The New Production of Knowledge

The Dynamics of Science and Research in Contemporary Societies

Michael Gibbons, Camille Limoges, Helga Nowotny, Simon Schwartzman, Peter Scott, Martin Trow

• Publisher: SAGE Publications Ltd
• Year: 1994
• Print ISBN: 9780803977945
• eBook ISBN: 9781446228722
• Edition: 1
• Topic: Social Sciences
• Subtopic: Sociology
• Index: Social Sciences

In this provocative and broad-ranging work, the authors argue that the ways in which knowledge - scientific, social and cultural - is produced are undergoing fundamental changes at the end of the twentieth century. They claim that these changes mark a distinct shift into a new mode of knowledge production which is replacing or reforming established institutions, disciplines, practices and policies.

Identifying features of the new mode of knowledge production - reflexivity, transdisciplinarity, heterogeneity - the authors show how these features connect with the changing role of knowledge in social relations. While the knowledge produced by research and development in science and technology is accorded central concern, the authors also outline the changing dimensions of social scientific and humanities knowledge and the relations between the production of knowledge and its dissemination through education.

1

Evolution of Knowledge Production

Summary

In this chapter we begin by defining the distinctive characteristics of Mode 1 and Mode 2 knowledge production, emphasising that the latter has evolved out of the disciplinary matrix of the former and continues to exist alongside it. The new mode of knowledge production involves different mechanisms of generating knowledge and of communicating them, more actors who come from different disciplines and backgrounds, but above all different sites in which knowledge is being produced. The problems, projects or programmes on which practitioners temporarily focus constitute new sites of knowledge production which are moved into and take place more directly in the context of application or use. There is no pressure to institutionalise these activities in a permanent way or for participants to move permanently to a new institutional location. As a consequence, this dispersed and transient way of knowledge production leads to results which are also highly contextualised. Due to their inherent trans-disciplinarity they greatly enhance further diffusion and production of new knowledge through techniques, instrumentation and the tacit knowledge which move to new contexts of application and use.

One of the characteristic features of Mode 2 is its trans-disciplinarity. Another is what we call its social distribution, that is, the diffusion over a wide range of potential sites of knowledge production and different contexts of application or use. But the socially distributed nature of Mode 2 knowledge production is above all embodied in people and the ways they are interacting in socially organised forms. Hence, the emphasis on the tacit components of knowledge which we see as taking precedence over the codified components. While this leads to a gradual rapprochement of how knowledge production is organised in the academic cultures and in firms, the firm’s business strategy in organising its specific technological dimension acquires all the more importance in choosing its design configuration.

A crucial consequence resulting from the shift in knowledge production from Mode 1 to Mode 2 bears upon quality control. Its mechanisms and the criteria upon which it is based are bound to range also over a wider and more differentiated area, both along an institutional and a cognitive-organisational dimension inherent in quality control mechanisms. In general we claim that quality control too becomes more context- and use-dependent. In a more dispersed institutional space, quality control also takes on more transient and temporary forms and fluid norms. But above all, success is defined differently in Mode 2. It includes additional criteria to the traditional one of scientific excellence, such as efficiency or usefulness which are defined in tems of the contributions the work has made to the overall solution of transdisciplinary problems. In other words, the environment of research already structured by application or use will have to be taken into account, making room for multiple criteria not only in general, but also in relation to specific expectations and results.

In order to understand the dynamics of Mode 2 knowledge production better we draw a distinction between homogeneous and heterogeneous growth. With heterogeneous growth we refer to a process of differentiation and diffusion through which rearrangement of component elements takes place within a given process or set of activities. The process of heterogeneous growth is captured by us in a conceptual framework which we call the model of increasing density of communication. We maintain that the origins of the stupendous heterogeneous growth which is exhibited by the science and technology systems can be located on three levels of communication: communication between science and society, communication among scientific practitioners, and, metaphorically speaking, communication with the entities of the physical and social world. On all these three levels as well as through their interlinkages, communication density has increased in a dramatic fashion with the inbuilt heterogeneity providing a powerful predictor for further heterogeneous growth and its societal distribution.

