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Adventures in the nature of trade : the quest for ’relevance’ and ’excellence’ in Canadian science 2002

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ADVENTURES IN T H E NATURE OF TRADE: T H E QUEST FOR 'RELEVANCE' A N D ' E X C E L L E N C E ' IN CANADIAN SCIENCE by Janet Atkinson-Grosjean M A . , S I M O N F R A S E R U N I V E R S I T Y , 1996 A THESIS S U B M I T T E D I N P A R T I A L F U L F I L M E N T O F T H E R E Q U I R E M E N T S F O R T H E D E G R E E O F D O C T O R O F P H I L O S O P H Y In T H E F A C U L T Y O F G R A D U A T E S T U D I E S ( I N D I V I D U A L I N T E R D I S C I P L I N A R Y S T U D I E S G R A D U A T E P R O G R A M ) We accept this thesis as conforming to the requited standard T H E U N I V E R S I T Y O F BRITISH C O L U M B I A N O V E M B E R 2001 © J A N E T A T K I N S O N - G R O S J E A N , 2 0 0 1 ' In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall riot be allowed without my written permission. DE-6 (2/88) ABSTRACT The study addresses: (1) changes i n Canada's science-policy climate over the past two decades; (2) impacts o f such changes o n the conduct and organization o f academic science; and (3) public- interest implications o f promoting, i n public institutions, research 'relevant' to private sector needs. W o r k i n g wi th in the interdisciplinary traditions o f science studies, the conceptual framework draws o n the cross-cutting tensions at the intersection o f public and private space, and basic and applied science. These tensions are articulated i n two opposing models: 'open science' and 'overflowing networks'. Canada's Networks o f Centres o f Excellence ( N C E ) program provides the study's empirical focus. Founded i n 1988, the N C E program rests o n dual goals o f research excellence and commercial relevance. It promotes a national research capacity that 'floats across' existing provincial institutions. The first part o f the study investigates the evolution o f the N C E program against the background o f Canadian science policy. The second part problematizes the not ion o f 'network' while investigating one o f the N C E s i n depth, examining the scientific, commercial , cultural, and spatial-structural practices that are the outcomes o f policy. Examinat ion o f these practices reveals not only the cultural and commercial shifts sought by policy, but also unintended consequences such as regional clustering; elitism and exclusion; problems wi th social and fiscal accountability; tensions wi th host institutions; and goal displacement between science and commerce. In relation to the overall problematic, the study constructs a new typology depicting network scientists as 'settlers', 'translators', or 'merchant scientists' according to their public/private, basic/applied orientation. The study then develops a set of broad conclusions about NCEs, especially those in the life sciences. (1) Translational research—at the nexus of public/private, basic/applied—is foundational for these networks. (2) As policy/practice hybrids, their spatial dynamics are highly enigmatic. (3) NCEs develop contradictory cultural norms. (4) Network effects resist standard assessments. (5) 'Public' and 'profit' seem to be problematic partners. (6) The recent historical focus of science policy has been myopic. The study expresses concerns for the public interest when commercial 'relevance' becomes an overarching goal of both science and policy. It concludes with a recommendation for open networks that would retain the flexibility of the network form, but would produce open rather than proprietary knowledge . iii T A B L E O F CONTENTS Abstract " Table O f Contents iv List of Figures vii List of Tables ; viii Acknowledgements ix Dedication x Acronyms and abbreviations used xi C H A P T E R 1: I N T R O D U C T I O N l Where this study fits, in theory 6 Details of the Study 8 Data Collection & Analysis 13 Chapter Outline 18 C H A P T E R 2: C O N C E P T U A L A N D A N A L Y T I C A L T O O L S 21 I. Mapping the Divides 22 Public and Private 22 Basic and Applied 27 The Spaces in Between 32 II. 'Open Science' or 'Science that Overflows'? 