The linear model did not exist: Reflections on the history and historiography of science and research in industry in the twentieth century

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1 The linear model did not exist: Reflections on the history and historiography of science and research in industry in the twentieth century i David Edgerton in Karl Grandin and Nina Wormbs (eds), The Science Industry Nexus: History, Policy, Implications. (New York: Watson, 2004) The linear model has become a term of art in studies of science policy and innovation, and in some historical studies of science and technology. ii It is, like technological determinism and Whig history of science and technology, an invention of academic commentators. iii Like these, but unlike scientific revolution or big science, linear model was not meant to be an analytically useful concept: it is there to be condemned as simplistic and inaccurate. It is a foil for the more elaborated academic account, in short, a classic straw man. But it is more than a straw man: although it is of recent invention, some students of science and technology have given the model historical agency. They have come to believe that it existed in the minds of academic analysts and key policymakers of the past, and that it had a powerful influence on policy and practice. Worse still, the idea of the linear model often locks even critics into a concern with basic science, even in the study of innovation : proponents (such as they are) and critics, share a model of science in which science is academic research. In this model studies of academic research are privileged, as is innovation in such studies. I will argue that using and criticizing the term linear model avoids critical engagement with the much richer models of innovation developed by academic specialists in innovation, as well as many crucial historical actors. Accounts of innovation in the 20th century, and indeed science in industry in the 20th century, more usefully start from a conceptual frame quite different from either the linear model or the usual criticisms of the model. In particular the history and historiography of non-academic research is a key resource. For example, the history of industrial research and of science in industry, and new accounts of military research and development both significantly often treated as part of the history of technology provides a rich alternative reading of the history of twentieth century science, including the development of academic science, big science, interdisciplinary research, and more obviously the industrialization of research, which historians of science should pay attention to. iv We need to be careful, however, because the academic research model has affected even our understanding of science in industry and the military. Industrial and military 1

2 research and development was much more than central corporate or government research laboratories. I argue that we should go further still, and note the systematic conflation between science and research: most research is not academic, and most science is not research. Finally, I will argue that the case of the linear model allows us to reflect on the general tendency to attack straw men in academic studies of science and technology, and on the lack of cumulation in the historiography of science and technology. What is The Linear Model? The linear model is clearly a term of art, but one that is rarely if ever closely defined. The term tends to be used in the sense of a model of innovation, rather than say, science, but most commonly it is a model of the interaction of science and society, and science and economic performance specifically. The model is often presented diagrammatically, as in Figure 1, and comes in many variants. The lack of clarity, the lack of consensus, or indeed debate over the details of the model is itself indicative that we are not dealing with a worked-out model which anyone ever believed in. Yet we can usefully distinguish some common themes. The linear model incorporates three elements the nature of the sources of innovation, of the innovative process, and the effect of innovation. The linear model is usually taken to be something like the following: basic or fundamental, pure or undirected, scientific research is the main source of technical innovation; the process of innovation is a sequential one, by which discoveries arising in such research are developed in a sequence through applied research, development and so on, to production. Overall, the innovation produced is the main source of economic growth. v This reading is very close to what Donald Stokes takes the linear model to be, in his recent study of science policy, as I discuss further below. vi Although is it is often described as a linear model of innovation, even when described in this way, it includes a model of effects of innovation: For example, Harvey Brooks describes the linear-sequential model of technological innovation in which radical innovations are triggered by new scientific discoveries and become foci for the growth of new industries and, thereby, sources of economic growth and employment. vii Yet stated as clearly as above the linear model is very hard to find anywhere, except in some descriptions of what it is supposed to have been. The most brazen propagandist for scientific research would wish to avoid formulations which so explicitly beg so many questions: the linear model not only did not exist, but it could not exist as an elaborated model. 2

3 [FIGURE?] That the linear model has been significant is not itself a straw man. By the 1990s the linear model and the linear model of innovation were terms in very widespread use in the academic and official literature (as a check with a search engine, or leafing through the pages of specialist journals like Research Policy will verify). It is always, however, something that was surpassed, criticized, to be moved beyond. viii That there was widespread discussion of the linear model was often commented on in academic literature in the 1990s. In 1993 I claimed that there is much condemnation of the so-called linear model of innovation: the argument that science, leads to technology, and thence to economic growth. ix By 1995 one paper in Research Policy was claiming, The linear model of innovation is the key reference point for understanding the relationship between science, technology and economic development. x The doyen of innovation studies, Chris Freeman, writing in 1996, noted that at one time it was almost impossible to read a book or an article on technology policy or technological forecasting that did not begin or end with a polemic, against the so-called linear model of innovation. xi Freeman himself suggested that The linear model cannot [ ] be dismissed simply as a convenient straw man erected for the convenience of those expounding alternative ideas. xii Ernest Braun, another veteran science policy academic, and around the same time, complained about the tendency to attack the crudest linear models, which in effect no one had ever believed in. xiii The linear model is a term of art without a history. As far as I know no-one has enquired into the origins of the term linear model, though the idea that is a recent creation as implied in one useful account of the concept in the context of science parks: Doreen Massey and colleagues see the linear model as used in Britain as something recent, developed out of a particular historical account of science and industry in British history. xiv If the term has no history, the underlying concept, has a very elusive one. Many accounts imply and some state (as I show further below), that the model was central to Vannevar Bush s Science: The endless frontier, and that this was the key to the influence of the model. A recent example is found in an essay review in Isis where it is noted that historians have grown skeptical of the interpretative reliability of the so-called linear model of science-push innovation, which, as popularized by Vannevar Bush and others, became an axiom of faith for many who drove and defended science and technology policy for over fifty years. xv 3