Finally, we draw attention to some specific features of innovative activities in science and technology which fall under a Mode 2 production display. They are based upon the recovery of interest in specific, ordered structures, rather than the search for first principles and the concomitant distributive role that techniques and instrumentation, practical skills and tacit knowledge come to play. The second feature is innovation based upon knowledge of and practice through design. The intention here is to use the improved understanding of specific ordered structures to build, manipulate and control their operation in specific conditions and, perhaps even more importantly, for specific functions and purposes. The third feature contributing to innovation under Mode 2 conditions is the role that computers and especially computational modelling have come to play, opening the way to develop both routines that are independent of particular applications and hence can be used to meet a wide variety of uses and of building more sophisticated techniques and instruments that will enhance the design principle and its range of application.

The production of knowledge is advancing into a new phase. It operates according to new imperatives in tension with the traditional way of doing things with far-reaching implications. These changes are described in this book in terms of a shift in emphasis from a Mode 1 to a Mode 2. The main attributes of Mode 2 have already been summarily described in the Introduction. Mode 1 is discipline-based and carries a distinction between what is fundamental and what is applied; this implies an operational distinction between a theoretical core and other areas of knowledge such as the engineering sciences, where the theoretical insights are translated into applications. By contrast, Mode 2 knowledge production is transdiscipli-nary. It is characterised by a constant flow back and forth between the fundamental and the applied, between the theoretical and the practical. Typically, discovery occurs in contexts where knowledge is developed for and put to use, while results – which would have been traditionally characterised as applied – fuel further theoretical advances. Discovery in the context of application in the case of hypersonic aircraft is illustrated in Box 1.1. Mode 2 is characterised by a shift away from the search for fundamental principles towards modes of enquiry oriented towards contextualised results. Further, the experimental process itself is increasingly being guided by the principles of design, originally developed in the industrial context. It is becoming possible to reverse the conventional procedures for making certain substances, such as molecules, chemicals and materials. For example, some materials can now be built up atom by atom, or molecule by molecule, by design, in order to obtain a product with specified properties. In this, the product and the process by which new materials are made become integrated in the design process, implying a closer integration of the process of discovery with that of fabrication. Mode 2 creates a novel environment in which knowledge flows more easily across disciplinary boundaries, human resources are more mobile, and the organisation of research more open and flexible.

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Box 1.1

Discovery in the context of application: the case of hypersonic aircraft

Some research programmes, although industrially-oriented, may deal with scientific and technological questions well beyond the current frontiers of knowledge and so suggest new problems and shape new research agendas. This situation is well illustrated in the search for a viable hypersonic aircraft now being undertaken by many nations.

Scientists have long contemplated the construction of an aircraft capable of attaining satellite speeds, taking off like a regular airplane and returning to earth once its mission is accomplished. The success of this project depends on solving the problem of propulsion generated by aerobic motors which use air as the combustant rather than an oxygen mass.

However, at hypersonic speeds beyond Mach 6 supersonic combustion becomes necessary, requiring the difficult merger of aerobic principles with hypersonic speed in the perfecting of a supersonic ramjet, scramjet. The production of a new vehicle is thought to require a change in technological paradigm. There is a belief that conventional aerobic propulsion systems cannot function at hypersonic speeds. Paradigmatic change implies discontinuities, scientific as well as technological. The two traditional supports for the elaboration of new technological concepts, science and the design experience of previous technological generations – the supersonic ramjet, in this case – can provide only certain, limited guidance. In the case of hypersonic technologies, the state of science does not yet permit the development of predictive models and therefore is of limited usefulness in the elaboration of designs and innovation.

Lack of direction from existing science. In the case of combustion at Mach 5 to 6, the first barrier to investigation is the near impossibility of producing experimentally, on the ground, the data necessary to predict the performance of the scramjet concept. There are no installations capable of reproducing the combination of speeds, pressures and temperatures necessary to simulate hypersonic flight. Wind tunnel experiment can only be of short duration – a few seconds. This weakness is partly overcome by mathematical simulation methods. Here, however, there are also immense difficulties. The solution of supersonic combustion equations would require very long calculation times. The simulations therefore comprise significant approximations. Another crucial problem is the absence of a predictive law for turbulence. Finally, simulations do not eliminate completely the need for tests on real vehicles. Calculations may none the less minimise the quantity of experimental work necessary. They enable researchers for example to limit wind tunnel tests to those precise areas where simulations are too difficult or do not provide sufficiently precise results. In the final analysis the current difficulty of ensuring synergy between calculations and real tests reveals that science is still far from being able to provide predictive models for innovation and analytical design.