35 The Open Science Model 36 The Overflow Model 41 Mode 2 and Triple Helix 45 Policy Regimes 47 III. Translating Networks 51 Structural Issues 54 'Studying up' • 55 Summary 57 C H A P T E R 3. S C I E N C E P O L I C Y I N C A N A D A A N D T H E N C E E X P E R I M E N T 59 I. Historical Influences on Policy 60 Public Science in Canada 62 II. Evolution of the N C E Program 69 Models for the N C E Program 71 Territorial Struggles and Program Design 75 Mobilizing Networks; Changing Attitudes 79 Summary and Discussion 87 iv C H A P T E R 4: C O N F I G U R I N G T H E C A N A D I A N G E N E T I C D I S E A S E S N E T W O R K 92 I. Power of One 93 Enrolling the Core-set 101 II. Managing the Network 109 Institutional Friction 112 III. Spatial-Structural Dynamics 120 Regional Distribution 120 Elitism: Norms of Equity and Exclusion 123 Accountability as Social Reflexivity 128 Accountability as Value for money' 132 Summary Discussion 136 C H A P T E R 5: C U L T U R E A N D S C I E N C E 138 I: 'A Nation of Colleagues' 139 Inducing Solidarity 140 Face to Face Community 142 A Climate for Collaboration 144 Phase Transitions 148 II: Network Science? 152 Medical Genetics: An Overview 154 Space and Scale 156 Scaling Up 159 A Network Research Program? 161 Core Facilities: 'Where all the spokes converge' 167 Conclusion 175 C H A P T E R 6: F R O M S C I E N C E To C O M M E R C E 177 I. Understanding the Pipe 178 Industry Partnerships 181 II. Traversing the Pipe 186 The First Commercial Turn 188 The Second Commercial Turn 191 Resistance ... 199 i n . T-tViW f U n ? 201 'Funding Galileo' 203 Conclusion 206 C H A P T E R 7: A D V E N T U R E S I N T H E N A T U R E O F T R A D E 208 I. Localizing Cosmopolitans 209 II. Towards a new typology 212 Setder Science: 'Excursions into the land of ignorance' 214 v Translational Research: 'I wouldn't call it science' 222 Merchant Science: Worlds in Transition 226 Conflicts of Interest and Commitment 229 Incorporating merchant science 235 Discussion 237 C H A P T E R 8: C O N C L U S I O N S & I M P L I C A T I O N S 240 I. Argument and General Findings 240 II. Case Study: Conclusions and Implications 242 Translational research is foundational 242 Spatial dynamics are enigmatic 244 Cultural norms are contradictory 247 Network effects resist assessment 249 'Public' and 'profit' are problematic 250 Policy's focus is myopic 251 III. Suggestions for Future Research 253 IV. Summary 255 Appendix A: Networks Funded 257 References 258 vi LIST O F FIGURES Figure 1: Conceptual Matrix 10 Figure 2: Formal Interviews Conducted 17 Figure 3: The Linear Model of Research: WWII to mid 1970s 31 Figure 4: Stokes's Quadrant Model of Scientific Research 34 Figure 5: Model of Canada's Strategic Science Policy Regime in relation to the N C E program 90 Figure 6: C G D N Investigators, listed in 1988 Proposal for Phase I of N C E Program 106 Figure 7: Tri-Nodal Distribution of Funding 121 Figure 8: Growth in Partner Institutions and Principal Investigators Phase I to Phase III 149 Figure 9: CGDN's Core Facilities, End of Year One, Phase I (1990-1) 168 Figure 10: CGDN's Core Facilities, End of Phase II, beginning of Phase III (1998) 170 Figure 11: Industry Relationships, Phase II 184 Figure 12: N C E Program: Funded Networks 1989—2005, sorted by date of first funding 257 vii LIST O F TABLES Table 1: Share of university research funded by industry (%) in 1996,1990, and 1985 83 Table 2: Percentage of R & D Expenditures for the G7 Nations in 1996 84 Table 3: Total cash contributions to NCEs, 1990-2000 H4 Table 4: Funding Allocations by Institution, 1991 to 2000 120 viii ACKNOWLEDGEMENTS Withou t the generosity o f m y sources, there w o u l d be no study. I want to thank the scientists, pol icy advisors, adrninistrators, bureaucrats, and many others who contributed their time and reflections to help me understand their complex worlds. I was fortunate i n the calibre o f m y interdisciplinary research committee and the breadth o f their research interests: D o n Fisher, Educat ional Studies, and Stephen Straker, His tory o f Science (co- supervisors); Richard Er i c son , Sociology and L a w ; Derek Gregory, H u m a n Geography; and Judy Segal, Engl i sh . The Science and Society group and the Individual Interdisciplinary Studies Graduate Program, both housed at Green College, constituted my intellectual communi ty and I am grateful for the opportunities for discussion and support provided by both. Finally, embarking o n the adventures o f graduate studies at a relatively advanced age is less foolhardy when it is a folie a deux. Thanks to my partner i n this madness: m y husband and friend, Garnet Grosjean. W e made it, k id! ix DEDICATION In gratitude for provid ing a climate o f encouragement, and the intellectual and material resources that al low students to w o r k outside disciplinary lines, I dedicate this dissertation to the Individual Interdisciplinary Studies Graduate Program (Rhodr i Windsor-Liscombe) and Green College (Richard Ericson) at the University o f Bri t ish Columbia , and the Graduate Libera l Studies Program at S imon Fraser Universi ty (Hannah Gay , L e n Berggren, and Steve Duguid.) ACRONYMS A N D ABBREVIATIONS USED ACST Prime Minister's Advisory Council on Science & Technology ANT Actor-Network Theory (aka Translation Sociology) 'big pharma' Multinational pharmaceutical industry CBDN Canadian Bacterial Diseases Network CGDN Canadian Genetic Diseases Network CHEO Children's Hospital of Eastern Ontario CIAR Canadian Institute of Advanced Research CIHR Canadian Institutes of Health Research CSA Canadian Standards Association HUGO International Human Genome Organization ILO University-Industry Liaison Office (aka Technology Transfer Office; Commercialization Office IP Intellectual Property IPR Intellectual Property Rights IRAP Industrial Research Assistance Program (see NRC) ISTC Industry, Science, And Technology Canada ((now Industry Canada) MOSST Ministry of State for Science & Technology MRC Medical Research Council NABST National Advisory Board on Science & Technology NCE Networks of Centres of Excellence NRC National Research Council NSERC Natural Sciences & Engineering Research Council NSF National Science Foundation (US) ORF Ontario Research Foundation OST Observatoire des sciences et des technologies PENCE Protein Engineering Network of Centres of Excellence PI Principal Investigator PRECARN Pre-Competitive Advanced Research Network PRI Policy Research Institute PUS Public Understanding of Science R&D Research and development 'Sick Kids' University of Toronto Hospital for Sick Children SME Small and Mid-Sized Enterprises SPRU Science Policy Research Unit (UK) SSHRC Social Sciences and Humanities Research Council UBC University of British Columbia UQAM Universite Quebec a Montreal UT University of Toronto NB In quotes from interviews or documents, capitals in parentheses are my locator codes, not acronyms. C H A P T E R 1 : I N T R O D U C T I O N The creation o f the Networks o f Centres o f Excellence ( N C E ) program, i n 1988, was arguably the most dramatic change i n Canadian science pol icy since the Na t iona l Research C o u n c i l was established i n 1916. The N C E program can be understood as an attempt to create an interpenetrating system o f public and private research wi th in academic settings. The federal government sought to establish a university-based system o f national research networks—'research institutes without walls '—that wou ld target and develop commercial opportunities. The program is now a central element i n the government's ' innovation agenda', where scientific excellence, commercial relevance, and public/private collaborations are recurrent themes. B y the end o f the 2001 fiscal year, a total o f 29 networks had been funded i n areas deemed strategically important to Canada's prosperity and international competitiveness (see Appendix A ) . What makes the N C E effort an exemplar in Canadian policy history is the explicit attempt to turn the culture o f academic science towards commercial application, and to manage research on private-sector rather than academic principles. Purposive tensions are 'designed i n ' to these networks i n the form o f commitments to both fundamental enquiry and exploitation o f intellectual property; private-sector investment and public funding; academic ideals and commercial values. N C E s are institutionally ambiguous i n that they occupy ^determinate publ ic /pr ivate spaces, inside/outside the academy. A s 1 such, they 'float above' universit ies—which fund a significant por t ion o f their costs—with little accountability. This abundance o f novelties would seem attractive to anyone interested i n the sHfting terrain o f science, economics, and policy. Y e t surprisingly, the program has largely escaped scholarly notice. 1 M y interest in N C E s began wi th an outsider's curiosity about the workings o f academic science and the way it appears to be changing. In earlier graduate work, 2 I 'd examined science as a master narrative o f modernity, presenting 'the scientific wor ldview' as a metaphor for Enlightenment values o f rationality, predictability, and order. In a wor ld characterized by quite opposite values, I 'd searched for a different metaphor: a 'postmodern science' that wou ld more accurately reflect today's fragmentation and loss o f certainty. Revisi t ing that work, I find little i n the way o f critical reflection or recognition that science itself might require some unpacking. Despite much talk o f the embedding o f science i n society, and the socially constructed nature o f knowledge, m y approach was deeply conservative. Science was treated as an institutional black box, governed by Mer tonian ideals. The 'booming, buzzing, confusion' o f actual scientific practices was nowhere to be found, and the structural and organizational contingencies that constrain and shape these practices were completely absent. M o v i n g o n to interdisciplinary doctoral work i n science studies and the poli t ical economy o f science, I studied the way market forces and neoliberal public-sector reforms were affecting research funding and science policies. T h e conversion o f public science into private (intellectual) property, and academic and state institutions into market players, was progressing rapidly and wi th relatively little 1 Clark (1998) is one exception, providing a comparative but atheoretical overview of various 'formal knowledge networks.' As well, as ongoing research program includes interest in certain NCEs, for example, Dalpe & Ippersiel (2000), Dalpe, et al. (2001). 