling and simulations) This raises a problem that has not been adequately addressed within contemporary philosophy of. We argue that while reification is a necessary component of any process of inquiry, there are significant consequent risks associated with producing scientific knowledge; and that such risks can be mitigated by explicitly acknowledging the forms of reification involved in research and their potential implications for interpreting scientific findings – in ways that COVID biomedicine, in its haste to inform the pandemic
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