4 Origins The earliest use of the term linear model in the context of innovation appears to be by William J. Price of the US Air Force Office of Scientific Research, and L.W. Bass of Arthur D. Little, in They argued, in Science, that Innovation is often viewed as an orderly process, starting with the discovery of new knowledge, moving through various stages of development, and eventually emerging in final, viable form. According to this linear model, innovation seems to be a rational process, essentially similar to the other, more systematic functions of an organization. The assumption is that it can be analyzed into component parts and controlled rationally that is to say, planned, programmed, managed much as other, more routine activities are. By contrast they argued that studies of innovation showed that the linear model was not typical, that the innovation process was irrational and could not be programmed in advance. xvi If this is indeed the origin of the term, then from the first it is a term of criticism of a particular set of views of innovation. Interestingly, the view of innovation criticized is richer than the later linear model, and so indeed was their criticism. They observed that in the Second World War, researchers brought many innovations forward. These researchers, were acting as technologists, and not, they argued, as was often suggested, as basic researchers. They also criticized the standard postwar view that innovation was a rational ordered plannable process. This view, it should be noted, was most radically and interestingly outlined by Schumpeter, and much criticized by later neo-austrian economists with interests in science, like John Jewkes. xvii The second use of the term that I know is also specifically concerned with innovation, and is also richer than later versions, though in another way. The once well-known British collection of case studies of innovation, Wealth from Knowledge, published in 1972, discusses and criticizes linear models of innovation. It takes then to be of two very different types neither of which corresponds to the idea of the linear model in use today. The authors distinguished between the discovery push and the need pull linear models, and then broke them down further into four in total: 1) the science discovers, technology applies model, 2) the technological discovery model 3) the customer need model and 4) the management by objectives model. They go on to claim that few of their cases fit any of these models; they 4

5 criticize them all. xviii The specific idea that basic or fundamental research was the main source of innovation (model 1) they saw as widely held, and often regarded as self-evident but they noted how rarely substantiated claims were made for it. xix Edwin Layton, citing Wealth from Knowledge, noted in the mid-1970s that there were a variety of models of technical development, but that all of these models postulate linear-sequential models of the innovative process, in which the linear sequence of cause and effect, followed from the first event. He agreed strongly with Wealth from Knowledge that actual innovation did not proceed in this linear-sequential way. xx By 1985, according to one study, there were two traditional models, the demand-pull and supply push. xxi However, the use of the terms the linear model or many linear models appears to have been very rare indeed before the mid-1980s. It is particularly significant that it is not used in most of the important work on innovation of the time. Nathan Rosenberg does not seem to use the terms at all in his seminal collection of papers from the 1960s and 1970s Perspectives on Technology. xxii Although the nature of innovation, and its sources, are central themes Rosenberg discussed the work of Schmookler and Schumpeter, Marx and Engels, and many other economists and economic historians, none of whom were anywhere near endorsing the linear model not least because they adopted much richer positions. Chris Freeman s standard text, The economics of industrial innovation (second edition, 1982), doesn t mention linear models either. This is especially relevant because he was concerned not just with industrial innovation, but also government policy. Freeman indeed divides the post-war years into two phases of government science and technology policy : the first had a strong supply side emphasis on building up strong R&D capability. He very clearly has in mind not pure science, or academic research, but mainly large-scale R&D projects military and civil in principally in the atomic and aeronautical fields. Freeman s second phase dates from the late 1960s had a stronger demand orientation, and was influenced, as he sees it, by economic, political and environmental critiques of the supply side approach. xxiii Nor is the linear model there in more detailed work on these topics in the pioneering days of the journals Science Studies, or Research Policy, which started publication in the early 1970s. xxiv It is missing from the seminal 1977 paper by Nelson and Winter In search of a useful theory of innovation, xxv and the well-known empirical study on the sources of invention by Vivien Walsh. xxvi Indeed to this day much good work in historical and other studies of innovation does not feel the need to invoke the linear model. For example, 5

