Open Source Biotechnology Project

Home

Theoretical Perspectives

Biotechnology Industry

Open Source

Project Design

Links

Revision history

Copyright (c) 2003 Janet Hope, Research School of Social Sciences, Australian National University, Canberra, ACT 0200. Verbatim copying and distribution of this site is permitted in any medium, provided this notice is preserved.

Sociology of Science

Current interpretations of the "norms of science"

Datastream theory

Introduction

Early sociologists of science placed great importance on the freedom of scientific communication and exchange. Legal protection of intellectual property rights was specifically condemned as a violation of scientific cultural norms which were supposed to align the self-interest of individual researchers with the common goal of scientific progress. Although most contemporary sociologists of science would not accept the existence of a set of functional scientific norms, up-to-date research in the sociology of science suggests that the exchange of information among scientists is an important aspect of scientific research which may be adversely affected by the expansion of intellectual property rights.

This section outlines theoretical developments in the sociology of science relating to the nature and significance of scientific exchange, beginning with the theories of Robert K. Merton and his colleagues and moving on to identify a useful and up-to-date sociological framework for the present study.

Traditional sociology of science: Merton's norms of science

Why did early sociologists of science consider free scientific exchange to be critical for scientific progress?

The concept of "scientific progress" dates from the sixteenth and seventeenth centuries and has long been linked with an ideal of free and open dissemination of scientific information. During the 1940s, sociologists of science formalised this conceptual link by theorising that a norm of common ownership of research results -- the norm of "communism", or "communalism" -- functioned together with other scientific cultural norms to align the interests of individual scientists with the overarching institutional goal of scientific progress, defined as the extension of certified knowledge. [19] According to sociologist Robert K. Merton and others of his school, these norms were not codified or necessarily explicit; rather, they operated as "prescriptions, proscriptions, preferences and permissions... legitimated in terms of institutional values... transmitted by precept and example and reinforced by sanctions". [20] Their existence could, it was argued, be inferred from a moral consensus among scientists expressed "in use and wont, in countless writings on the scientific spirit and in moral indignation directed toward contravention of the ethos". [21] Disagreement among scientists was acknowledged by sociologists, but regarded as deviant and generally attributed to insufficiently internalised norms. [22]

The "norms of science", especially the norm of communism, reflected what sociologists regarded as the essentially cooperative and cumulative nature of scientific research. In order to collaborate and build on each other's work, scientists needed access to a common fund of knowledge. The norm of communism was supposed to encourage scientists to contribute to this common fund by communicating the results of their research to other scientists: the norm ensured that secrecy was condemned, while timely, open publication was rewarded. [23] The norm was also supposed to preserve scientific knowledge within the public domain, where it could be freely used and extended. Merton wrote: "The substantive findings of science... constitute a common heritage in which the equity of the individual producer is severely limited. An eponymous law or theory does not enter into the exclusive possession of the discoverer and his heirs, nor do the mores bestow upon them special rights of use and disposition. Property rights in science are whittled down to a bare minimum by the rationale of the scientific ethic. The scientist's claim to "his" intellectual "property" is limited to that of recognition and esteem". [24]

Like the ideal of open dissemination of scientific knowledge, the notion that science should be commonly owned and pursued for the public good has long been associated with the concept of scientific progress. [25] In the 1930s and 1940s, leaders of the "radical science movement", from which the research agenda adopted by early sociologists of science evolved, set out to consider how science could best be organised for maximum social benefit. [26] Thus, Merton intended his examination of the normative structure of science as an introduction to a larger problem: the comparative study of the structure of science under different political conditions. [27] He argued that because the institution of science is only a part of the larger social structure, with which it is not always integrated, the scientific ethos can be subjected to serious strain when the larger culture opposes a scientific norm. [28] In the case of the norm of communism, Merton saw such conflict arising out of the incompatibility of the scientific norm with the definition of technology as private property in a capitalist economy. He referred specifically to patents, with their exclusive rights of use (and, he remarked, often non-use), and to the suppression or withholding of knowledge (for example, through trade secrecy) as being in opposition to the rationale of scientific production and diffusion. [29]

Notes

[19]["Certified knowledge": [Merton, 1996 (1957) [1942] #181], page 40-41/552-553. Can probably eliminate this footnote. May wish to mention others of Merton's School, e.g. Barber and Hagstrom. Eisenberg 1989 mentions them; probably so does Nowotny.]