2 Atkinson-Grosjean (1996) 'Science in Postmodern Times', unpublished MA terminal project. Simon Fraser University 2 resistance. I found this curious because Canada's structure and values, and the heterogeneity o f its federal and provincia l poli t ical institutions, generally preclude radical change. I could find few, i f any, evidence-based studies o f the phenomenon and no disinterested calculations o f the social and financial costs and benefits involved. It seemed that the pol icy o f 'privatizing' public science and its institutions was proceeding ideologically, rather than by rational calculation. Such policies were assumed to fuel innovat ion and maximize wealth creation, but that was a highly contestable assumption. M a n y economists were point ing to the relative inefficiency o f proprietary approaches to public science. 3 Meanwhile , other critics 4 questioned a calculus that collapsed the social into the economic, and turned universities into 'knowledge factories'. It was clear that these policies could fundamentally realign the publ ic /pr ivate divide wi th potentially far-reaching consequences. The shift f rom 'public ' to 'private' i n Canadian university science was accelerating rapidly; intellectual property rights were becoming the hegemonic currency o f the research economy. Gross revenues from royalties and license fees grew more than threefold between 1991 and 1997, while industrial research funding saw more than a fourfold increase ( A U T M 1998). 5 O f the almost 400 spin-off companies created i n Canadian universities since 1980, more than 6 2 % had been formed since 1990, at an average rate o f 23 per year (Statistics Canada 1999). The 'free f low o f ideas' into the public knowledge base tends to falter when public research becomes privatised. A review o f various literatures indicated that researchers become reluctant to share 3 For example, Nelson and Romer, 1998:59; Nelson 1996; Mazzoleni & Nelson 1998; Rosenberg 1998, and see Chapter 2, following 4 See the reference list for works by David Noble, Sheila Slaughter and colleagues, Janice Newson, and Claire Polster. 5 AUTM is the US-based Association of University Technology Managers. Since the majority of Canada's major research universities participate in the AUTM survey, these are fairly reliable indicators of growth. Conversely, the majority of Canadian universities do not participate in the AUTM survey, suggesting that commercialization concentrates in the major institutions, as in the US. This is confirmed by the Statistics Canada survey (1999:17), which shows that the 12 most active universities account for 75% of invention reports and licenses, and two thirds of new patent applications. Of the remaining universities, medium-sized institutions account for the majority of activity. The number of universities that can effectively pursue commercialization activities and academy-industry partnerships thus appears limited. 3 information wi th colleagues; sponsored research contracts sprout clauses that restrict dissemination; public and private 'partners' squabble about the ownership o f intellectual property; and universities develop policies governing disclosure o f research wi th commercial potential. Such practices are rationalized o n economic grounds: i f science is to be harnessed i n pursuit o f competitive advantage, subscribing to free-flowing knowledge is deemed hazardous. O n the basis o f the literature reviews and statistical evidence, I developed a hypothesis that some kind o f radical break from past practices was underway. Academic science was turning away from disinterested enquiry and open sharing towards commercial interests and 'secret knowledge'. Academic forms o f organization were being replaced by new and dynamic cross-sectoral networks. The hypothesis drew o n the tension between research pursued for understanding and research pursued for use and o n associated attitudes towards ownership and access, secrecy and openness. The argument was posit ioned wi thin the shifting and historically contingent distinctions dividing 'public ' f rom 