6 Mowery and Rosenberg s book of 1989 does not appear to mention linear models, xxvii nor do some more recent good textbooks on technology and society, by for example, Rudi Volti and Kurt Jacobsen. xxviii Historical studies of US and British science policy do not generally use the term linear model, xxix and key reviews of the economics of science and innovation don t mention it either. xxx However, since the 1980s the term the linear model [of innovation] has become a standard term in much of the literature, extending to historical work, to describe what is taken to be a standard or traditional position. Use of the term diffused very quickly, together with the assumption that it was dominant even in the academic literature on science and technology. As already noted, it always referred to a position that had been criticized and/or should be criticized as a myth, but was itself allegedly prevalent and influential. The first academic use of the term in the singular, common form of linear model dates from It is due to Stuart MacDonald, and is as follows: Although a staunch defense of the linear model of innovation [ ] would be rare, it is very convenient when dealing with such an uncertain process as technological change to assume that everything hangs on research. xxxi A paper by S.J. Kline on industrial innovation (from 1985), credits the Price and Bass paper of 1969 with the term linear model, referring specifically to the idea of innovation an orderly process starting with the discovery of new knowledge. Kline recognizes that Price and Bass saw this as an inadequate model, but he sees the model as central: the linear model continues to underlie the thinking in many current speeches and much writing, seeing it as implicit in push-pull models, and in the very term R&D. He goes on to claim, no other model has been available. In this case, as in others, it is unclear what exactly is being referred to since no examples are cited, nor is the prevalence of the argument examined, nor is it clear whether the market-pull linear model is taken as a linear model or not. xxxii But one 1988 textbook already refers to the notion that technical innovations result from the application of new scientific insights and ideas. Such a notion is often referred to as the linear model of innovation. xxxiii The term linear model quickly came to be used in papers concerned with new theoretical approaches to the history and sociology of science and technology. Trevor Pinch and Wiebe Bijker, in their well-known joint manifesto for SCOT (social construction of technology) found it useful to attack the widespread use of simple linear models to describe the process of innovation. Although they refer to models in the plural this is because The number of developmental steps in these models seems to be rather arbitrary [ ] and varies. They 6

7 clearly have academic studies in mind since they suggest that they have contributed a great deal to understanding of conditions of economic success in technological innovation; they cite no examples, and claim that such models are not of interest to them because they ignore technical content! They also claim that their multi directional model is preferable to the linear model, which they see as important in many innovation studies and much history of technology. xxxiv In this latter case the linear model does not seem to be focused on basic research. Pinch and Bijker were not alone in making use of the linear model as something for new approaches to compare themselves with. Arie Rip noted in a paper given at a conference of historians of science and technology specifically discussing science-technology relations: It is convenient to start with a brief discussion of the so-called linear model of the relation between science and technology. That technological innovation derives from scientific discovery, as it were in a linear sequence, is a myth, but a prevalent myth. As a myth it is tenacious because of its links to important legitimations of science as the horn of plenty, and of technology as the magic wand. The linear model has some truth in it, but it hides more than that it helps our understanding. xxxv Did the Linear Model exist by Other Names? If, as seems clear, no academic study of innovation, has ever proposed or defended a linear model of innovation it does seem rather odd that historians of sociologists of science and technologists of the 1980s came to believe that this had been so. Perhaps this was because a linear model had been implicit in such literature. And yet, as we have see a generation of researchers working in the 1960s and 1970s was clearly either indifferent to or hostile to any implicit linear model. But even the earlier academic literature, is not dominated by an implicit the linear model. Take the British economists Charles Carter and Bruce Williams who did a great deal of empirical work on innovation in industry in the 1950s. xxxvi They warned of the likelihood of overestimating the value of research in industry. In some firms it was too academic too little oriented towards commercial needs. The misconception underlying the latter waste of scarce scientific resources is that research is naturally a 7

8 left-to-right process that is fundamental research produces something which is communicated to the industrial scientist, who performs some applied research and communicates the results to someone else who takes matters a step further. We have not found any cases of successful industrial research where this movement was not accompanied by movement in the opposite direction. xxxvii Carter and Williams found in their studies that the majority of projects started outside R&D laboratories. If there was a linear model it was a bi-directional one, which surely doesn t count. xxxviii Clearer still is the case of The Sources of Invention by John Jewkes and others of 1958: it has powerful criticisms of many different assumptions that were made about many aspects of invention. They argued that the relations between science and technology were simply not known, that it was not obvious that the scientifically most wealthy country would be the richest, and warned against investing in pure science in the expectation of a payoff. xxxix Sources of Invention was particularly notable as a neo-liberal attack on the bureaucratization of innovation, and the assumption that it was predictable, an important element in one early version of the linear model, as we have seen. More generally, in the 1960s at least, economists pointed to the clear lack of positive correlation between expenditures on research and development and economic growth a clear general argument against the linear model at the macro-level. xl At the same time there was a great emphasis on demand-pull models of innovation. It is thus difficult indeed to argue that economists put forward, or believed in, the linear model of innovation. They certainly distinguished between science, invention, innovation, diffusion and so on, but that doesn t amount to a model of innovation. The closest I could find to an endorsement by an economist, and then only for heuristic purposes, of something that looks like a linear model, is in a textbook by Rosegger of the 1980s, which refers to stage models. xli On another dimension it is clear that historians of technology rejected the model of science-technology relations implicit in the linear model, even in the 1940s and 1950s. xlii My claim is then, that the linear model did not exist in even the earliest generations of academic work on innovation. Did then the linear model exist elsewhere, for example in the in the writings of scientists and engineers? The academic students of innovation, going back to the 1950s, are all criticizing something which looks a bit like the linear model. Certainly something like it can be found, not least if we see it as a general argument in favor of the utility of theory as well as practice, of pure as well as applied science and for the 8

