The dominant theory of cross-disciplinarity represents multidisciplinarity as ‘lower’ or ‘less interesting’ than interdisciplinarity. In this paper, it is argued that this unfavorable representation of multidisciplinarity is ungrounded because it is an effect of the theory being incomplete. It is also explained that the unfavorable, ungrounded representation of multidisciplinarity is problematic: when someone adopts the dominant theory of cross-disciplinarity, the unfavorable representation supports the development of a preference for interdisciplinarity over multidisciplinarity. However, being ungrounded, the support the representation provides for (...) a preference for interdisciplinarity, is invalid. The issue is even more pressing because research policy makers and funding bodies are among the adopters of the theory, which means that there is a risk of policies reflecting an unjustified preference for interdisciplinarity over multidisciplinarity. This paper presents an improved version of the dominant theory of cross-disciplinarity, obtained by completing the original version with the information it was missing. Because the improved version is more neutral regarding the value of different types of cross-disciplinarity, it is better suited for use by research policy makers and funding bodies. (shrink)

In this paper we chart epistemological similarities between shared function talk in biology and the engineering sciences, focusing on the notions of biological advantage function and technical advantage function. We start by showing that biological advantage function ascriptions are common in biology and that technical advantage function ascriptions are common in engineering science. We then proceed to show that these ascriptions have a very similar structure and that their epistemic value also is similar: both biological advantage function and technical advantage (...) function ascriptions provide the means to answer what-would-happen-if questions. We develop and illustrate our claims with four case studies: two from biology, and two from engineering design research. Our results offer new insights into a relatively neglected issue in both philosophy of biology and technology, viz. assessing the explanatory and predictive utility of function ascriptions. (shrink)

In the recent literature on explanation in biology, increasing attention is being paid to the connection between design explanation and mechanistic explanation, viz. the role of design principles and heuristics for mechanism discovery and mechanistic explanation. In this paper we extend the connection between design explanation and mechanism discovery by prizing apart two different types of design explanation and by elaborating novel heuristics that one specific type offers for mechanism discovery across species. We illustrate our claims in terms of two (...) lines of biological research on the biological advantages of organismal traits, one on the eye-size of giant squid, the other on foraging habits of specific bat species. We argue that this research illustrates useful heuristics for mechanism discovery across species, viz. reasoning strategies to infer likely mechanisms for a certain biological role based on assessments of the environmental conditions in which the role is performed efficiently and less or in-efficiently. We bring out the novel features of our analysis in terms of a comparison with mechanistic approaches to mechanism discovery, amongst which graph-theoretical ones, and by comparing the different types of design explanation and the discovery heuristics they support. (shrink)

In this paper we assess the explanatory role of idealizations in ‘design explanations’, a type of functional explanation used in biology. In design explanations, idealizations highlight which factors make a difference to phenomena to be explained: hypothetical, idealized, organisms are invoked to make salient which traits of extant organisms make a difference to organismal fitness. This result negates the view that idealizations serve only pragmatic benefits, and complements the view that idealizations highlight factors that do not make a difference. This (...) analysis in particular strengthens the perspective that idealizations are means to highlight difference making factors, and identifies a novel, more direct role for idealizations in doing so. It thus offers a novel argument why in some explanatory contexts idealizations are in-eliminable. (shrink)

In this paper we assess the explanatory role of idealizations in ‘design explanations’, a type of functional explanation used in biology. In design explanations, idealizations highlight which factors make a difference to phenomena to be explained: hypothetical, idealized, organisms are invoked to make salient which traits of extant organisms make a difference to organismal fitness. This result negates the view that idealizations serve only pragmatic benefits, and complements the view that idealizations highlight factors that do not make a difference. This (...) analysis in particular strengthens the perspective that idealizations are means to highlight difference making factors, and identifies a novel, more direct role for idealizations in doing so. It thus offers a novel argument why in some explanatory contexts idealizations are in-eliminable. (shrink)

In the recent literature on explanation in biology, increasing attention is being paid to the connection between design explanation and mechanistic explanation, viz. the role of design principles and heuristics for mechanism discovery and mechanistic explanation. In this paper we extend the connection between design explanation and mechanism discovery by prizing apart two different types of design explanation and by elaborating novel heuristics that one specific type offers for mechanism discovery across species. We illustrate our claims in terms of two (...) lines of biological research on the biological advantages of organismal traits, one on the eye-size of giant squid, the other on foraging habits of specific bat species. We argue that this research illustrates useful heuristics for mechanism discovery across species, viz. reasoning strategies to infer likely mechanisms for a certain biological role based on assessments of the environmental conditions in which the role is performed efficiently and less or in-efficiently. We bring out the novel features of our analysis in terms of a comparison with mechanistic approaches to mechanism discovery, amongst which graph-theoretical ones, and by comparing the different types of design explanation and the discovery heuristics they support. (shrink)