Abstract
We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and the transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape.
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Notes
Research programs are, of course, also influenced by non-epistemic values and social contexts, which possibly cannot be separated from these other aspects (Longino 1990). Especially proponents of a sociology of scientific knowledge looked at conflicts in science as indicators of divergent values, interests and socio-political positions (Barnes 1977). Nonetheless, regarding the articulation by scientists themselves of their own assumptions or those of their opponents, while power relations within science are thematized, social interests from what is perceived as outside of science are rarely mentioned in the debates we look at. Presumably this is the case because these scientists share the epistemic stance of value-free science. Hence even when this is not the case, they often speak as if their differences were not related to social-political positions.
A similar notion of philosophy of nature as part of research programs is discussed in Köchy (2009).
The domain of an inquiry should not be seen as given, but instead as demarcated in the course of inquiry, and such demarcations can change. If we take “field” to refer to a domain and a type of inquiry, characterized by problems posed and techniques employed, two distinct fields can nonetheless share a domain if they share a broader interpretation of the subject matter of their respective different methods of inquiry. This often happens in processes of divergence of fields. Furthermore, when a hierarchical view of fields (and domains) is applied, it is possible to say that two fields, which carve out their domains differently, work on sub-domains of the same domain more broadly conceived and hence can be considered sub-fields of a broader field. For helpful considerations about these notions and their relation, see Shapere (1984). On the ways in which knowledge regarding the choice of research domains, questions and methodologies as well as organizational principles are transferred from other fields in the design of new research projects from which new fields might emerge, see Meunier (2018).
Plurality (of questions, approaches, theories, etc., and, accordingly, disciplines or fields) is a fact about current science, which has to be acknowledged by philosophy of science independently of any view on the question of pluralism as a philosophical position (Kellert et al. 2006). We are concerned here with pluralization, i.e. the processes by which plurality comes about.
What might be called the dynamics of research fields, comprises processes of divergence or pluralization, conflict and cooperation, integration or unification, as well as—not always synchronized—continuities and discontinuities on the level of concepts and practices (see Meunier and Nickelsen 2018). On the diversity of patterns of change, esp. in data-driven life sciences, see also Paul (2009).
According to Georg Simmel one of the hallmarks for competition is that parties compete for a prize awarded by a third party (see Nickelsen 2014, p. 355); the prize, in this case, is acceptance in the double sense of recognition and integration.
On the three categories, epistemic competition, competition for resources and scientific controversy, see also Meunier (2016). Jane Maienschein (2000) speaks of “competing epistemologies” in a related way. Jan Sapp’s (1983) notion of a “struggle for authority” resists a separation of the intellectual and social aspects of competition.
On the relevance of names in discipline formation, see Powell et al. (2007).
Although what is borrowed are often not the specific mathematical approaches of these precursors, but a general “world view”.
This translation is usually not carried out explicitly for lack of the required information to specify a detailed model representing a genome-scale network, apart from the fact that such a model would be computationally intractable. Arguments are often based on toy models whose behaviors are thought to be generic and will likely be exhibited by the network of interest as well.
Statisticians commonly use the term “data reduction” to describe the process of extracting the meaningful parts of a dataset. This is not necessarily related to any form of reductionism (cf. Schaffner 2002). However, in our case study not only the data are reduced, but the obtained statistical summary is also believed to reveal the relevant level of organization. Moreover, information that is neglected in this procedure would arguably not be considered meaningless by other biologists. Feinstein (1999) uses the term “statistical reductionism” in a similar sense in the context of medical data.
Fleck comments on the importance of researchers who are part of more than one community in this respect; see Fleck (1979, Ch. 4).
This is, of course, reminiscent of the point captured by Kuhn’s notion of “incommensurability”. However, Kuhn in this respect had a narrower focus on theories, rather than approaches comprising methods, concepts, models etc. The nature and consequences of incommensurability of theories are much debated; see e.g. Oberheim and Hoyningen-Huene (2018) for an overview, as well as contributions in Soler et al. (2008).
With Fleck (1979, p. 111) one might say that a specialist field is successful if it acquires a circle of general experts (professionals not at the forefront of research but engaged in research-based activities) and possibly even an exoteric circle of educated amateurs. For an account of how scientists make third parties interested in their work and the role of translation in the process, see also Latour (1987).
Because the debates concern fundamental rather than technical issues and address a broader community, they often appear in the opinion sections (commentary, perspectives, letter to the editor, correspondence, etc.) of scientific journals. Again, we wish to emphasize that we do not neglect the role of competition for resources in such debates. Even though it is not discussed in greater length here, we believe that epistemic competition and competition for resources typically go hand in hand.
STS scholars have argued (with reference to the notion of underdetermination of theory by evidence) that controversies—despite the opponents’ belief to the contrary—often cannot be settled empirically, but that closure is instead achieved by social means. Our point here is that while contrahents in controversies at least think the conflict can be settled empirically, in cases of epistemic competition this is not the case. Instead, competitors accuse their opponents of having an inappropriate understanding of the phenomena or being invested in unsuitable methods. Some of the cases discussed in the STS literature might however count as epistemic competition on our account; see e.g. Sismondo (2010, Ch. 11), for a summary of STS work on scientific controversies.
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Acknowledgements
This paper was written in the context of the International Biophilosophical School (University of Padua, 27-30 April 2015) as part of the “Integrative Biophilosophy” research project located at the University of Kassel. Funding by the DAAD (German Academic Exchange Service) is gratefully acknowledged. We would like to thank Kristian Köchy, Pierre-Luc Germain, the Editor of the Journal and an anonymous reviewer for helpful comments. R.M. wishes to acknowledge the hospitality of the Institute for Cultural Inquiry (ICI) Berlin where he was an affiliated fellow while revising the paper.
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Gross, F., Kranke, N. & Meunier, R. Pluralization through epistemic competition: scientific change in times of data-intensive biology. HPLS 41, 1 (2019). https://doi.org/10.1007/s40656-018-0239-5
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DOI: https://doi.org/10.1007/s40656-018-0239-5