9 importance of fundamental and basic research. There is little doubt, for example, that academic research scientists have long made, and continue to make, exaggerated claims for the significance of their work for technological and economic development, and that agencies which came to fund them did the same. These arguments have often had the aim of securing state support. We could, if we wished, label these obviously self-interested claims the linear model, but to call the propaganda of academics the linear model is to flatter the claims, and to avoid stating the obvious: that these are generally claims by academic researchers for the power of academic research. To call it a linear model, also runs the risk, especially in the context of the current use of the term, of smuggling in the assumption that what academic research scientists said about innovation was the most influential discourse of innovation around. In other words, to believe that ideas about innovation were created by academic research scientists, and diffused out to engineers, to government, to industry and to the public; to believe in a linear model not of innovation, but of ideas about innovation. That second linear model is already implicit in the much literature in the history of science, and even technology. What models of innovation, public and private, where used by government officials, industrial researchers, academics, is an open historical question. It is, however, worth presenting some tentative arguments, if only to stimulate research. Firstly, non-academic scientists and engineers have often been resistant or indifferent to the linear model. For the US case, George Wise was clear that the assembly line model was the product of the science-policy elite and not more widespread than that. xliii In a 1946 British conference concerned with industrial research, the closest thing to a linear model is the claim that while day to day advances came from industrial research, really spectacular advances and the creation of new industries came from fundamental research, but this was from the government official who was charged with funding such research. xliv The papers of a conference of US industrial research managers of 1954, reveals no explicit or implicit linear model in its deliberations. xlv In 1960 the research heads of important US companies were presented with a question: why was there such a lag between scientific discovery and industrial and military application in the USA and the free world; there was a concern that the Soviet Union was doing better. The questioners wanted ways to shorten the pipeline between original scientific discovery and engineering application. xlvi The question assumed the linear model but the answers from directors of research, chief engineers and so on, are notable for questioning the question. The 9

10 lag was shortening, said some, it was inevitable said, others, they assumed the question referred to many different processes, and so and so forth. It clear that the managers were not thinking is anything like as simplistic a way as the question implied. The linear model was not the common understanding in industry. Second, while academic research scientists arguments have generally been crude and repetitious they also often showed a richer and broader understanding of the role of academic research than the crude linear model (involving training of scientists and engineers, for instance). Thus Vannevar Bush s famous 1945 report Science: The endless frontier is much more subtle and interesting. This is a key case because in academic works which refer to the linear model it is typically the only cited work which predates papers critical of the model from the 1980s. Many commentators are explicit in their attribution of the model to Bush, and/or see Bush as its most influential exponent. Chris Freeman has claimed that Science: the endless frontier did indeed outline a linear model of science, technology and innovation, and [ ] was certainly influential among policy-makers. xlvii More recently, Donald Stokes notes a postwar paradigm exemplified by Science: The endless frontier. xlviii He sees the paradigm for science policy as resting on the view that basic science should be unconstrained, and that this will lead to technological innovation, which became what he calls the familiar linear model when extended through to production. xlix Stokes argues that Bush endorsed a strong form of the linear model basic advances are the principal source of technological innovation [original emphasis], noting too the use of the term technological sequence by the National Science Foundation in the early 1950s. l Elsewhere Stokes notes, Nothing in Bush s report suggests that he endorsed the linear model as his own, though he did assert that scientific discoveries are a source of technological progress. li We need to clarify what Vannevar Bush was arguing, and not arguing, in his supposedly foundational text. lii Another Look at Science: The Endless Frontier Vannevar Bush was the wartime Director of the US Office of Scientific Research and Development, one of the many US agencies concerned with warlike R&D. In FY 1945 the OSRD spent around $100m, the US Army and Navy $700m between them and the Manhattan Project $800m. liii His Science: The endless frontier was a proposal for very particular policies concerned with a small part of postwar research. The report is not concerned with innovation nor with how this should be organized, thus it could not even implicitly set out a linear model 10

