‘The linear model’ did not exist: Reflections on the history and historiography of science and research in industry in the twentieth centuryi
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
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.
[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
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 1969. 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
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,
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 1983. 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
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
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 pay-off.xxxixSources 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
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
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
of innovation. The term ‘linear model’ is nowhere used. Bush was arguing for the public
support of basicliv 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 1940. 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
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
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
linear model of science pushing technology, which policy-makers once saw as a self-evident 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 1958.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
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,
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
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
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 non-research science and technology, though both subjects are generally innovation and non-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
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
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’.
i
I am grateful to the participants at the Symposium for their many and varied comments,
which have helped strengthen the argument of the paper. I am especially grateful to Mats
Fridlund, Andrew Mendelsohn and participants in a doctoral seminar at Imperial College for
their invaluable criticisms of earlier versions. Thanks are also due to Mats Fridlund for many
examples of the use of the term I would otherwise not have seen. I am also grateful to Eric
Schatzberg for his observations, and for some material I would not otherwise have come
across.
ii
As was clear in the preliminary paper for this Nobel Symposium, and indeed in many of the
abstracts submitted.
iii
I have sought to clarify meaning of ‘technological determinism’ in David Edgerton, “De
l’innovation aux usages: Dix theses sur l’histoire des techniques,” Annales HSS, no. 4–5
(Juillet–Octobre 1998), pp. 815–837. English version, “From Innovation to Use: Ten
(eclectic) theses on the history of technology,” History and Technology, vol. 16 (1999): 1–26.
I deal with the particular inflexions of Whig history in the British case in England and the
Aeroplane: An Essay on a Militant and Technological Nation (London: Macmillan, 1991) and
Science, Technology and the British Industrial ‘Decline’ ca. 1870–1970 (Cambridge:
CUP/Economic History Society, 1996).
iv
Here I am following on from a paper by Michael Dennis which is insufficiently known
among historians of science (and technology) Michael Dennis, “Accounting for Research:
New histories of corporate laboratories and the social history of American science,” Social
Studies of Science, vol. 17 (1987): 479–514.
v
I think it is clear from most of the criticisms of the linear model that what is objected to, is
not just the linear sequence of steps, but also the alleged main source of innovation. I do not
important, or the separate argument that research managers, say, plotted sequential models.
One of the clearest linear models attacked is that in Terence Kealey, The Economic Laws of
Scientific Research (London: Macmillan, 1996), which takes the model as one starting with
publicly-funded academic research.
vi
Donald Stokes, Pasteur’s Quadrant: Basic science and technological innovation
(Washington DC: Brookings, 1997), pp. 10, 18-19.
vii
Harvey Brooks, “Lessons of History: Successive challenges to science policy,” in The
Research System in Transition, eds. S. Cozzens, P. Healey, A. Rip and J. Ziman (Dordrecht:
Kluwer, 1990), p. 13. Kealey, Economic Laws also clearly extends the meaning of ‘linear
model’ to include economic growth.
viii Bruno Latour’s ‘diffusion model’ is in many ways the linear model in another, funnier,
guise. Bruno Latour, Science in Action: How to follow scientists and engineers through
society (Cambridge, MA: Harvard University Press, 1987), pp. 132–144.
ix
David E. H. Edgerton, “Research, Development and Competitiveness,” in The Future of UK
Industrial Competitiveness and the role of Industrial Policy, ed. K. Hughes (London: Policy
Studies Institute, 1994), p. 48. I went to state in a footnote that it was “largely a straw man
invoked to demonstrate the superiority of current ways of discussing innovation […] If it
existed at all, [it] was merely an apologia for the funding of pure science,” pp. 53–4, the
argument I am developing here.
x
Nick Henry, Doreen Massey and David Wield, “Along the Road: R&D, Society and Space”,
Research Policy, vol. 24 (1995), p. 708. The article finds that ‘the linear model’ structures
R&D and its relation to production in the companies they study.
xi
Chris Freeman, “The Greening of Technology and models of innovation”, Technological
Forecasting and Social Change, vol. 53 (1996), p. 27.
xii
xiii
Ernest Braun, Futile Progress: Technology’s Empty Promise (London: Earthscan, 1995), p.
