Richard Nelson

I could comment, and extensively, on a wide number of parts of the Diamond article, but that would lead me to jump from one remark to another and to still a third, without developing a coherent connected argument. Indeed, one complaint I have about the article is that Dia- mond does just that: jumps from one interesting point to another. Thus, I think it might be more fruitful if I focus on one particular issue.

I think Diamond is unduly narrow in associating an "economic analy- sis" of science with one that employs rational actor theory. Further, while I do not deny that there are various aspects of science that relatively straightforward "rational actor" theory can illuminate, there is much about the scientific enterprise that it cannot, at least in its standard form. Worse, by looking at science through those spectacles, one becomes blind to important phenomena, and inclined to deny their existence when some- one else calls attention to them.

What do I mean by these comments? Well, Diamond references both Dosi and Metcalfe. They, along with Sidney Winter and myself, have argued for some time that one needs to understand "technological ad- vance as an evolutionary process." Since Diamond has read those ar- ticles, he knows we mean by that a set of processes that involve bounded rationality in an essential way, differences in beliefs and perceptions among different parties, learning by individuals, and learning from each other, with various kinds of selection mechanisms at work. I believe that this characterization holds at least as much for science as it does for technology. I find it interesting that, in his otherwise very extensive bibli- ography, he nowhere references Don Campbell, or the rather extended group of scholars who are concerned with "evolutionary epistemology."

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Knowledge and Policy: The International Journal of Knowledge Transfer and Utilization, Summer/Fal l 1996, Vol. 9, Nos. 2 & 3, pp. 79-96.

80 Knowledge and Policy / Summer/Fall 1996

Loet Leydesdorff

Dis-Equilibria Within and Among the Sciences

"The Economics of Science" by Arthur Diamond provides a useful and comprehensive review of the literature. The aim of being comprehensive and synthetic, using the metaphor of markets, however, leads the author to amalgamate analytically different perspectives. The differences between theoretical traditions are not always sufficiently appreciated. For example, the author relates all kinds of sociologies that are more often identified in opposition to one another. Analogously, neo-classical (mainstream) eco- nomics, evolutionary economics, and theories of the firm are not analyti- cally distinguished. While this may be legitimate with reference to the subject matter under study, it nevertheless requires theoretical justifica- tion.

Let me sketch an alternative approach for the sake of this discussion. First, one might list those S&T policy issues to which the economics of S&T could make a contribution. This listing could then be organized into a scheme that distinguishes the various reflexive discourses. I know that there is always overlap, but there are also some useful distinctions. The analytical differences may enable us to formulate research questions.

As a starting point for such an analysis one could take the changing relations between science and the economy since WW II and the role of policies in organizing these relations. Given the increased importance of science-based technologies, allocation decisions are (and have been) press- ing. For example, one could begin the analysis with the discussions in OECD-circles about "picking the winners."a This has been a crucial policy issue about which economists may have a lot to say.

Before turning to tools, however, an analyst should distinguish be- tween the dynamics of the various markets involved, the changes and differences in social structures (e.g., among sectors, geographic areas, etc.), the diffusion of knowledge over interfaces, and the role of public and private organization in supporting these diffusion processes. 2 Then the various reflections could be discussed in terms of studies using a case by case narrative and/or quantitatively oriented approaches (which study the development of distributions within domains and thereby test the theoretical distinctions for their significance).

Such analytical reconstruction can lead to the formulation of a research agenda (in addition to the summary and overview that Diamond's ap- proach provides) that the various traditions will be able to elaborate. The clarification of overlap and lacunae can then be most useful. For ex- ample, in my own field of expertise (scientometrics), there are rather loosely coupled traditions of scientometric research evaluation (e.g., cita- tion studies), patent research, and econometric research; yet one will rarely find an econometrician at a scientometrics workshop or vice versa.

Leydesdofff 81

Perhaps the framework of evolutionary economics can help to bridge this gap, but important methodological problems remain to be solved, such as the difference between (static) multivariate analysis in scientometric mapping and modeling in terms of differential fluxes. 3 Diamond's article does not, however, address the problem of relating different research traditions: it fails to specify the problem of the function of dis-equilibria in developments within and among the sciences.

