The Socio-Economic Importance of Scientific Research To Canada

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The Socio-Economic Importance of Scientific Research to Canada Page 9© David A. Wolfe and Ammon Salteras a process of discovery that proceeds in a clear fashion from scientific discovery totechnological change in terms of new product and process development, production, marketingand ultimately, the sale of those products and processes. According to Harvey Brooks,This simplistic model, though increasingly challenged by scholarly research, has had animportant and persistent influence on the organization and management of innovation inthe United States until recently. It still provides a plausible description for many of theradical paradigm–shifting technological innovations during the cold war period, notonly in defense but also in a number of other commercial areas. The most classic caseis the development of nuclear weapons and nuclear power . . . , but other examplesinclude the transistor, the laser, genetic engineering, and many biomedical technologies(1996, 21; cf. also US Office of Technology Assessment 1995, pp. 32–35).As appealing as this model was in its simplicity, and despite the examples cited above thatseemed to provide confirmation for it, it does not bear up well under closer scrutiny.Nathan Rosenberg points out that the image of science leading in a unidirectional chain ofcausation toward new products and processes is simply inaccurate in historical terms (1976).Much of the activity of science owes its course to prior developments in technology or theproductive sphere. For example, the Wright Brothers developed the first airplane without anunderstanding of aerodynamic theory and Chester Carlson developed the first xerographiccopier without a thorough understanding of photoconductive materials. In these cases,however, the line of development leads in the opposite direction to that posited by the linearmodel: these inventions triggered considerable scientific research into aerodynamic theory andmaterials science (US Office of Technology Assessment 1995, p. 21). The technologies thatare developed in the form of new products and processes are not simply an ‘applied’ science.Engineering technology is its own form of knowledge and a critically important one at that (cf.Vincenti 1990). The relationship between publicly–funded research and economic performancemay flow in the opposite direction to that suggested by the linear model and the informationalapproach of neoclassical economics. Rather than flowing from science to technology toproducts and processes, it often goes from production problems to technology to science, in thereverse order of causation posited by the linear model (Martin et al. 1996).Figure 1 about hereThe alternative approach based on evolutionary economics has generated two new strands ofresearch. The first strand suggests that despite the poverty of the old approach,publicly–funded research can still usefully be seen to represent information. Information isseen as codified knowledge, i.e. knowledge which is written down or made explicit. This9
The Socio-Economic Importance of Scientific Research to Canada Page 10© David A. Wolfe and Ammon Salterapproach stresses the informational properties of science discussed above, while at the sametime recognizing the criticisms enumerated by Rosenberg and others. For example, Dasguptaand David see the informational properties of science as a powerful analytical tool for studyingthe payoffs to publicly-funded basic research. Through information theory, Dasgupta andDavid suggest it is possible to develop a new economics of science, focusing on themechanisms engendered by information's public good properties. This new economics ofscience focuses on changes in the properties of knowledge brought about by new developmentsin information and communication technologies, such as the Internet. It suggests that thesenew technologies allow for an expansion of the informational or codified component ofscientific knowledge. It calls on policy makers to focus on expanding the distributive power ofthe innovation system through new information resources, such as electronic libraries(Dasgupta and David 1994, David and Foray 1995).The second strand in the new approach focuses on the properties of knowledge not easilycaptured by the information view described above. Influential here is the work of Pavitt andRosenberg, who stress that scientific and technological knowledge often remains tacit, i.e.people may know more than they can say (Rosenberg 1990, Pavitt 1991). 6 Moreover, thedevelopment of such tacit knowledge requires an extensive personal learning process. It isbased on skills accumulated through experience and expertise and often through years of effort.This perspective places great emphasis on the learning properties of individuals andorganizations. Apprehending the learning capabilities generated by public investments in basicresearch makes it possible to appreciate the economic benefits of such investments, Pavittsuggests (1991, p. 117). Of crucial importance in this approach are the role of skills, thenetworks of researchers, and the development of new capabilities on the part of actors andinstitutions in the innovation system. The approach we follow in this report owes much moreto the second strand of research than the first. The information–theoretic approach, developedby Dasgupta and David (1994), is still quite new and has yet to be validated by empiricalresearch, whereas the Rosenberg/Pavitt approach is grounded in a solid body of research inscience policy studies. At present, it offers a more productive line of inquiry into the issuesunder discussion.6 The concept of tacit knowledge originates in the work of the philosopher of science, Michael Polanyi, whodistinguishes between the two dimensions of knowledge - tacit and explicit (1966). For a stimulating application ofthis concept in the recent literature on innovation, cf. Nonaka and Takeuchi (1995).10
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