'private' and 'basic' f rom 'applied'. M y larger purpose was to question the impact o f shifts i n the organization and ethos o f science o n 'the public interest'. T o w h o m is a privatized science accountable? I asked. Wha t is gained and what is lost when longstanding institutional distinctions dissolve? These questions constituted the 'moral purpose' o f the project. A pi lot study revealed flaws i n the way the hypothesis had been formulated. T o avoid the errors o f my earlier work, I had adopted an empirical approach that wou ld open up the black boxes marked science and public interest. Interviews quickly demonstrated that I was, nevertheless, focusing almost exclusively o n structural forces. In the first place, the way my thesis was framed left no r o o m for agency, yet the autonomy that individual scientists exercised over their work came through clearly at an early stage, as d id the choices some had made to engage in 'academic capitalism'. 6 In the second 6 The term was coined by Ed Hackett in a 1990 article and developed by Sheila Slaughter and Larry Leslie (1997) in their book 'Academic Capitalism: Politics, Policies, and the Entrepreneurial University' 4 place, it seemed to matter wh ich type o f science I was addressing. Whi l e network forms o f organization were becoming a default requirement for funding, commercial interests were largely absent i n whole areas o f the natural sciences. It soon became apparent, therefore, that I should focus o n changes i n the biomedical sciences rather than, say, physics or chemistry. Next , an examination o f the historical record quickly dispelled notions o f 'radical ' or 'revolutionary' breaks. Before 'networks' there were 'invisible colleges', and the relations between science and commerce seemed anchored i n a long evolutionary process. Compar ing the end o f the 19 t h century and the start o f the 2 1 s t , for example, I perceived differences o f degree rather than k ind i n academy- industry ties. Finally, as expected, I found many examples o f federal steering o f the research agenda, but few indications o f direct interference by 'big business'. Thus the empirical realities o f the data disciplined my opening assumptions, al lowing a more 'grounded' approach to emerge. Adjusting for these new insights, the core assumptions seemed sound and the study could proceed. 5 Where this study fits, in theory The study participates i n the interdisciplinary tradition o f enquiry k n o w n as science studies. Science studies is a broad church embracing many sects, including the three that in fo rm this project: micro- studies o f laboratory and organizational practices; the economics o f science; and science policy studies. Because the study incorporates a case study o f the work that individual and institutional actors do to construct, extend, stabilize, and maintain complex networks and power relations, it is most at home i n the 'Paris Schoo l ' o f science studies, where such networks have long been a topic o f enquiry. M i c h e l Ca l lon , B runo Latour, J o h n L a w , and others have worked to develop A c t o r - N e t w o r k Theory ( A N T ) , or 'the sociology o f translation', for the past 30 years. But despite the powerful descriptive vocabulary it has accumulated, A N T carries little explanatory weight, as many, including the principals, have argued. A workshop at Keele Universi ty i n 1997, and a subsequent book (Law & Hassard 1999), focused actor-network theorists o n what 'comes after' A N T . A l though this study's primary purpose is empirical, rather than theoretical, I hope it w i l l in some way contribute to that debate. O n e o f A N T ' s weaknesses is 'explanation by incorporation' . N i c k Lee & Steve B r o w n (1994) complained o f A N T ' s 'colonial ' expansion. Because everything is enrolled into the network, nothing remains outside. O n e o f the results is that surrounding institutional structures are (under)explained, or explained away, as network outcomes. I find this unsatisfactory. L i k e D a n i e l Lee K l e i n m a n (1991 & 1998), I believe that actor-networks are constrained and shaped i n important ways by the institutional structures that provide their context. I see these structures as important already-existing features external to the network, rather than as the contingent outcomes that A N T depicts. Accoun t ing 6 for the transition f rom 'micro-structure' to 'macro-structure' is an ongoing challenge i n A N T and this study participates i n that challenge. A related problem is that A N T adopts a deliberately agnostic stance towards the broader polit ical , economic, and social implications o f what it describes. In a theory that erases al l boundaries between