On the qualitative side, the circulation of knowledge as a product (even if it is knowledge about a process) can be distinguished from the generation of scientific knowledge by scientists and engineers. Diamond shifts the focus to scientists as units of analysis without sufficiently dis- tinguishing the academic institutions from the economic functions of their products in the social system (or, more generally, in other subsystems of society). The existence of (inter-)organizational relations does not pre- clude the operation of a (conditionalized) market. Perhaps one could say that the current version of Diamond's article focuses first on the theory of the institution (the firm) and only thereafter on the economics of the system. In my view, the distinction between knowledge as a commodity and knowledge production processes is important in any discussion of the economics of science and technology. 4

Evolutionary Economics and Nonlinear Dynamics

Diamond's article reflects a (sometimes implicit) tendency to react against modeling; it also does not recognize the need for modeling. Dia- mond even suggests a patronage relationship between mathematical eco- nomics and the NSF, to the detriment of other branches of economics. New developments on this side of the field are not discussed seriously.

In a recent contribution, I reflect on what nonlinear dynamics can teach us about the relationship between theoretical specification and for- mal modeling. 5 Among other things, modeling enables us to proceed from specification to generalization. In other words, the "phenotypical" behavior of the model system is more complex than is its composing "genotypical" dynamics, while only the latter can be the subject of sub- stantive theorizing. 6 In my opinion, this insight changes the epistemo- logical status of theoretical specifications. They remain provisional hy- potheses that may help to explain part of the variation.

In my opinion, three bodies of theory can be specified along three (nearly) orthogonal axes of the complex dynamic system: (1) mainstream economics as mainly a theoretical reflection on the price mechanism; (2) evolutionary economics and innovation studies, which add theoretical reflections about the mechanisms upsetting economic equilibria; and (3) technology assessment and theory of the firm, which add reflections about the social and institutional organization of this complex system. The fourth perspective is formal; i.e., the specification of the various subcybernetics

82 Knowledge and Policy / Summer/Fall 1996

(e.g., variation and selection) generates a complex model that can be simulated algorithmically.

Simulation enables us to evaluate the phase-space spanned by the theo- retical specifications for alternative solutions7 In general, the specifica- tion of theoretical insights on the basis of discursive interpretations is useful for a more precise definition of sub-cybernetics. Theorizing allows us to improve the model locally, in terms of one or more equations. In principle, the formal theory then enables us to proceed from the theoreti- cal specification toward generalization. Today, this perspective is still rather programmatic in technology studies. 8

The interaction among various subcybernetics can be appreciated with reference to each of the interacting (sub-)systems. Furthermore, one ex- pects theories to emerge concerning each of the interacting dynamics. 9 The consequent proliferation on the semantic side may lead to confusion if the relations between the substantive dynamics and the formal model are not sufficiently specified. The evolutionary models should not be appreciated only in a metaphorical sense; the (often counterintuitive) results of the simulations can also be used for generating new questions. As noted, a scientist needs distinctions, or "dia-phors," in addition to metaphors. 10

For example, the relation between variation in the first dimension and selection in the second can be distinguished from the relation between "change" in the first dimension and stabilization over time as a third dimension. While selection (e.g., market clearing) is expected at each moment in time, the sociologist may wish to use the metaphor of an engineer or an entrepreneur for the historical construction of a network. Although the various subdynamics are formally equivalent, they have profoundly different meanings: selection by the market is different from purposeful selection by an entrepreneur. 11

It is important to make analytical distinctions among both possible units of analysis (e.g., firms, markets) and theoretical programs in terms of relevant dynamics (e.g., production and diffusion processes). Various theories specify different subcybernetics, and only modeling allows us to span the phase-space of the possible interactions among these subcybernetics. In general, it may be easier to develop a comprehensive semantics using the metaphor of the market than to specify how this semantics must be positioned in relation to other semantics. However, the complex system should not be confused with the market. The selec- tive market mechanism constitutes one of its subdynamics. Using mod- els, one is able to study the question of how much of the variation (or its dynamic equivalent, i.e., the probabilistic entropy) can be explained by each specification (i.e., equation). 12 The positive insights from the various theories to that purpose are translated into selective (i.e., negative) condi- tions.

In summary, we need theoretical specification and appreciative inter- pretations, but we need them reflexively: the various theories should be

Leydesdorff 83

specified with reflexive awareness of the partiality of the perspective, the limits of the domains, and the specificities of the communication pro- cesses (e.g., markets) under study. By explicating the various theories in these terms, greater clarity can be achieved with respect to the lacunae that are still in need of further specification, subsequent modeling, and measurement efforts.

Notes

1. Irvine, J. and B.R. Martin (1984). Foresight in Science: Picking the Winners. London: Pinter.

2. Dasgupta P. and P.A. David (1994). Toward a new economics of science. Research Policy 23:487-521.

3. Leydesdorff, L. (1995). The Challenge of Scientometrics: The development, measurement, and self-organization of scientific communications. Leiden: DSWO Press, Leiden Univer- sity.

4. Leydesdorff, L. and H. Etzkowitz. (1996). Emergence of a triple helix of university- industry-government relations. Science and Public Policy (forthcoming).