Discontinuities with previous experience. A further problem is evident in results obtained at the threshold of Mach 5 many of which are no longer valid beyond Mach 5. Certain physical-chemical laws are even reversed once one passes from the supersonic domain to the hypersonic. Different concepts need to be developed for the different velocity regimes. There is therefore a discontinuity between supersonic and hypersonic domains which precludes evolutionary development based on modest additional investments in human and physical capital. In addition, the analogical links between aerobic propulsion and rocket propulsion are relatively insignificant. They do not allow for more than a small likelihood of transferring knowledge from one domain to the other.

In this situation of uncertainty the primary need is for information on the very structure of problems involved and to overcome a critical lack in the scientific data necessary for the operations of measurement, test, control and trial. New instruments, techniques and knowledge are required. Currently many hypersonic programmes’ research are oriented towards the production of such an instrumental basis.

The point is that this research phase precedes basic and applied research and contains a strong technological dimension. The formulation of this research agenda itself cannot be understood without paying attention to prior developments in the realm of technology, particularly instrumentation technology. This will structure the context of application and set future problems for scientists and engineers from many backgrounds.

Source: Foray and Conesa (1993)

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Mode 2 is spreading across the entire landscape of science and technology. The proliferation of sites outside of normal disciplinary structures and institutions developed since the turn of the nineteenth century, in which recognisably competent research is taking place, opens up a vast field of interconnections. As interactions multiply, the epistemological status of the knowledge thus produced does not follow traditional, that is, disciplinary criteria. In Mode 1, any knowledge is validated by the sanction of a clearly defined community of specialists. In transdisciplinary Mode 2, such legitimating structures are either lacking or dysfunctional. Transdisciplinary research also needs some legitimating procedures, but they are different because different criteria are being applied to what is considered good research. Moreover, with the broadening and relatively transient character of the communities of practitioners involved the assessment of knowledge will occur through a much stronger societal contextualisation.

Science does not stand outside of society dispensing its gifts of knowledge and wisdom; neither is it an autonomous enclave that is now being crushed under the weight of narrowly commercial or political interests. On the contrary, science has always both shaped and been shaped by society in a process that is as complex as it is variegated; it is not static but dynamic. The range of possible problems which could be tackled by science is indefinitely large and therefore the research agenda cannot be understood in purely intellectual terms.

Science possesses a variegated internal structure, made of a vast number of communities or specialisms, each with distinct forms of practice and specific modes of internal and external communication. In fact, so diverse are the activities that comprise the scientific enterprise that it is perhaps misleading to group them under a common label. Contemporary science appears to be in more or less continuous flux, a state of turbulence which contrasts sharply with the perception of science as a socially autonomous enterprise with stable institutions, well delineated disciplinary structures and ageing slightly remote practitioners.

In Mode 1 disciplinary research, the term paradigm is used to denote a provisional consensus among the relevant set of practitioners. It is the result of a particular mode of organisation, and it denotes a way of seeing things, of defining and giving priority to certain problem sets. Many scientists are employed by universities, work within the structure of a particular specialism, and regularly teach within a disciplinary structure. However, in that seemingly comfortable world they have had to evolve a wide range of strategies for survival. Personal research strategies have become necessary because the scientific enterprise has grown to such proportions that resources must be allocated to those who demonstrate continuous creativity. The more astute researchers in trying to balance their need for equipment and staff with the need to work within a given paradigmatic structure, build their careers around a broad base of research funding. They work on problems that are intellectually challenging and interesting enough to catch the attention of relevant peers and a range of funding agencies, and they try to establish their particular ideas, theories and methods as paradigmatic, that is, as the way to do things. By contrast, scientists who refuse to take a strategic approach to their careers face the prospect of being left behind as research councils, foundations and even universities adjust their resources to new horizons. Such scientists will be chronically short of research funds, become relatively unproductive and, in the end, come to be judged by their peers as mediocre performers. In this situation, the ability to raise funds becomes, in itself, an indicator of success.