[20] ([Merton, 1996 (1957) [1942] #181], page 39/551)

[21] ([Merton, 1996 (1957) [1942] #181], page 40/552)
[22] [Laudan, 1982 #216], page 260

[23] [Merton, 1996 (1957) [1942] #181], page 45/557

[24] [Merton, 1996 (1957) [1942] #181], page 44/556

[25] [[Eamon, 1975 #96] page 338-340]

[26] [Nowotny, 1996 #178], page xvii]

[27] Merton, 1996 (1957) [1942] #181], page 40/552

[28][Merton, 1996 (1957) [1942] #181], page 41/ 553. In each case of conflict between a norm and the wider social values, Merton's starting assumption was that the guiding principles of democracy (though these may be inadequately put into practice) are aligned with the scientific norm, so that the more democratic a society, the less conflict scientists find themselves subjected to (40: 552)]

[29] [Merton, 1996 (1957) [1942] #181], page 46/558].

More recent approaches

Current interpretations of the "norms of science"

The first genetically engineered organisms were created in the United States in 1973 by academic scientists Herbert Boyer and Stanley Cohen. By this time, mainstream sociologists of science had largely abandoned models of scientific research based on Merton's theory of scientific norms.

The reason relates to the historical development of the discipline: early philosophers and sociologists of science regarded science as unique among intellectual activities, and in particular, they thought that science as a discipline was defined by a high level of agreement among scientists about assertions of fact; for this reason early sociologists of science, including Merton, were chiefly concerned with constructing models to explain the phenomenon of scientific consensus. [71] However, during the 1960s and 1970s -- influenced by developments in the history and philosophy of science -- sociologists of science began to take a more cynical view of competition and collaboration within scientific communities. Questioning the existence of any distinctive scientific ethos, they turned away from an idealised picture of consensus among scientists and instead became preoccupied with studying scientific debate and disagreement. [72] As a result of this shift in focus, many of what had been central issues in the classical sociology of science came to be generally neglected, among them issues relating to intellectual property and the openness of scientific communication. Moreover, because the new "sociology of scientific knowledge" incorporates a diverse range of theoretical approaches, its insights have not been as easily accessible to scholars outside sociology as those of Merton and his colleagues.

Today, most sociologists of science doubt the reality of normatively controlled behaviour, preferring instead to treat references to norms in the course of scientific debate as either mere rhetorical tools or rationalisations for interest driven behaviour. [30] Nevertheless, the idea of scientific norms remained influential both within and outside the discipline of sociology, [31] and when questions about the impact of commercialisation on scientific research attracted the attention of intellectual property lawyers in the late 1980s, possible effects on the normative structure of science provided a natural starting point for discussion.

Notes

[71] [Laudan, 1982 #216], page 254-257

[72] [Nowotny, 1996 #178], page xix-xx: the biggest single influence from the philosophy of science was [Kuhn, 1970 #364]. See also generally [Laudan, 1982 #216], and footnote [30] above.

[30]See [Mulkay, 1976 #349]. Laudan has identified a number of criticisms of Merton's theory in more recent sociology of science literature ([Laudan, 1982 #216], page 261). First, disagreements among scientists cannot really be treated as minor deviations from a consensual norm: as Harry Collins, Trevor Pinch and others have shown, controversy is ubiquitous in science ([Laudan, 1982 #216], page 266; see also [Collins, 1994 #169]). Second, scientists who are doing their best to follow norms of disinterestedness, objectivity and rationality find themselves led to very different conclusions about what constitutes conformity with these norms: Mulkay has pointed out that since no rule can specify completely what is to count as following or not following that rule, we cannot assume that any norm can have a single meaning independent of the context in which it is applied ([Mulkay, 1980 #182]). Third, violations of Merton's norms are frequent, often rewarded, and sometimes even important for scientific progress: for example, Mitroff has presented substantial evidence of successful "counternormal" behaviour ([Laudan, 1982 #216], page 263; [Mitroff, 1974 #362], cited in [Eisenberg, 1989 #58], page 1048, footnote 130).