5. See my chapter--New models of technological change: New theories for technology studies. In: Evolutionary economics and chaos theory: New directions in technology studies, L. Leydesdorff and P. Van den Besselaar (eds.), pp. 180-92. London: Pinter, 1994.

6. See pp. 147 in C.G. Langon (ed.), Artificial life (1989). Redwood City, CA: Addison- Wesley.

7. L. Leydesdorff and P. Van den Besselaar. (forthcoming). Technological development and factor substitution in a complex and dynamic system. Journal of Social and Evolu- tionary Systems.

8. P.W. Anderson, K. J. Arrow, and D. Pines (eds.) (1993). The economy as a complex evolving system. Reading, MA: Addison-Wesley; E.S. Andersen (1994). Evolutionary economics. Post-Schumpeterian contributions. London: Pinter.

9. See pp. 1-27, The organization of complex systems, H.A. Simon. In: Hierarchy theory: The challenge of complex systems (1973). H.H. Pattee (ed.). New York: George Braziller.

10. Niklas Luhmann, The cognitive program of constructivism and a reality that remains unknown, pp. 64-85. In: Self-organization: The portrait of a scientific revolution (1990). W. Krohn, G. Kfippers, and H. Nowotny (eds.). Dordrecht: Kluwer.

11. See, for example, M. Callon, J. Law, and A. Rip (eds.), (1986). Mapping the dynamics of science and technology. London: Macmillan; Wiebe E. Bijker, Thomas P. Hughes, and Trevor J. Pinch (eds.). (1987). The social construction of technological systems. Cam- bridge, Mass.: MIT Press.

12. See, for a further elaboration, G. Blauwhof, Non-equilibria dynamics and the sociol- ogy of technology, pp. 152-66. In: Leydesdorff & Van den Besselaar. Evolutionary economics and chaos theory, op. cit., note 5.

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84 Knowledge and Policy / Summer/Fall 1996

Edward J. Hackett

Economic perspectives would greatly enrich studies of science and technology, as proved by Diamond's comprehensive article and Stephan and Levin's fine book. To this social scientist with only a passing knowl- edge of the discipline, economics appears to offer an utterly unrealistic but very explicit set of assumptions about human behavior, coupled with powerful tools for developing and formalizing the implications of those assumptions into a model that can be tested against observations. Eco- nomics also seems well suited to further the goal of characterizing in contextual variables and delineating their implications for actors. Much science studies research today is so committed to telling the full story, in all of its idiosyncratic detail, including the story of the story telling--the reflexive turn--that studies seem unsystematic, incomparable, and in- consequential (in the narrow sense of seeming to lack consequence for theory, further research, or policy). The economic approaches discussed in Diamond's article may counterbalance such studies, urging more ex- plicit grounding in systematic assumptions and models, and more bold and systematic inferences about implications and consequences.

In some instances, economic approaches reveal new faces of a prob- lem. For example, the model of stocking a fish pond (p. 12), which has been applied to the problem of research financing, also offers a fresh perspective on publication and citation behavior. Just as it is difficult to determine how much value is created by those who stock a fish pond, maintain the pond, and catch the fish, it is also hard to know how much credit is due those who write articles, those who edit and referee jour- nals, and those who reference the articles that appear in publications. In current practice, citations redound exclusively to the credit of authors-- especially first or last authors on the by-line. But the fish pond analogy draws attention to the contributions of the editors and referees who se- lect publishable papers and who offer suggestions for their improve- ments, and to the contributions of subsequent authors who "fish" articles from the murky pond of potentially relevant literature and prepare them for serving in a new piece of scholarship.

Both the Stephan and Levin book and the work by Siow (discussed on pp. 18-19) suggest that publications will have different values depending on the career stage of the author. Prominent publications are more valu- able early in the career than later because their authors will enjoy the benefits over a longer period of time. This proposition is consistent with the sociological model of accumulative advantage in the reward system of science, which proposes that early success is itself a source of later success. I wonder, however, if a more general theory of the time-varying value of publication could be developed. For example, senior scientists would presumably have little to gain from quotidien publications, so would have an incentive to seek the most significant and prominent

Hackett 85

publications, even at the risk of failing and not publishing at all. In con- trast, even modest publications have some value for a young scientist trying to establish credentials and secure a job. How do these varying incentives play themselves out in scientists' publication decisions? What happens to such calculations when scientists at quite different career stages are bound together in a research group?