By adopting a strategic approach to their careers, many scientists have become entrepreneurs and have had to loosen their disciplinary affiliations while contributing to the blurring of subject boundaries. Scientists have long appreciated that there is no intrinsic reason why the funding strategies of governments, firms, or foundations should conform to the current internal, cognitive structure of their discipline. Over the years, they have exercised great ingenuity in translating their own research interests into the language appropriate to other agendas. This has generated an awareness of problems beyond the immediate concerns of particular specialisms. Working in a problem context tends to improve appreciation of the importance of transdisciplinarity and also softens the distinctions between pure and applied science, between what is curiosity-oriented and what is mission-oriented research. The constant search for funds has indirectly increased the permeability of knowledge. To the extent that the imperatives of a problem context require cooperation or networking with other practitioners, whether in industrial, governmental or university laboratories, whether nationally or globally, the hold of established modes of knowledge production is weakened. In brief, much of the impulse for a shift to Mode 2 knowledge production has been endogenous to the practice of Mode 1.

All these changes are reflected in the ethos of the newest fields. The development of science has now reached a stage where many scientists have lost interest in the search for first principles. They believe that the natural world is too complex an entity to fall under a unitary description that is both comprehensive and useful, in the sense of being able to guide further research. In fields such as genetic engineering and biotechnology, information theory and information technology, artificial intelligence, microelectronics, advanced materials, researchers do not concern themselves with the basic principles of the world but with specific ordered structures within it (Barnes, 1985). The current upsurge of interest in applications is only partly a reflection of the persistence of commercial and military interests in science and technology. Equally important has been the shift of interest within science to the understanding of concrete systems and processes. This is reflected in the shift in emphasis from Mode 1 to Mode 2.

Though we have so far spoken mainly of science, the trend described obtains no less in technology. Indeed, the distinction between the two is becoming in most regards highly questionable. The idea that technology is also a form of knowledge is obscured by the tangibility of its artefacts. Artefacts are the outcome of a transformation process in which energy and matter in one form are transformed into energy and matter in another, often with better performance characteristics along some dimension. The aim of generating technology is to improve performance by rearranging existing elements. Though we are familiar with the outputs of various transformation processes, these artefacts often conceal their most basic constituents.

To concentrate on technology as artefact means keeping the lid very firmly on the ‘black box’ in which the transformation process occurs. It obscures the role of knowledge as a key element in this process. Only by opening the black box can the cognitive dimension of technology be unravelled. Certain commonalities in the ways in which scientific and technological knowledge are produced are then highlighted and the process by which science, technology and industry are being brought into closer contact is clarified.

Technology as a form of knowledge displays some of the traits of the paradigmatic structure of disciplinary science. Technological knowledge is a mixture of codified and tacit components. Codified knowledge need not be exclusively theoretical but it needs to be systematic enough to be written down and stored, whether in a computer database, a university library or in a research report. As such, it is available to anyone who knows where to look. Tacit knowledge, by contrast, is not available as a text and may conveniently be regarded as residing in the heads of those working on a particular transformation process, or to be embodied in a particular organisational context. The distinction between codified and tacit knowledge can be complemented by a parallel distinction between migratory and embedded knowledge. The former is mobile and can move rapidly across organisational boundaries, while the latter is less so because its movement is co...

Table of contents

• Cover Page
• Title
• Copyright
• Contents
• Preface
• Introduction
• 1 Evolution of Knowledge Production
• 2 The Marketability and Commercialisation of Knowledge
• 3 Massification of Research and Education
• 4 The Case of the Humanities
• 5 Competitiveness, Collaboration and Globalisation
• 6 Reconfiguring Institutions
• 7 Towards Managing Socially Distributed Knowledge
• Glossary
• Further Reading
• Index