53.
xiv
Doreen Massey, Paul Quintas and David Wield, High-Tech fantasies: Science parks in
society, science and space (London: Routledge, 1992), chapter three. Thanks to Mats
Fridlund.
xv
Roy MacLeod, “Toward a New Synthesis: Chemists and chemical industry in Europe,” Isis,
vol. 94 (2003), p. 114.
xvi
William J. Price and Lawrence W. Bass, “Scientific research and the innovative process:
The dialogue between science and technology plays an important, but usually nonlinear role
in innovation,” Science, vol. 164 (1969): 802–3.
xvii
The latter argument was extremely important in Schumpeter’s account of capitalism. See
my brief account in Industrial Innovation and Research in Business (Cheltenham: Edward
Elgar, 1996); John Jewkes, David Sawers and Richard Stillerman, The Sources of Invention
(London: Macmillan, 1958).
xviii
J. Langrish et al., Wealth from Knowledge (London: Macmillan, 1972), pp. 72–3.
xix
Wealth from Knowledge pp. 33–5.
xx
Edwin Layton, “Conditions of Technological Development” in Ina Spiegel-Roesing and
Derek de Solla Price, eds., Science, Technology and Society: A cross-disciplinary perspective
(London: Sage, 1977), p. 204. This is the closest I could find to the linear model anywhere in
this comprehensive landmark text, except in a passing reference (p. 234) by Chris Freeman to
Layton’s chapter.
xxi
Roy Rothwell and W. Zegveld, Reindustrialisation and Technology (London: Longman,
1985), p. 49.
xxii
Nathan Rosenberg, Perspectives on Technology (Cambridge: Cambridge University Press,
xxiii
Chris Freeman, The economics of industrial innovation, Second edition (London: Pinter,
1982), pp. 194, 196–200. I have not checked the first edition.
xxiv
See for example the particularly relevant cases of Karl Kreilcamp, “Hindsight and the
Real World of Science Policy,” Science Studies, vol. 1 (1971): 43–66, and his “Towards a
theory of Science Policy,” Science Studies, vol. 3 (1973): 3–29, and Harold Orlans, ”D&R
allocation in the United States,” Science Studies, vol. 3 (1973): 119–159.
xxv
R. R. Nelson and S. G. Winter, “In search of a useful theory of innovation,” Research
Policy, vol. 6 (1977): 36–76.
xxvi
Vivien Walsh “Invention and innovation in the chemical industry: Demand-pull or
discovery-push?” Research Policy, vol. 13 (1984): 211–34.
xxvii
David C. Mowery and Nathan Rosenberg, Technology and the pursuit of economic
growth (Cambridge: Cambridge University Press, 1989). Though it criticizes the neo-classical
economic approach, which they say does radically separate between basic research, where the
key steps are seen to reside, and the appropriation stage (pp. 4 and 6).
xxviii
Rudi Volti, Society and Technological Change, Second edition (New York: St Martin’s
Press, 1992).
xxix
Bruce L. R. Smith, American Science Policy since World War Two (Washington, DC:
Brookings Institution, 1990). For Britain see Gummett, Scientists in Whitehall (Manchester:
Manchester University Press, 1980).
xxx
G. Dosi, “Sources, procedures and microeconomic effects of innovation,” Journal of
Economic Literature, vol. 26 (1988): 1120–1171; R. R. Nelson and Gavin Wright, “The rise
and fall of American technological leadership: The postwar era in historical perspective,”
Journal of Economic Literature, vol. 30 (1992), 1931–1965; Paula E. Stephan, “The
xxxi
Stuart Macdonald, “Technology beyond machines” in The Trouble with technology:
Exploration in the process of technological change, eds. Stuart Macdonald, et al. (London:
Pinter, 1983), p. 31. Thanks to Mats Fridlund.