Rent-seeking, a novel concept to me, offered a plausible if unflattering explanation for some of the entanglements of academic life. Comprehen- sive explanations of peer review, publication, the tenure system, salaries, and other aspects of the academic labor market seemed less persuasive. It seems unlikely that publication performance is used to screen the quality of faculty for teaching purposes; as many of the most published faculty do not teach, research skill and teaching ability are probably not corre- lated very highly, and research activity brings important rewards (of reputation and cash) to the university. To me tenure appears to be a reward offered in place of salary, an institutional effort to show commit- ment to a person and to a professional system of self-direction, in an effort to keep costs down and to sustain faculty commitment to a diffuse set of professional values. In its absence faculty might demand higher wages and might have little incentive to do many of the small but time- consuming chores of the profession. In this regard I wonder what would happen if faculty billed their professional time along the lines lawyers use: consultations with students about papers, theses, curriculum, and careers would be charged in six-minute increments. Manuscript and pro- posal review would become prohibitively expensive. Indeed, without some show of support for academic values on the part of the university, what would prevent professors from the expedient of catering to stu- dents' interests by giving them all an "A'? Given the difficulty and ex- pense of monitoring complex professional work, universities may find it easier to appeal to a set of shared values and to sustain those values through the granting of tenure.

Diamond's article prompted me to think about an ongoing research problem in a different light. I am interested in the behavior of scientific and engineering research groups, chiefly because they are the social unit at the intersection of resources, knowledge production, work and career. During my research on this topic it became apparent that each research group had a distinctive experimental system (or preparation, instrumen- tality or approach) that bestowed competitive advantages and disadvan- tages (such as speed, precision, cost, labor intensivity, flexibility, or even the capacity to evince a unique phenomenon or to address a specific sort of research question). Much of a group's effort is devoted to maintaining the system, in the narrow sense of "housekeeping" (such as tending plants or cell cultures or mechanical instruments) and in the broader sense of improving or refining the system to secure a place in the research area (and an attentive audience for research findings). The group's success and long-term viability are also connected in no small measure to such

86 Knowledge and Policy ! Summer/Fall 1996

characteristics of the research system. I now wonder whether it is pos- sible to think about such behavior as a form of investment or capitaliza- tion, and whether some principles concerning the behavior of firms (such as risk-taking, diversification, responsiveness to changing market condi- tions, information-handling, and even failure rates) may be borrowed to develop a theory of research group behavior. Such a theory would be socioeconomic by necessity (because research groups do more than maxi- mize profit or utility; they serve a variety of ends and honor a range of competing values in the process) but might reflect a fruitful synthesis of ideas from economics and science studies.

Diamond's article convincingly demonstrates the value and insightful- ness of economic perspectives on science. The next challenge is to inte- grate economic analyses and explanations with those current in science studies to identify testable inconsistencies and novel hypotheses. Rather than supplant the rich and diversely descriptive studies of science now underway, economic approaches promise to urge more explicit and con- sistent prior assumptions, more formal and determinative tests, and more integrative explanations.

Lowell Hargens

Although a "Merton-Price" sociologist of science with at least latent sympathies for an economistic approach to science, I nevertheless am skeptical about the likelihood that such an approach will have much of an impact on STS studies. Before listing the reasons for my skepticism, however, I will begin by listing two reasons for endorsing the "minimal" claims Diamond makes in his article.

First, who can object to the argument that economists' perspectives and analytic tools are necessary for attaining "a complete understanding of the advance of science and the behavior of scientists"? As Diamond himself points out in the last section of his article, even constructivist sociologists of science have borrowed basic concepts from economics in their analyses of science. Similarly, the methods developed during the last half-century by econometricians are now commonly used through- out the social and behavioral sciences, including many STS studies.

Second, I am confident that, in the abstract at least, most sociologists would agree that it would be nice to have a "general theoretical frame- work" to guide and integrate our research efforts. Furthermore, the "maxi- mizing-under-constraints" model, broadly interpreted, is certainly a can- didate for fulfilling these functions.

These two points accepted, why am I skeptical about the prospects for

Hargens 87

economizing STS studies? First, it is almost an article of the sociological faith that economics overemphasizes the monetary aspects of human be- havior and therefore takes an overly narrow view of what is being maxi- mized by rational actors in contexts of constraint. One of my favorite cases in point here is McDowell's (1982) article on the cost of having an interrupted career in fields with varying rates of "knowledge obsoles- cence." Using straightforward human-capital arguments, McDoweU claims that rational actors who anticipate having interrupted careers (i.e., women) will avoid fields like physics and will be attracted to fields like English. Few sociologists, psychologists, or anthropologists accept this analysis because we believe the allocation of people to fields of study is a compli- cated process that is improperly viewed as one being driven by indi- vidual choice. In becoming a nuclear physicist one is probably chosen at least as much as one chooses, and the former process involves all kinds of considerations about the skills, demeanor and physical characteristics appropriate to doing nuclear physics.