[31] Merton's colleagues included Warren O. Hagstrom, Bernard Barber and Harriet Zuckerman. Mulkay ([Mulkay, 1980 #182], page 112) describes a paper by Zuckerman ([Zuckerman, 1977 #363]) as "perhaps the best exposition of the Mertonian position"; see also [Zuckerman, 1988 #367] and [Cozzens, 1989 #365]. Hagstrom's "gift-exchange" theory of scientific exchange, in which individual scientists donate their findings to the scientific community and in return receive various forms of recognition ([Hagstrom, 1965 #366]), has been recently applied to molecular genetics by Katherine W. McCain ([McCain, 1991 #137, referred to in [Hilgartner, 1997 #49], page 2; see also McCain, 1995 #139 and McCain, 2000 #117]). Outside sociology, recent literature exploring the effects of university-industry relations also builds on Merton's theory (see [Etzkowitz, 1989 #200] and [Blumenthal, 1992 #132; Blumenthal, 1997 #143; Campbell, 2000 #134]), as does Rai ([Rai, 1999 #53] -- see below, fn 68).

Datastream approach

In an invited paper at the 1996 research tools workshop, sociologist Stephen Hilgartner moved to correct the neglect of issues relating to intellectual property and the role of scienctific communication by presenting a new model of scientific exchange -- the "data stream" model, developed in a 1994 paper co-authored by Sherry Brandt-Rauf -- incorporating insights from the new sociology of science. [73] The data stream model is described here in some detail because it is highly relevant to the question of how legal aspects of commercialisation affect patterns of access to scientific research tools.

The first insight from the new sociology of science to inform the data stream model is that the concept of "data" should be subjected to social analysis rather than treated in commonsense terms. [74] In contrast to earlier models of scientific research, the data stream model conceptualises data not as well-defined, stable entities -- the end products of research -- but as elements of an evolving data stream. [75] Data streams have four key characteristics. First, they are composed of heterogeneous networks of information and resources, including many categories commonly used by scientists to describe the input and output of their work: data, findings, results, samples, materials, reagents, laboratory techniques, protocols, know-how, experience, algorithms, software and instruments. However, because the meaning of each of these terms is context-dependent, and each element is linked to many others in the data stream, it may be difficult to assign any given element to a single category. [76]

Second, their elements range from mundane items which are part of the ordinary social infrastructure, such as water, electricity and computers, through elements specific to a research area but widely available either free or as commercial products, such as journal articles or assay kits, to specialised elements which are not publicly available but may be disseminated through personal contacts, and finally to novel or scarce elements available only by special arrangements. Hilgartner and Brandt-Rauf remark that critical issues in the analysis of scientific access practices most often concern elements of the data stream lying towards the "novel or scarce" end of this spectrum. [77]

The third property of data streams is that different elements have different information status. At one extreme, elements of a data stream may be generally accepted as reliable and valuable, while at the other, they may be so uncertain that even the scientists who produce them doubt their credibility or usefulness. Data are constantly interpreted and reinterpreted through the research process, so that scientists' perceptions of the reliability and value of particular parts of the data stream vary with time; this can be important in decisions about access, as scientists ask themselves whether data are "ready" for dissemination, or how much data are "worth". [78]

Finally, data streams are composed of chains of products. Scientists initially record data using primary inscription devices, such as x-ray film or electrophoresis gel, then convert the data into second, third or fourth order inscriptions; materials may processed and purified; electronic information may be subjected to a series of manipulations, and so on. Hilgartner and Brandt-Rauf argue that these translations and conversions affect access practices because they alter not only the information content and material form of the data, but also the purposes for which they can be used. [79]

