Abstract
Contemporary philosophy of science has seen a growing trend towards a focus on scientific practice over the epistemic outputs that such practices produce. This practice-oriented approach has yielded a clearer understanding of how reductive research strategies play a central role in contemporary scientific inquiry. In parallel, a growing body of work has sought to explore the role of non-reductive, or systems-level, research strategies. As a result, the relationship between reductive and non-reductive scientific practices is becoming of increased importance. In this paper, I provide a framework within which research strategies can be compared. I argue that no strategy is reductive or non-reductive simpliciter, rather strategies are more, or are less, reductive than one another according to a frame of reference. That frame of reference is provided by a continuum of possible ways in which the target system might be conceptualised. I illustrate the utility of the framework by deploying it to analyse a recent debate in cancer research. When set within the framework, a prominent reductive strategy—the somatic mutation theory—and a prominent non-reductive strategy—the tissue organisational field theory—do not stand opposed to one another. Rather, they serve as boundary markers to chart the territory of approaches to carcinogenesis within which most strategies in the field fall.
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Notes
I’d like to thank Anna Kocsis, Maria Kronfeldner, Michele Luchetti, Garrett Mindt, and Lena Zuchowski, for criticisms, discussions, and support at various stages of developing the ideas in this paper. I’d also like to thank two anonymous reviewers for their very helpful and constructive comments.
The language of these debates sometimes masks an underlying standoff. For example, Kaplan and Bechtel’s (2011) strategy to dissolve a standoff between mechanistic and dynamical approaches is to argue that there is no competition between them because the former is in the business of providing explanations whereas the latter is not (2011, p. 443; see also Kaplan 2011, p. 367). To me, this seems less like the dissolution of a standoff and more like the development of an epistemic standoff—reductive (in the mechanistic sense) approaches explain whereas non-reductive (at least in dynamic systems modelling) approaches do not. My aim is to move beyond this kind of epistemic standoff by remaining neutral on the explanatory potential of different approaches and instead to analyse their relationship to one another in terms of key aspects of system conceptualisation.
To be clear I am not suggesting that it is impossible for different research strategies to reach an insurmountable standoff. Rather, my argument is that the framework I develop here will show that how reduction can be understood as a comparative relation rather than being absolute. In the example I discuss here, apparently competing theories will be shown to be boundary markers for a field of inquiry rather than competitors. I am confident that this framework will be generalisable beyond the example I use here. However, that expansion requires further empirical cases and their specific details, opening a project for future development.
For example, often practical decisions or practical obstacles will strongly affect system conceptualisation (theoretical assumptions). Simplifying assumptions are often required given limitations of experimental tools available or a lack of knowledge about the system at a given stage of inquiry e.g., in the search for an appropriate unit of intervention for the system. Assumptions such as studying parts in isolation from their environment context (Kaiser 2015, pp. 225–229), or homogenising or fixing environmental factors in space and time (Wimsatt 2007, pp. 347–352) sometimes (but not always) follow from these sorts of practical considerations. In this paper, my analysis is focused on the theoretical assumptions that result in system conceptualisation as a starting point for a framework of analysis. Should this analysis be convincing, then important specificity will surely be added with a thorough treatment of how and why those given theoretical assumptions are adopted, however that work remains for later development.
For a detailed but clear and accessible explication of nonlinearity see Favela (2015, pp. 45–47).
I should be clear that these usages of interaction dominance and component dominance are inspired by, but not necessarily the same as, their usage in dynamic systems theory. However, I think my use of them as container terms for the dynamics of a system is certainly still faithful to what they represent in dynamic systems theory.
As testament to this claim, even for the Cancer Genome Atlas project almost all 33 types of cancer investigated are classified according to the tissue/organ in which they present, and then further sub-classified at the molecular level. Squamous Cell Carcinoma is an exception, although the project focused only on squamous cells collected from the mouth, nose, and throat. Full list is available here: https://cancergenome.nih.gov/cancersselected.
On a cautionary note, this issue remains contested. On the one hand intra-tumour heterogeneity (ITH) is a major area of research, with some claiming that genetic (as well as epigenetic and phenotypic) ITH is now widely recognised across many major tumour types; putting some pressure on Vaux’s argument (Marusyk et al. 2012; Gay et al. 2016). On the other hand, novel treatments—such as BRAF inhibitors for the treatment of metastatic melanoma—and detection methods have been developed that exploit the strong correlation between specific mutations and certain tumour types (Hodis 2012; Bruno et al. 2016).
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Baxendale, M. Mapping the continuum of research strategies. Synthese 196, 4711–4733 (2019). https://doi.org/10.1007/s11229-018-1683-1
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DOI: https://doi.org/10.1007/s11229-018-1683-1