The McDowell article also illustrates a second source of resistance to the spread of economic analysis. In constructing an explanation of a given phenomenon along the lines of rational actors maximizing utility, econo- mists are prone to accept uncritically the possible explanation as being the explanation. Perhaps this is the price a field pays for having a unify- ing general framework and for trying to explain "a lot with a little." If so, many STS scholars will be reticent to accept economists' perspectives on social behavior regardless of the integrative possibilities of those per- spectives.

Will an economistic approach to science overcome these kinds of resis- tance? In the long run, the success of this approach will be determined by practitioners' ability to provide compelling analyses of science and tech- nology. For example, it has been almost a decade since human capital theory was supposed to revolutionize sociological research on the family, but as yet this classically economistic perspective has made little head- way. Closer to home, we need only recall the claims during the early 1970s that the time was ripe to analyze the content of scientific knowl- edge using the sociology of knowledge perspective. It is easy to claim that rethinking a field along new lines will revolutionize the field, diffi- cult to convince other scholars, and even more difficult to succeed. Diamond's article accomplishes the first task, but the second and third remain unlikely achievements.

Reference

McDowell J.M. (1982). Obsolescence of knowledge and career publication profiles: Some evidence of differences among fields in costs of interrupted careers. American Eco- nomic Review 72 (September):752-768.

88 Knowledge and Policy / Summer/Fall 1996

Raphael Sassower

This is one of the most comprehensive surveys of the literature I have ever encountered, and as such is both informative and critical. It is also one of the most ambitious surveys one can expect in the age of narrow specialization. It remains, therefore, as a benchmark for any of us who are interested in science studies, in the intersection between economic theory and scientific inquiry, and in policy issues related to the funding formulae proposed by government agencies and the academy. In light of this general assessment, I have only three general comments to make, comments I expect will be contributions to the present text.

First, though mentioned briefly in the text (pp. 27-28), I think more attention must be paid to the blurring of boundaries between what have traditionally been characterized as science and as technology. The history of science is filled with examples that illustrate how technologically de- pendent scientific discoveries are, how the need for technical prowess is paramount in the activities of scientists, and how, in the age of so-called big science, technology is indispensable for the functioning of a scientific community (no matter how large or small). Now the question of the blurring of the distinction between science and technology--assuming, for example, that science is theoretical and technology practical, or that technology is the handmaiden of sciencc ~.s not limited to practical is- sues, such as the necessity to know how to handle equipment and tools and techniques of the trade. Rather, there is a real sense in which there is an epistemological dimension to this shift (see Ormiston & Sassower, 1989).

Epistemologically speaking, this is not only a shift toward the Marxian notion of praxis (combining theory and practice or showing how the two are intimately connected), but also a shift that recognizes social, political, and especially economic conditions within which the scientific enterprise is undertaken. So, the question no longer is "what do we know?" and "how do we know what we know?", but instead it is also "why do we care to know what we know?" The historical grounding for this mode of thinking dates back to Egyptian land surveys motivated by the flooding of the Nile that relate to the development of geometry, as well as to the encouragement of the study of astronomy for navigational purposes. Simi- larly and much later, the development of the theory of probability was linked to gambling, to the trade between the British empire and the Far East, and to life insurance rates.

My first comment relates to the relation between science and technol- ogy, especially in light of the study of the economics of science. I guess I would recommend either to add the study of the economics of technol- ogy to that of science or to collapse the distinction and develop the study of the economics of technoscience, as sociologists like Bruno Latour call the field.

Sassower 89

Second, let us examine the category of scientist. We know the original use of the term somewhere in the middle of the nineteenth century by Whewell, and we know that the term has been contested repeatedly. For example, the British Association for the Advancement of Science planned the expulsion of Section F, Statistics and Political Economy in the 1870s because of some disputes concerning the so-called scientific method (see Sassower, 1993:Ch. 1). Now, I bring up this point because the text glides effortlessly between the notion of scientist and economist as if there is no contestation that economists are indeed scientists. I think that we need to pay some closer attention to the history of economic thought so as to highlight the criteria by which economic theory has attempted over two hundred years to gain scientific respectability if not outright validity (see Sassower, 1985).

I venture to guess that bringing up the point about the scientific status of economics itself would add an interesting dimension to the text, at least for two reasons. First, it would open the discussion about what field of inquiry qualifies as a bona fide science, and second, it would put into question the whole enterprise of developing a new exciting area of re- search called economics of science. That is, the very status of the inquiry here developed would immediately come under the kind of scrutiny it rightfully deserves.