11 of innovation. The term linear model is nowhere used. Bush was arguing for the public support of basic liv science in universities at a time when he thought the growth in such research had failed to keep up with the huge rises in government and industrial research both of which were overwhelmingly and necessarily applied. lv He did not (as many later analysts have done when thinking in the linear model terms they supposedly abhor) conflate policy for academic research, with policy for innovation. Thus Expenditures for scientific research by industry and Government almost entirely applied research have more than doubled between 1930 and Whereas in 1930 they were six times as large as the research expenditures of the colleges, universities, and research institutes, by 1940 they were nearly ten times as large. And he went on to note, expenditures for scientific research in the colleges and universities increased by one-half during this period, those for the endowed research institutes have slowly declined. The war made things worse: We have been living on our fat. For more than 5 years many of our scientists have been fighting the war in the laboratories, in the factories and shops, and at the front [ ] they have been diverted to a greater extent than is generally appreciated from the search for answers to the fundamental problems from the search on which human welfare and progress depends. The key point was that If the colleges, universities, and research institutes are to meet the rapidly increasing demands of industry and Government for new scientific knowledge, their basic research should be strengthened by use of public funds. It is easy to find in it claims which we might loosely take to be the linear model, for example, to secure a high level of employment, to maintain a position of world leadership the flow of new scientific knowledge must be both continuous and substantial. Or, There must be a stream of new scientific knowledge to turn the wheels of private and public enterprise. Or, Today, it is truer than ever that basic research is the pacemaker of technological progress. Or, that the universities, and other centers of basic research, were the wellsprings of knowledge and understanding. As long as they are vigorous and healthy and their scientists are free to pursue the truth wherever it may lead, there will be a flow of new scientific knowledge to those who can apply it to practical problems in Government, in industry, or elsewhere. Crucially however, he never claims basic research as the main source of invention, or innovation, and indeed he sees basic research as leading not to new products 11

12 or processed, but repeatedly to knowledge and to understanding (terms which I have italicized in the quotations). Thus basic research results in general knowledge and an understanding of nature and its laws. This general knowledge provides the means of answering a large number of important practical problems, though it may not give a complete specific answer to any one of them. lvi Universities were uniquely qualified by tradition and by their special characteristics to carry on basic research. They are charged with the responsibility of conserving the knowledge accumulated by the past, imparting that knowledge to students, and contributing new knowledge of all kinds. For the US could no longer count on ravaged Europe as a source of fundamental knowledge. In the past we have devoted much of our best efforts to the application of such knowledge, which has been discovered abroad. In the future we must pay increased attention to discovering this knowledge for ourselves particularly since the scientific applications of the future will be more than ever dependent upon such basic knowledge. Indeed his own model is not so much a linear chronological one, though that element is there, but a spatial one, in two senses. First, different kinds of scientific activity take place in different spaces, and secondly, the extension of scientific knowledge creates a new enlarged arena for the actions of others. That is the significance of the term endless frontier for, as Bush noted, it was an established policy of the US government that new frontiers shall be made accessible for development by all American citizens. As Arie Rip points out, Bush had a reservoir model of the role of basic science, and indeed was somewhat avant la lettre here. lvii However, the idea that what basic academic research produced was knowledge was not unique to Bush. For example a 1931 study of US industrial research, which like Bush highlighted the relative numerical strength of industrial to academic research, claiming a ten-fold advantage, saw the industrial applied researchers looking to the pure scientists for fundamental information [emphasis added]. lviii The same study saw industrial research as the managerial means for the systematic application to technology of the fundamental knowledge gained by pure science [emphasis added]. lix In Britain there was no equivalent to the Bush report, not least because Bush s central claim was unnecessary: the state had long funded academic research by direct support of universities and of university research via the so-called research councils, including the Department of Scientific and Industrial Research (DSIR). But while there was indeed strong support for such research after the Second World War, and it did indeed increase, it is hard to see a linear model in operation even for basic research. Sir Henry Tizard, the chief government scientific adviser for both the civil and military side in the immediate post-war 12

13 years, and a former head of the DSIR, clearly did not believe in the linear model. In his presidential address to the British Association for the Advancement of Science in 1948, he asked: to what then shall we attribute the relative decline [of Britain as a great power]? Shall we argue that a main cause was that research was on too small a scale? He preferred other reasons, noting that Sweden and Switzerland had strong technology, but no great strength in research. His view was that it is not the general expansion of research in this country that is of first importance for the restoration of its industrial health, and certainly not the expansion of government research remote from the everyday problems of industry. What is of first importance is to apply what is already known. lx That view may not be incompatible with elements of the standard linear model, but it is different from and richer than the whole linear model. Putting the Linear Model into the History of Science Policy There is a suggestion in some of the more recent literature that something very close to the linear model was the core idea in science and technology policy after 1945, at least into the late 1960s. Many historical studies of US and British science policy, even if they do not use the term linear model, refer to articles of faith and paradigms amongst which was support for basic research on economic grounds, going beyond a science policy elite. lxi Bruce Smith, writing of US policy notes that: While a healthy basic research effort as the lynchpin of the system was a primary article of faith, the consensus was broad enough to include those who wanted more basic research, and those who had doubts, because there was money for all. lxii In the non-academic literature, the linear model looms large as the core of post-war policy, with implicit and explicit reference to Vannevar Bush. The first example refers to Britain: science was seen as the engine of progress and as such worthy of State patronage. The science policy debate therefore focused on the resource inputs into science, in the belief that if a country had a sufficient investment in basic science then technological innovation, economic growth and social progress would surely follow. Within this science push phase, the chief policy issues concerned the funding of big science, above all nuclear research; the search was for criteria for choice. Below this strategic level (in which scientists themselves played a considerable part), the chief mechanism for resource allocation was peer review. Phase 1 took a fundamentally optimistic view of science as a quest an endless frontier. Serendipity would take care of the rest. This 13