The second insight which Hilgartner and Brandt-Rauf draw from recent social studies of science is that transactions involving data are negotiated within complex research networks. [80] They argue that analyses of data access patterns are often framed in terms of relationships between two parties -- the primary researcher or producer of the data and the secondary researcher who wants to obtain access -- but that in reality, each member of a research network is linked to many other people and organisations. Moreover, access practices are intimately involved in the construction and maintenance of such networks. Therefore, the analysis of data access practices should take account of a range of relevant actors. A decision about whether to grant access to data may involve many parties: a research team of scientists, possibly from several institutions or several fields of study, with different levels of training and of involvement in the project; government and corporate sponsors providing funds; perhaps also a host university, with all its internal bureaucracy. These parties may have different goals and differing claims to portions of the data stream, and they may disagree about the optimal means and timing of dissemination. [81] Similarly, audiences or markets for data do not necessarily consist of individuals or undifferentiated groups: they may include competing research groups, potential collaborators, authors of studies with conflicting results, gatekeepers who control key resources (e.g. department heads, corporate sponsors), potential markets for research based products, or venture capitalists. [82]

The third relevant insight from the new sociology of science is that there is a wide range of mechanisms available for granting, limiting or denying access to data, and that analysis of data access practices should take into account the incentives and strategic considerations associated with each. [83] While traditional models of data access emphasise peer recognition as a scientist's primary reward for discovery, with open publication as the primary legitimate means of achieving recognition, open publication is only one of many mechanisms for disseminating portions of a data stream. Data may be bartered in negotiations with prospective collaborators or sponsors, distributed to selected colleagues, patented, transferred by visitors being trained in new techniques, provided to a limited group on a confidential basis, bought and sold, pre-released to existing sponsors, kept in the lab pending future decisions about disposition, and so on. [84] Hilgartner and Brandt-Rauf again identify a spectrum, from limited access to widespread distribution, and argue that as access becomes more widespread, the competitive edge conferred by possession of unique data declines. Scientists can exploit this competitive edge by restricting access, using data to produce more data, or by providing carefully targeted access; or they may choose to provide widespread access in order to enhance their scientific reputation. [85] Other factors affecting decisions about how to provide access include timing, the portion of the data stream to be made available, and the costs and logistics associated with different modes of access. Hilgartner and Brandt-Rauf observe that in order to comprehend these strategic issues in relation to a particular area of research, it is necessary to acquire a detailed understanding of the structure of data streams in that area.

The fourth and final insight from the new sociology of science is to examine how access practices interact with strategies for commercialisation. [86] In his 1994 article with Brandt-Rauf and more recently, Hilgartner acknowledges that legal mechanisms of commercialisation may have a significant impact on scientific data access practices, noting that the law is clearly relevant to these practices because it addresses questions of ownership and control. [87] He describes the legal approach to data ownership as atomistic: it involves plucking items from the data stream and attempting to place them into discrete categories in order to designate an end product that may qualify for some type of protection -- patent, copyright, trade secrets, misappropriation, contract, or conversion (fn:transferred material is bailed property) -- [88] while data which are not construed as falling into one of these categories are considered to fall within the public domain. [89] Distinguishing between areas in which the law offers a relatively stable set of data protection mechanisms, and areas in which the law is still evolving (so that legal and scientific practices are simultaneously constructed in part through their interaction), Hilgartner proposes that future empirical research should focus on the relationship between scientific practices and the law. [89a] In particular, he believes it is important to understand how researchers try to employ legal mechanisms for controlling data access, what dilemmas and strategies are created by the disparity between the law's reductionist approach to ownership and the continuity of data streams and research networks, and how access practices, the law and the political economy of research interact to redefine legal regimes governing fast-moving areas such as biotechnology. [90]

(iii) applying these insights to determine the appropriate scope for intellectual property rights in science