Third, perhaps we should broaden the scope of the enterprise of this text. If we follow only partially the ideas of Marxists and postmodernists, not to mention feminists, it becomes apparent that it is not clear what is meant by the concept economics. Are we alluding only to econometric models, whereby a certain input of data yields a certain output? Are we presuming certain things about human nature, such as a competitiveness or a maximizing preference curve? Economists, such as Amartya Sen, are careful to include more, rather than less, variables in their analyses. They are aware, perhaps in the sense of Lionel Robbins, that one must avoid Friedman's insistence on positive economics and move toward political economy (despite the sense in which this text is honestly descriptive). Now, I know how difficult it is when one wants to study the kind of returns that accrue to scientists, and the author admits that much when he talks about the curiosity and performance of scientists for sheer enjoy- ment.

Perhaps there is room in the present discussion to consider the general mode of production in the late twentieth century, may it be called post- capitalist or post-Fordist or post-Marxist. The reason this may be an im- portant issue is because of the kind of public policies intended to come as a result of the study of the economics of science. For example, must we change the ideological climate under which decisions for funding are made? Is technoscience an essential part of our society or a mere luxury only wealthy nations can afford? Do we need technoscience for our very survival or only in order to get richer than other, less developed coun- tries? Must the scientific community be large or small? Should it be orga-

90 Knowledge and Policy / Summer/Fall 1996

nized democratically or with a specific hierarchy? The internal structure of the scientific community (as sociologists of science are prone to argue) reflects and sometimes deflects the structure of society as a whole. Per- haps the appreciation of the political economy context of the workings of technoscientists would help direct the study of the economics of technoscience.

In conclusion, I think the present text is extremely stimulating and worthwhile, for it brings up the sort of concerns that remain buried or are routinely assumed away in the studies of sociologists and philoso- phers of science. I am in complete agreement with the author that it is essential to think about economic conditions when thinking about sci- ence.

References

Ormiston, G.L. and R. Sassower (1989). Narrative experiments: The discursive authority of science and technology. Minneapolis: University of Minnesota Press.

Sassower, R. (1985). Philosophy of economics: A critique of demarcation. Lanham, MD: Uni- versity Press of America.

- - (1993). Knowledge without expertise: On the status of scientists. Albany, NY: SUNY Press.

Warren Schmaus

In order to make a persuasive case that science can be made more efficient through the application of economic theory, Diamond needs to analyze certain key concepts, including "advance," "productivity," and "growth." Most of the conceptual problems are to be found in the last two sections. Hence, my comments will concern the sections "The Con- tribution of Science to Technological Change and Economic Growth" and "Prospects for the Economics of Science."

Science, Technology, and Economics

Diamond assumes that the growth of science leads to advances in technology, which then lead to economic growth. This assumption ac- quires whatever plausibility it has only through trading on ambiguities in some of the key concepts mentioned above.

Terms like "productivity" and "growth" may be applied to both sci- ence and economic life, and it is easy to be misled into thinking that productivity and growth in each are somehow related. However, these terms may have very different meanings in these two applications. For

Schmaus 91

example, (on p. 21), Diamond talks of the productivity of scientists as measured by the number of articles they produce. Yet, he provides no arguments or evidence to the effect that more articles lead to more tech- nology, let alone to more economic growth. To take a crude measure of technological growth, does the number of articles produced by a scientist or engineer correlate with the number of patents?

Hence, before we turn to the question of how best to allocate resources "so as to provide the most scientific advance per dollar spent" (p. 34) we had better be clear about what we mean by scientific advance. If we simply reward scientists for the number of articles they produce, we will encourage what has been called "salami science," that is, slicing the re- search project as thin as possible to get as many articles out of it as possible. If we do not mean to measure scientific growth by number of publications, then how should we measure it?

I am also disturbed by the all-too-easy slide from science to technol- ogy. Supposedly, engineering is the application of the physical sciences to problems of technology. However, there is a growing literature, most notably by authors like Eugene Ferguson and Walter Vicenti, that sug- gests that engineering is relatively independent of science. Rather than waiting for science to supply the means for the solution of technical problems, engineers will forge on ahead, even in the absence of scientific knowledge. The use of wind tunnels in aeronautical engineering is a good example. No scientific theory can adequately characterize the flow of wind around an airplane. The mathematics is just too difficult for anyone, except perhaps Laplace's demon. So engineers build models and test them in wind tunnels. They did not derive the optimal shape of an airplane propeller from physics. Rather, they built dozens of different models, slightly varying the angles, sizes, and curvatures of the blades, and then tested them in wind tunnels to see which worked best.