14 linear model of science pushing technology, which policy-makers once saw as a selfevident truth, has long since gone as the relationship between basic science and technological innovation has come to be understood as highly complex and quite difficult to influence. lxiii The second example is a US embassy summary of a Chinese document on science and technology policy, which testifies to the ubiquity of the model: Since 1945 the United States has followed the basic research to applied research to product development linear model propounded by President Roosevelt s science advisor Vannevar Bush in his 1945 book Science the Endless Frontier. According to this view, which has been fundamental to U.S. S&T policy, basic and applied research are distinct and not complementary. lxiv If the content of Science: The endless frontier is misrepresented so its influence is exaggerated. As historians have long pointed out, its main recommendations were ignored. Basic research was increasingly funded by government, but neither by the agencies or in the spirit proposed by Bush. For while Bush proposed the support of basic science across a wide field by a new agency, many different agencies were to do so, above all the Office of Naval Research, the Atomic Energy Commission, the National Institute(s) of Health, and so on. When the National Science Foundation was formed in 1950, it was an addition not a substitute: the ONR dominated basic research into the early 1950s, even in the early 1960s the NSF supported less than 10% of all basic research, and less than 15% of all federally-funded basic research. lxv The Department of Defense was still supporting as much as 44% of federally funded basic research in universities and colleges in lxvi Did these funding agencies really believe in free untrammeled university research directed only by curiosity, as the linear model analyses of post-war science policy would imply? Historians are clear: in the case of physics the military did not believe they were funding generic fundamental science even if the recipients often claimed this. lxvii The ONR did not operate peer review as its main allocation process it relied on program managers. lxviii Forman notes that the military spent 5% of the military R&D budget on basic research, not because this was what was needed to feed technical development, but because it was a convenient proportion. lxix Furthermore, In truth, only a small fraction of that 5% of R&D funds labeled basic research went to support investigation that could reasonably be called fundamental. lxx By which he 14

15 means much was devoted to techniques and applications. It was a physics as the military funding agencies would have wished. lxxi Academic physics was not in command, it was being used, and they had lost control of their discipline. lxxii The linear model never dominated innovation policy; nor did it dominate narrower science policy. Academic historians and other analysts have, by granting so much attention to policy for basic or fundamental research, reproduced the focus of the linear model they criticize, and shared its assumption that what really mattered was this high level stuff. The rest is merely derivative. The problem is that the great bulk of research and development (which is better described as development and research) was not basic or fundamental or thought of in terms of the linear model at all: it was driven by quite different concerns. At best the fundamentalists, to call them something, were arguing for a small space for fundamental research in a world of applied, directed, and controlled research. They had to argue against large constituencies of technical experts and researchers and users, who demanded control and direction of research and development, and did indeed control most research and development. It may well be the case that the fundamentalists succeeded, relatively, in increasing the proportion of fundamental or basic research in total research and development, but not that fundamental research ever dominated. And yet that is what much commentary on postwar research and development and innovation policy implies. Histories of Twentieth Century Science Most histories of twentieth century science are concerned with the academic basic science that Bush wanted to promote, and the agencies that did indeed promote them: that, or something like it, is what science is taken to mean. Certainly few general accounts of nineteenth and twentieth century science, technology and medicine give anything like enough weight to non-basic, non-academic research. This is true even when the small scale of the academic research enterprise, compared to research and development or even science and engineering is recognized, as in the case of the work of Bruno Latour. lxxiii This bias is obvious in the importance given to accounts of university research, but where its invisible power is best seen is in accounts of science and the military, science and government and science and industry. There is a systematic bias in these accounts towards the study of academic scientists in relation to these bodies. For the case of Britain, which I know best, there was a genre of writing on the history of science policy, which systematically confused the history of science policy with the history of academic and related research. For example, 15