xxxii
Kline, S. J., “Innovation is not a Linear Process,” Research Management, 28:4 (July–
August 1985), p. 36. On the latter point see p. 44 also.
xxxiii
Steven Yearley, Science, Technology and Social Change (London: Unwin Hyman, 1988),
p. 115, citing J. Ronayne, Science in Government (London: Edward Arnold, 1984), p. 44.
xxxiv
Trevor Pinch and Wiebe Bijker, “The Social Construction of Facts and Artifacts,” in The
Social Construction of Technological Systems, Wiebe Bijker, Thomas Hughes and Trevor
Pinch eds. (Cambridge, MA: MIT Press, 1987), pp. 22 and 28.
xxxv
Arie Rip, “Science and Technology as Dancing Partners,” in Peter Kroes and Martijn
Bakker, Technological Development and Science in the Industrial Age: New perspectives on
the Science-Technology Relationship (London: Kluwer, 1992), p. 233.
xxxvi
C. F. Carter and B. R. Williams, Industry and Technical Progress: Factors governing the
speed of the application of science (London: Oxford University Press, 1957); Investment in
Innovation (London: Oxford University Press, 1958) and Science in Industry: Policy for
progress (London: Oxford University Press, 1959).
xxxvii
Carter and Williams, Industry and Technical Progress, p. 54.
xxxviii
Ibid., p. 56.
xxxix
John Jewkes, David Sawers and Richard Stillerman, The Sources of Invention (London:
Macmillan, 1958), pp. 6–7. The authors clearly wanted to make analytical distinctions
between science, invention and development.
xl
See my Science, Technology and the British Industrial ‘Decline’ ca. 1870–1970
(Cambridge: CUP/Economic History Society, 1996); “The ‘White Heat’ revisited: British
Terence Kealey, The Economic Laws of Scientific Research (London: Macmillan, 1996). As
an example see John Jewkes, David Sawers and Richard Stillerman, The Sources of Invention,
Second edition (London: Macmillan, 1969), chapter X: “The last ten years in retrospect.”
xli
Gerhard Rosegger, The Economics of Production and Innovation: An industrial
perspective, Second edition(Oxford: Pergamon Press, 1986) [first edition 1980] notes that
economists and social scientists, in order to simplify a complex process of innovation, have
used ‘sequential’ or ‘stage’ models, without specifying any, but giving a diagram, which is
considerably more complex than the usual linear model one. He notes, “the stage model
provides a very useful framework for the study of innovative activity” (p. 9). He notes three
shortcomings immediately: 1) it involves arbitrary definition into phases 2) it is unidirectional
with no feedback 3) it is useful only for major, visible innovations (p. 10).
xlii
George Wise, “Science and Technology,” Osiris 2nd series (1985): 229–246.
xliii
George Wise, “Science and Technology,” Osiris 2nd series (1985): 229–246. There is a
whole literature surveying accounts of science technology relations, which is relevant. See for
example: Alex Keller, “Has Science Created Technology?,” Minerva, vol. 22 (1984): 160–
182; R. Kline, “Construing ‘technology’ as ‘applied science:’ Public rhetoric of scientists and
engineers in the United States 1880–1945,” Isis, vol. 86 (1995): 194–221.
xliv
Sir Edward Appleton, “Fundamental research and industrial progress,” in Federation of
British Industries, Industry and Research (London: Pitman, 1946), p. 14.
xlv
Albert H. Rubinstein ed., Coordination, Control and Financing of Industrial Research:
Proceedings of the fifth annual conference on industrial research, June 1954, with selected papers from the fourth conference, June 1953 (New York: King’s Crown Press, Columbia
University, 1955).
xlvi
F.B. Tuck, Ideas, Inertia and Achievement: a survey of current opinion on how to shorten the time lag between scientific discovery and engineering application. New York: American Society of Mechanical Engineers, 1960. Thanks to Eric Schatzberg
xlvii
Freeman, “The Greening of Technology,” p. 27.