I do not mean to suggest that technological advances are never the result of science. However, the relationships between science and tech- nology are rather complex, and Diamond's project will not succeed with- out careful analysis of these relationships. Because of the complexity of these relationships, research by economists like Romer and Rivera-Batiz relating economic growth to the level of research, which Diamond men- tions (on p. 31), in fact tells us very little. The problem is not simply one of distinguishing basic from applied research. This very distinction as- sumes that engineering research is applied science. Sometimes it is; some- times it is not. Testing propeller blades or airplane wings in wind tunnels is certainly research. It may even be research with economic pay-offs. But it is neither pure nor applied science.

The relationship between technology and economic growth also re- quires some analysis. Diamond does not consider that the nature of this relationship may depend on local conditions. He brings up the example of the former Eastern block countries needing "to know the impact of science on economic growth in order to travel the fast track toward West-

92 Knowledge and Policy / Summer/Fall 1996

ern economic productivity" (p. 34). However, in regions of the former East Germany, Czechoslovakia, and Poland, the environmental degrada- tion has been so severe as to make economic growth impossible until the environment is cleaned up. How to achieve economic growth in this part of Europe is an entirely different problem from how to achieve growth in "traditional third world countries," which Diamond also mentions. The technologies that would lead to growth in agrarian societies may be en- tirely different from those that would lead to growth in countries de- stroyed by over-rapid industrialization with no concern for consequences. In sum, there is no simple equation of more science yielding more tech- nology yielding more economic growth.

In fact, just as the technology that should be developed may vary according to region, so, too, may the appropriate form of economic growth. Diamond's casual references to technological developments that improve the "quality of human life" (p. 26) are insufficient. Quality of life issues have as much to do with the distribution of wealth in a society as with economic growth. Technological advances leading to economic growth may do little to improve the quality of most people's lives in a tightly controlled oligarchy. In societies with vast differences between rich and poor, increasing the average standard of living could mean very little.

Intellectual Property

A study of the reward structure in science must give far more atten- tion to issues regarding intellectual property than Diamond has in his article. For instance, when he asserts (on p. 29) that there is a conflict between academic patent-seeking and the Mertonian norm of openness, he seems to have forgotten that patenting, unlike trade secrets, is a way of making technological advances public knowledge. Engineers may be secretive about their work before their patents are awarded, but engi- neers and scientists may also be secretive about their work before their articles are published. Scientific research is not as open as Merton may have once thought it was. Diamond then says:

The main concern is that the increased incentives for scientists to produce patentable research will reduce scientists' incentives to discover and commu- nicate basic science, thus reducing the positive externalities from science as a public good, and muddying the university's claim for government or chari- table support.

The university's claim for government support may have been muddy twenty years ago, at least in the United States. Since then, however, the US Congress has passed the Patent and Trademark Amendment Act of 1980, which allows universities, small businesses, and non-profit organi- zations to obtain patents for government-funded research while at the same time granting the government a royalty-free license. Diamond should

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also consider the Stevenson-Wydler Technology Innovation Act of 1980, which allows for the establishing of industrial-technology centers at uni- versities that are jointly funded by industry and the government, and which legislates that patent rights are to be held by the centers and that royalties are to be reinvested in research.

As I mentioned in the last section, patents are only a crude measure o f technological growth. Part of the problem is that rapidly advancing tech- nology, especially in the fields of computers and genetics, has made the patent obsolete. Typically, large corporations prefer trade secrets to pat- ents, finding the application process for patents too time-consuming and costly. The award of a patent may take two or three years, in which time the technology being patented has become out of date. Large firms have the resources to develop, manufacture, and market the invention, while smaller firms do not. Hence, smaller firms with new inventions must seek outside investors in order to manufacture and market their prod- ucts. In order to obtain such funds, they must disclose their invention and risk having it stolen. In order to provide intellectual property protec- tion for new, rapidly developing technologies, Congress has passed such sui generis legislation as the Semiconductor Chip Protection Act of 1984.

In addition to new statutes, there have also been many recent impor- tant court decisions concerning intellectual property. This flurry of legis- lative and legal activity has changed the reward structure in technologi- cal fields in ways that Diamond's project will need to address. Intellec- tual property law also varies from country to country, complicating the relationship between technological development and economic growth.

Economics and Science Studies

Diamond may be overly optimistic about the potential for cooperation between the discipline of economics and the science studies disciplines. He appears to assume that historians and sociologists would be happy to provide richly detailed case studies, leaving economics to provide "a general theoretical framework" or the "big picture" (p. 34). Once I heard a philosopher of science make a similar proposal, only with philosophers instead of economists providing the theory, to an interdisciplinary meet- ing of science studies scholars. The reception was rather chilly. It re- quires the utmost tact and skill to make such a proposal, to have it accepted by the science studies community, and to encourage scholars to contribute case studies. Perhaps the best way for Diamond to proceed would be to set up a graduate program in which students would be encouraged to undertake such case studies for their dissertation research.