16 the Haldane principle of autonomy of research councils, which only applied to fundamental research, and some cross-cutting research, is assumed to be the central guiding principle behind all state research funding. lxxiv For the US case there is a distinct tendency to focus on the OSRD and the NSF that it is as if these bodies were the only ones which mattered in mid-century science policy. In the case of science and the military the story in most literature is one of the entry of academics scientists into association with the military in times of war, and the continued funding of academic science (in the US case) by the military in the cold war. lxxv The historians of technology, have tended to focus on the most academic of industrial research. An account by Donald Cardwell in 1957 made an interesting distinction between technology and applied science technology the application of given laws was the application of the results of science while applied science was the actual investigation by the methods of pure science, of laws relevant to the industry concerned: it was science restricted to the foreseeable interests of industry. Cardwell saw it as new, and explicitly denied that it arose from other older industrial practices. lxxvi He denied too that the technologists evolved into the applied scientists the pioneering German industrial labs were derived from academic examples, the staff were the products of universities and colleges that otherwise turned out teachers. A whole generation of studies of industrial research (and I too am guilty) have focused on research in industry and above all on central corporate research laboratories. This profoundly academic-research-oriented model of twentieth-century science is all the more surprising in view of the long tradition of stressing the non-academic origins of modern science, particularly the craft traditions, and the insistence of much history of science, strengthened in the last 20 years, on the significance of industrial contexts for science, from dyeing to brewing to engine making. The idea that academic science is strongly dependent on, affected by, derivative of technology has long been a commonplace of the history of nineteenth and twentieth century science. In that sense we have long since moved from a scientific conception of technology to a technological conception of science. lxxvii Indeed one historian suggests shifting from the usual historical use of science-based industry to industry-based science. lxxviii Nevertheless there is a strong tendency to look at the industrial, technological and other contexts of academic science rather than non-academic science as such. lxxix 16

17 Alternatives to the Academic Research Model of History of Science Bush s account of the development of research in the United States, is, paradoxically enough, a good place to start a sketch of an alternative picture. lxxx For Bush pointed out that the great bulk of research was applied research and was done in government and industry; he highlighted the increasing proportion of industry and government research. Simply recognizing the comparative scale of industrial and government research through the century is enough to transform the usual implicit maps of the twentieth-century research enterprise historians have worked with. lxxxi The history of innovation and innovation policy must surely focus on industry and government agencies concerned with it, rather than science policy. Such a non-academic perspective can change our accounts of standard linear model cases. Take for example histories of the atomic bomb project which usually take the form implied by the linear model they start with academic physics, and go through big science to the atomic bomb: this is history taken from the biographies of academic physics as they move from pure to applied. For the historian of technology and the military there are many precedents, both industrial and military, to the bomb project, as is clear in Thomas Hughes quite distinct account of the Manhattan Project. lxxxii Indeed the Manhattan project is seen as possible because there were such precedents and capacities. But, one could see it a part of a process of development of the innovative capacity of the military and of large corporations, which extended their range to pure nuclear physics. Indeed the whole of wartime R&D activity is best seen in this way as an extension and strengthening of pre-existing military and industrial organizations, rather than the export of academic basic science into wartime bodies. Even in the post-war years, when the prestige of basic science, and particularly academic basic science, was very high, it is still useful to see industrial and military research as an upgrading of industrial facilities as much as an importation of academic models and personnel. To be sure, there was a wave of laboratory building far from production, and the bringing in of high-level academics, but there was expansion in all kinds of scientific activity after the war. lxxxiii At very best the linear model to the extent we grant its existence at all will be a very small part of the picture. I want to argue for a more general critique based on the observation that there is a systematic confusion in the literature between science and scientific research, which is hardly noticed because so many analysts assume science to be research. lxxxiv It is important to distinguish between expertise, including scientific expertise, and research. The twentieth century belief that Science implies the breaking of new ground, lxxxv has made the history of science and 17

18 expertise the history of research. Intellectuals, even engineers like Vannevar Bush, generally used science and scientific refer to scientific research. This is one reason why the history of science in business, or of science in government, or the university is, without this being clear, the history of research. lxxxvi Yet research was something new which increasingly came to define science, and scientific, even though only a small proportion of scientists were ever engaged in it; the research revolution in the late nineteenth century, not merely a laboratory revolution, and that it extended right across the field of knowledge, and to many kinds of institution, was of huge significance. lxxxvii On the other hand we should not ignore the continuing importance of non-research technical expertise. lxxxviii Nor should we ignore the historical processes by which research became so important, and we should resist the temptation to see research as itself created with the realms of pure science. We would do well to think about twentieth century science as a great mass of non-research science, some applied science, and a little bit of basic science, if we grant the categories. Research is not the norm for scientific activity, and within research pure research is not the norm either. Of course some historians of technology, and some historians of science, have looked at nonresearch science and technology, though both subjects are generally innovation and research centered. lxxxix As Ernst Homburg has pointed out, it is highly misleading to identify the beginnings of science in industry, with research, or more generally the significance of science in industry with the significance of research. xc However, in the literature on science in industry, although dominated by research, scholars have been careful to point to (though often without giving too much detail) that research was generally built on top of, or out of significant pre-existing scientific organizations. xci Scientists were first employed in routine jobs, for example in industry scientists are first employed for production, and the scientific role is upgraded with time till some is involved in pure science. Indeed we can follow a line of analytical labs, development labs, and research labs, generally established in that order. In this alternative picture the actual placing of pure, fundamental and basic research is best understood as emerging (sometimes) from what academic researchers see as lower kinds of scientific activity. What we see is not the rise of science as such, but the rising prestige of the researcher. This is not to say that particular individuals evolved in the same way in many cases, each higher level meant the recruitment of new kinds of personnel from outside industry. xcii Such developments are familiar in cases of IG Farben, GE, AT&T and Du Pont, where research laboratories came after the establishment of many other sorts of laboratories. One of the best-studied cases in this context is IG Farben: it had around 2,000 chemists in the 18