Applying the data stream perspective to the issue of whether an emphasis on intellectual property in academic science should be expected to cause a reduction in scientific openness, Hilgartner suggests we need answers to a series of empirical questions. Do intellectual property considerations influence what portions of data streams are provided, to whom, and when? Do they introduce new sources of delay, or change the kinds of restrictions that are placed on the use of data? Do intellectual property considerations increase the complexity and formality of negotiations over access to data, make collaborations more unstable or difficult to form, or complicate the development and maintenance of shared understandings about control over data streams that are collectively produced? [91] Hilgartner argues that at any rate, we should not expect intellectual property protection to lead to an increase in openness among academic scientists: restrictions on openness motivated by possible commercial exploitation probably tend to propagate upstream from the point of potential commercialisation back into the research process, so that portions of data streams that are believed to be precursors of potentially patentable products are likely to be relatively tightly controlled. [92] He notes that existing empirical evidence suggests intellectual property considerations do actually reduce openness, [93] but warns that the effects of intellectual property protection on academic science will not be uniform across all fields, hypothesising that access practices are most intensively shaped not at the level of the discipline or field but at levels of research that can be defined in terms of a characteristic data stream and a particular competitive structure. [94]

Ultimately, in Hilgartner's view, the most important questions about scientific data access practices are normative. Like Eisenberg responding to the concerns of research scientists in the 1980s, Hilgartner asks whether the public domain should be defended against encroachment by proprietary categories of information -- though in the light of sociological literature problematising the concepts of "public" and "private" in scientific research, we should perhaps prefer his alternate formulation, in which the problem is expressed as one of deciding which data access policies are most likely to contribute to research productivity while promoting other social goals. [95] Hilgartner's emphasis on the policy implications of data access practices is consistent with Eisenberg's 1987 argument that intellectual property policy-makers should be interested in the norms of science because legal rules are more likely to achieve their desired effect if they resonate with scientists' existing conceptions of appropriate behaviour. [96] Not only does Hilgartner's empirical work demonstrate the continuing relevance of access issues in research science, [97] his theoretical approach is particularly valuable from a legal policy perspective because, unlike earlier theories of scientific exchange, it confronts the complexity of scientific research systems.

This complexity is reflected not only in the problems faced by policy-makers, but also in the wide range of techniques which have been used to try to influence access practices, from informal admonishment, through formal rules imposed on grantees by funding agencies to reforming national and international intellectual property laws, to in-built technical solutions such as those employed in relation to human genome research. [98] Hilgartner makes the important point that there are limits to what can be achieved by these methods: no single policy can resolve all the problems surrounding access to data in a particular field, because access issues reflect tensions -- competition versus cooperation, "public" versus "private" -- that are deeply embedded in the structure of scientific research.[99] Nevertheless, policy-makers must do their best to prevent and resolve disputes over access because, regardless of where the merits lie, such disputes interfere with research by diverting resources away from the central business of knowledge production.

One limitation of Hilgartner's theoretical approach is worth mentioning. Eisenberg's argument in favour of designing intellectual property laws with an eye to existing scientific incentives has recently been picked up by Robert Merges and Arti Kaur Rai, writing from a law and norms perspective.[100] Though promising, these analyses suffer from the necessity of drawing on the classical sociology of science literature for their understanding of scientific norms, even while acknowledging modern criticism of that literature. Hilgartner's focus on data access practices represents a move towards a more sophisticated understanding of the nature of these norms in the light of recent advances in the sociology of science, but there is still a gap between old and new approaches to the social study of scientific research; until these approaches have been reconciled as far as possible, we risk losing much that is still valuable in the classical sociology of science. There are signs of hope in Hilgartner's writing: he acknowledges that the data stream model does not take sufficient account of rhetoric based on traditional scientific norms, which may be important in shaping access negotiations, and points to the need to explain how collective definitions of appropriate conduct in science influence access practices. [101]

Aside from this limitation, Hilgartner's data stream model provides a sound sociological basis for analysing the relationship between intellectual property law (and other legal mechanisms for controlling access to data) and data access practices in areas of scientific research undergoing rapid commercialisation, like biotechnology.