xlviii
Donald Stokes, Pasteur’s Quadrant: Basic science and technological innovation
(Washington DC: Brookings, 1997). xlix Ibid., p. 3. l Ibid., p. 10. li Ibid., pp. 18–19. lii
Science, The Endless Frontier: A Report to the President by Vannevar Bush, Director of the Office of Scientific Research and Development, July 1945 (United States Government Printing Office, Washington: 1945). I don’t know of any work that analyses the argument of the report with the exception of part of Ronald Kline, “Construing ‘technology’ as ‘applied science:’ Public rhetoric of scientists and engineers in the United States 1880–1945”, Isis, vol. 86 (1995): 194–221, but the argument here goes further. For the political background see: Daniel Kevles, “The National Science Foundation and the debate over postwar research policy 1942– 1945: A political interpretation of Science—The Endless Frontier,” Isis, vol. 68 (1977): 5– 26; Jessica Wang, American Science in an Age of Anxiety: Scientists, Anticommunism & the Cold War (University of North Carolina Press, 1999); David Hart, Forged Consensus: Science, technology and economic policy in the United States, 1921–1953 (Princeton: Princeton University Press, 1997)
liii
Paul Forman, “Behind Quantum Electronics: National security as a basis for physical
research in the United States, 1940–1960,” HSPS, vol. 18 (1987), p. 152.
liv
It is claimed by Stokes that Bush coined the term ‘basic research;’ but Benoit Godin,
“Measuring Science: Is there ‘Basic Research’ without statistics”, (Mimeo, Montreal,
Observatoire des Sciences et des Techniques, 2000) shows it was used by Julian Huxley in
Scientific Research and Social Needs (London: Watts, 1934). Thanks to Mats Fridlund.
lv
The key statistical background was the following: “In the decade from 1930 to 1940
expenditures for industrial research increased from $116,000,000 to $240,000,000 and those
for scientific research in Government rose from $24,000,000 to $69,000,000. During the same
period expenditures for scientific research in the colleges and universities increased from
$20,000,000 to $31,000,000, while those in the endowed research institutes declined from
lvi
For the importance of distinguishing ‘research’ from the stock of ‘knowledge’ see for
example, S. J. Kline, “Innovation is not a Linear Process,” Research Management, 28:4
(July–August 1985), p. 36 and Keith Pavitt’s paper in this volume.
lvii
Arie Rip, “Implementation and evaluation of science and technology priorities and
programs,” in S. Cozzens, et al., Research System in Transition, p. 274.
lviii
Edward R. Weidlein and William A. Hamor, Science in Action: a sketch of the value of scientific research in American industries (New York: McGraw Hill, 1931), p. 278. Thanks to Eric Schatzberg.
lix
Ibid., p. 267.
lx
Sir Henry Tizard, “The passing world,” Presidential Address BAAS, September 1948.
lxi
Smith, American Science Policy, p. 78.
lxii
Ibid., p. 40.
lxiii
From SET Forum Shaping the Future: A policy for science engineering and technology
(1995)
<http://www.shef.ac.uk/~sfl/textonly/policy/set03.html>.
lxiv
Science and Education for a Prosperous China: Lessons From Abroad: A report from U.S.
Embassy Beijing November 1996
<http://www.fas.org/nuke/guide/china/doctrine/stabrd4.htm>.
lxv
Bruce L. R. Smith, American Science Policy since World War Two (Washington, DC:
Brookings Institution, 1990), p. 51.
lxvi
Harvey M. Sapolsky, Science for the Navy: A history of the office of Naval Research
(Princeton: Princeton University Press, 1990), Table A-5, p. 137.
lxvii
That the military didn’t believe it is argued by Paul Forman, in for example, his “Into
Quantum Electronics” in National Military Establishments and the Advancement of Science
and Technology, eds. Paul Forman and José Manuel Sánchez-Ron (Dordrecht: Kluwer, 1996),