19 late 1920s, with around 1,000 classified as research chemists. The latter they worked in 50 laboratories, of which ten were large main laboratories. xciii In Britain too, the pattern was very similar with research emerging out of existing scientific activity. xciv In the armed forces too research was added to pre-existing scientific work, but of the uniformed branches and of civilian technical specialists. Certainly in the interwar years there emerged a large civilian research corps was gaining in power and prestige in the interwar years, gaining ground over other technical specialists, later supplemented by academic researchers. Can a similar story be told for academic research? It can, for most academics were not researchers until well into the twentieth century. In the case of laboratories, these too were concerned with teaching when first introduced in the nineteenth century, then a place for analysis and testing, and then a research laboratory focused on a research program. xcv Indeed the study of industrial research laboratories has provided materials for the reassessment of the history of academic research. Dennis argues research developed simultaneously, and in parallel ways in industry and the university. xcvi In medical schools too, laboratories are first teaching places, and their teaching staff lowly figures compared with the clinicians. Later research laboratories and researchers clearly have higher relative prestige. xcvii The research revolution in the universities, as in industry and government, was a slow one: even in the 1930s research was not universal in university departments of arts or sciences. xcviii In short the linear model does not work for institutions, just as it does not work for innovations. The new institutions of science were not pioneered through fundamental work in the academy and then progressed linearly down to everyday practice; the reverse might be better, crude, approximation. Non-Cumulation Why such a straw man as the linear model gained such currency and such significance in the academic literature of the 1980s and 1990s is not a question readily answered. Indeed what needs explanation is not just this case for there was a general tendency in the science and technology studies literature, and the associated historical literature too, to deploy a number of other straw men like technological determinism and whig history. One can understand why this was done it was convenient to invent labels for naïve positions influentially peddled in the public sphere by scientists and engineers, and found in particular in the views science and engineering undergraduates taught by STS and other academics. The very failure of STS to define the public discourse around science and technology doomed us to attacking 19

20 public science. Instead of engaging with the arguments of critics of naïve positions, of which there were by the 1990s several generations, the naïve conceptions still had to be attacked. These naïve conceptions created by academics thus achieved greater prominence than they would otherwise have had. xcix The result was a non-cumulation of the critical positions, to the extent that it came to be argued that even the older academic literature was contaminated. The linear model case reveals how some academics systematically ignored several generations of academic work on innovation, which presented much richer accounts of innovation than those criticized. But it is hardly the only case. Let me take some examples from my own work. For example, the radical British Ministry of Technology of the late 1960s, famous then and now, did many things, which many analysts hold did not, and could not have happened in Britain. c Studies of the relations of science and the military and Britain have not maintained the knowledge present in Bernal s otherwise famous Social Function of Science. ci Histories of British industrial research done in the 1970s refuted the key conclusions of well-known work produced in the 1980s. cii The SCOT program relied to a significant degree on rubbing out previous generations of studies of social construction. ciii Perhaps the most devastating criticism of the linear model that there is no correlation between national R&D spending and national economic performance, appears to be unknown to most students of innovation, certainly most critics of the linear model, but was a commonplace in the 1960s. civ For the history of British science we have had generations of what I have called anti-histories. cv Readers will doubtless have their own examples. In this particular paper I have argued that we should take on board what we have known (in principle) for several academic generations that the study of industrial innovation and science in industry, rather than starting yet again with an attack on a straw man. In studying science in industry we should start with the literature on industry, not academic science, and in particular from literature that it not driven by academic research model assumptions. cvi What deserves criticism is our own academic work, not straw men, or models popularized for propaganda purposes by the academic researchers. cvii The implications are that we should reject the academic-research-centered model of science, and indeed the research-centered model of science, which remain dominant, if we are to understand the relations of science and industry in the twentieth century. While the study of academic research science is interesting in its own right, it can t stand for the study of science as a whole, unless, that is, we believe in the linear model. 20