Notes

[73][Hilgartner, 1997 #49]; [Hilgartner, 1994 #160]

[74] [Hilgartner, 1994 #160], page 358

[75][Hilgartner, 1994 #160], page 359

[76][Hilgartner, 1994 #160], page 359-360

[77][Hilgartner, 1994 #160], page 360

[78][Hilgartner, 1994 #160], page 360-361. Jordan and Lynch ([Jordan, 1998 #142]) describe how the polymerase chain reaction (PCR) technique has been adapted to different circumstances in science, medicine, industry and criminal forensics. Their paper explores in detail the evolution of the information status of a molecular biological technique from unreliable to standardised.

[79][Hilgartner, 1994 #160], page 361

[80][Hilgartner, 1994 #160], page 358; page 362-363

[81][Hilgartner, 1994 #160], page 363

[82][Hilgartner, 1994 #160], page 363

[83][Hilgartner, 1994 #160], page 358; page 363-366

[84][Hilgartner, 1994 #160], page 363

[85][Hilgartner, 1994 #160], page 364-365

[86][Hilgartner, 1994 #160], page 358

[87] [Hilgartner, 1994 #160], page 358; page 366-368; [Hilgartner, 1997 #49], page 7-8; [Hilgartner, 1998 #183], page 202

[88] Transferred material is bailed property.

[89] [Hilgartner, 1994 #160], page 366-367

[89a] [Hilgartner, 1994 #160], page 367

[90] [Hilgartner, 1994 #160], page 367-368

[91] [Hilgartner, 1997 #49], page 7. Or do intellectual property laws actually assist members of the research community to negotiate what is, irrespective of the existence of intellectual property rights, an inherently complex set of relationships? See below, reference to the information function of intellectual property rights (Arrow/Mandeville...), and to Powell's empirical work demonstrating the complexity of modern research networks in biotechnology ([Powell, 2001 #298]).

[92] [Hilgartner, 1997 #49], page 7.

[93] [Hilgartner, 1997 #49], page 7, refers to the work of Cambrosio, Mackenzie and Keating on the interaction of scientific and legal innovations in the commercialisation of monoclonal antibodies ([Mackenzie, 1990 #180]; see also [Cambrosio, 1998 #192]), to his own empirical work (see [Hilgartner, 1998 #183], [Hilgartner, 1995 #161]), and to the controversy which led to the formation of the Committee on Intellectual Property and Research Tools in Molecular Biology and to attempts to develop a Uniform Biological Materials Transfer Agreement (for more detail, see [Enserink, 1999 #130] and [Relations, 1996 #35]). Hilgartner also refers to [Blumenthal, 1992 #132], one of a series of survey studies investigating the effects of academic-industry relationships in the life sciences. Over the decade from 1984 to 1994, the results of these surveys were remarkably stable, indicating that academic researchers in the life sciences who were involved in research relationships with industry tended to be more secretive about their results than academics without industry support, and that a substantial number were influenced by commercial considerations in the choice of research projects ([Blumenthal, 1986 #102, Blumenthal, 1992 #132, Blumenthal, 1996 #144, Blumenthal, 1996 #145]). Two more recent studies in this series specifically investigated the prevalence and determinants of data withholding behaviours among academic life scientists. A 1994 -1995 national survey of life sciences academics in top United States research universities found that participation in academic-industry research relationships and engagement in the commercialisation of university research was significantly associated with delays in publication and refusal to share research results. Nearly one-fifth of respondents reported delays of over six months in publication of research results (... NIH considers more than 60 days unreasonable) in order to allow for patent applications or negotiations, to slow the dissemination of undesired results, to protect scientific priority or to resolve disputes over the ownership of intellectual property. ([Blumenthal, 1997 #143]). A 1996-1997 survey of US medical school academic staff found that 12.5% of medical school researchers had been denied access to other academics' data during the previous three years, and that those who were most likely to be denied access were those who had withheld research results from others, published more than 20 articles in the last three years, applied for a patent, or spent more than 40 hours per week in research activities. ([Campbell, 2000 #134]) The results of this second survey suggest that researchers who are perceived as being particularly successful or productive either commercially or academically may have difficulty maintaining sharing networks, perhaps because others are jealous or suspicious of highly successful colleagues. The fact that researchers who had previously withheld research results from others were frequent victims of data withholding is not surprising, but it does highlight the fact that exchanges of data among scientists are not usually one-off events; in bargaining terms, it may be as important in any given negotiation to preserve the relationships between the parties as to achieve a particular outcome.