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94 Knowledge and Policy / Summer/Fall 1996

Paula Stephan and Sharon Levin

Art Diamond's "Economics of Science" provides a useful overview, particularly for noneconomists, of work in economics relating to science as well as work relating to academic labor markets. The article should be quite useful for those wishing to do work in the area, particularly those seeking annotated references. Any project that casts such an ambitious net will, however, undoubtedly omit certain topics that we think should be included, and include some that we would not choose. This article is no exception. In the short space allotted to us we briefly discuss these shortcomings of "commission" and "omission."

From the point of view of "commission" we object to the fact that Diamond consistently places studies of the economics of "economics" alongside studies of the economics of science. We grant that science and economics share many characteristics. But, by almost always writing of them in the same breath, Diamond becomes inattentive to ways in which they are substantially different. Three are particularly noteworthy. First, there is the issue of the importance of the team in science. Economists often write in two's, and occasionally in three's or four's. Five hundred (the reported extreme in particle physics), however, is unheard of in economics, and the article with ten to fifteen authors, extraordinarily common in science, virtually does not exist in economics. We do not think that differences of this magnitude are merely differences of degree. The investigation process becomes extremely different once teams begin to dominate the process. In a sense, Diamond (along with many others) assumes a specific form for the production function of science that is borrowed so heavily from economics that it does not permit the intro- duction of characteristics particularly common to science. If economists are to model science, it is important to understand the significance of the team and to realize that models that focus only on individual scientists may increasingly miss the mark.

By looking to the field of economics for inspiration, Diamond also omits two topics that seem to be of particular importance to the econom- ics of science. Both again point up differences between economics and science as fields. One issue relates to the importance of funding. The other is the "public" nature of science and what this has to say about the distinction between science and technology.

As economists we know the usefulness of having grants, and we cer- tainly devote considerable energy and resources to getting funding. But the stakes are very different for economists compared to most scientists when it comes to grantsmanship. In particular, many scientists simply cannot do scientific research without funding because they cannot do research without having a lab. Since labs are generally started and sup- ported by funding, this means that fairly early in their careers scientists must become successful at obtaining grants if they are to make their

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mark as researchers. It is not only the lab equipment that becomes the responsibility of the scientist. It is also the responsibility of the scientist to find financial support for graduate students involved in the program.

Finally, we would argue that a major contribution that economists have made to the study of science is to show how the reward structure of priority relates to the fact that scientific research has properties of a pub- lic good. The recognition that priority is the motivating force in science i~ not something that economists can take credit for. This Merton noted many years ago. Neither were economists the first to note the public nature of ideasmthe fact that when one individual gives another an idea neither has the less. Jefferson made statements concerning the public nature of knowledge more than two hundred years ago. What econo- mists did, however, is point out how well adapted the priority system in science is to the public good known as "knowledge" since priority makes individuals wish to share discoveries as quickly as they are made in order to insure that they will win the race and hence establish priority. Since "economics" also has aspects of a pure public good one could readily ask if this does not provide fuel for including economics in a study of the economics of science. The point that needs to be made, however, is that in scientific research, much more than in economic re- search, a line can be crossed where knowledge can be used to develop products for the market. Once this possibility exists (and becomes fairly common in an area such as biotechnology), priority rights can wither in comparison to "proprietary" rights, which give the owner the ability to profit from the innovation. The consequence for the sharing of informa- tion is significant, a point that is argued in the work of Stephan and Levin. Dasgupta and David think that this distinction is important enough to establish the difference between "science" and "technology." In their view scientists and technologists are interested in two distinct forms of property rights. Reputational rights are important to scientists. Propri- etary rights are important to those engaged in technology.

References

Dasgupta, P. and P.A. David (1987). Information disclosure and the economics of science and technology. In: Arrow and the ascent of modern economic theory, G.R. Feiwel (ed). New York: New York University Press.

Jefferson, T. (1904). Letter to Isaac McPherson, Monticello, August 13, 1813. In: Jefferson Cyclopedia, vol. 1, John P. Foley (ed.) New York: Russell and Russell, 1967.

Merton, R. (1957). Priorities in scientific discovery: A Chapter in the Sociology of Science. American Sociological Review 22:635-659.

Stephan, P. and S. Levin. (1996). Property Rights and Entrepreneurship in Science. Small Business Economics 8:177-188.