[94] [Hilgartner, 1997 #49], page 8. Hilgartner's own empirical work has been conducted in the highly competitive field of genome research; he notes that in less competitive fields where goals are not so focused and other restrictions on data access are less prevalent, intellectual property considerations might be thought likely to produce greater reductions in openness.

[95][Hilgartner, 1994 #160], page 369. Cambrosio and Keating ([Cambrosio, 1998 #192]) give examples in which the private ownership of monoclonal antibodies became the key to public circulation. They argue (at page 176) that the issue of access pertains less to ownership in itself, or to the distinction between public and private sectors of the national economy, than to the construction of an infrastructure that allows specific techniques or tools to be transferred from local to extended networks. Private companies may be part of such an infrastructure.

[96][Eisenberg, 1987 #93], page 229-231

[97] [Hilgartner, 1998 #183] describes policies adopted by funders of genome research to manage tensions surrounding data access.

[98][Hilgartner, 1998 #183], page 205 and 208-210.

[99][Hilgartner, 1998 #183], page 215

[100] [Merges, 1996 #57] and [Rai, 1999 #53] Merges and Rai both share the aim of the "New Chicago School" of law and norms scholarship (footnote 67), i.e. that of identifying ways in which the state could use law to strengthen desirable norms or weaken undesirable norms, in this case within the scientific research community. Merges begins by acknowledging concerns over the impact of commercialisation, and in particular intellectual property rights, on the conduct of public scientific research. He points out that in terms of property rights theory, scientists have traditionally treated the public sphere more like a limited-access commons than a truly open public domain. He then argues that just as scientists asserted various informal property rights in relation to scientific information even before commercialisation (see [Hagstrom, 1965 #366]), current scientific practices effectively "water down" formal intellectual property rights (at least in dealings involving only research scientists) so as to minimise the impact of legal change. (So watering down has a damping effect...?). Merges argues that, since actual scientific practice appears always to have been influenced not only by the legal position with respect to ownership of scientific information but also by internal rules of the scientific community, it makes sense for intellectual property policymakers to "show respect" for those rules -- by which he means starting with the assumption that they help to establish desirable co-operation (in sociological terms, that they are "functional") -- and be prepared to adjust some of the rules of the formal intellectual property system to better reflect the fact that science originates as a product of cooperative effort. In particular, Merges favours formalising the experimental use defence to patent infringement and re-evaluating the patent utility requirement to ensure that inventions reach a significant degree of practical promise before a patent application is filed.

Rai begins by arguing that the evolution of academic scientific research norms from the period before 1980 to the present day illustrates the tenets of law and norms theory: specifically, as the background law has changed to encourage patenting by academic researchers, norms have evolved in the same direction. However, she argues that scientific norms have not changed to the extent of endorsing the patenting of upstream research in biotechnology, and to back up this argument she points to the refusal of certain major research universities in the US to seek patents for ESTs (above...; ([Rai, 2001 #54], page 707-708, summarising [Rai, 1999 #53]) ). Rai advocates government reinforcement of these "residual" norms of academic research to create a public domain that embodies the appropriate balance between research and development in biotechnology ([Rai, 1999 #53], page 151). (Rai's primary criticism of "full-blown" patent rights in fundamental scientific research is that such rights create significant transaction costs which may hinder rather than promote development; the problem of transaction costs is discussed further in the text below. See generally [Rai, 2001 #54], replying to [Kieff, 2001 #55].)

[101][Hilgartner, 1997 #49], page 6-7

Return to Home