science and society, such agnosticism seems to me a contradiction, since i t separates science f rom its consequences. I think an agnostic stance is a luxury A N T can no longer afford. Thus, A N T needs to be 'stiffened' wi th several critical starches and this study may indicate just where those stiffeners can be most effectively applied. First, I point empirically to the myriad ways biomedical networks are bounded and closed by members, w h o thereby invent 'insides' and 'outsides'. Second, through the empirical evidence, I can challenge A N T wi th normative questions about the nature o f public and private science and h o w the public interest can be served. T h i r d , I develop a typology that classifies network scientists by their response to poli t ical-economic pressures. Th is new typology operationalizes the intersection o f publ ic /pr ivate , basic/applied divides i n networks, and reinterprets A N T ' s not ion o f 'translation'. Finally, i n pursuit o f this effort to give A N T an afterlife, I fo l low M i c h e l Ca l lon into the current controversy i n economics o f science and science policy, where 'open science' takes o n the network model . B y weighing the arguments against m y empirical results, I hope not only to contribute somerliing to that debate, but also to contribute to policy studies and in fo rm future policy. In that regard, the study's primary contribution is empirical: collecting and systematizing data o n the Networks o f Centres o f Excellence ( N C E ) program and the Canadian Genet ic Diseases Ne twork i n the context o f Canadian science policy. 7 Details of the Study A review o f the current science policy environment suggested that, for the reasons indicated earlier, the N C E program w o u l d reward attention. In fact, the research reported here constitutes the first full-length, academic analysis o f this program. T o extend the study beyond the structural level, I wou ld conduct a detailed review o f one o f the networks, using ethnographic techniques. (Time and cost constraints precluded more than one in-depth case study.) A number o f criteria were developed to guide selection, inc luding research sector; posi t ion o n the pub he/private cont inuum; longevity; density o f linkages; amount o f funding; and location. The best match wi th my selection criteria was the Canadian Genet ic Diseases Ne twork ( C G D N ) . C G D N was one o f the first networks funded under the N C E program. Inaugurated i n August 1990, it brought together medical genetics researchers across the country, under the leadership o f Scientific Di rec tor Michae l Hayden. B y 2001, support received from the program totalled $50 M . Currendy, some 50+ researchers belong to the network, together wi th 11 universities and hospitals and eight companies. The research program covers four integrated themes: gene identification; pathogenesis and functional genomics; genetic therapies; and genetics and health care. 'Core facilities' i n major centres undertake work such as D N A sequencing, genotyping, and bioinformatics ttaining. The network opened a ' ch i ld ' organization—the Centre for Molecular Medic ine and Therapeutics— i n Vancouver i n 1998. Merck Frosst, a founding industry partner, contributed $ 1 5 M towards the Centre. The network's commercial prowess can be seen in the major intellectual property (IP) agreement it brokered between Schering Canada Inc. and the Universi ty o f Toron to ; at the time, the largest university IP agreement i n Canadian history. The agreement was based o n the 1995 discovery, by a network researcher, o f two genes for early-onset Alzheimer 's disease. Schering's 8 initial $9M funded a three-year research program in the development of drugs and technologies to treat and prevent Alzheimer's. Over the long-term, the agreement has a potential value of $>34.5M, not mcluding royalties. In 1997, when the N C E program announced a 14-year 'cap' for all networks, C G D N learned its funding would 'sunset' in 2005. This policy change set in motion a major strategic shift. In 1998, the network incorporated itself as C G D N Inc. It adopted a corporate organizational form and an aggressively commercial focus. The goal was to maximize revenues from license agreements and equity holdings in order to replace the $4.5 M a year in federal funds that would cease in 2005. Many of the scientists interviewed expressed ambivalence at the direction in which the network was moving. On one hand, they knew action was needed if the network was to survive. On the other hand, they regretted the attendant loss of collegiality and openness that had marked earlier days. If one imagines public/private and basic/applied as cross-cutting dimensions (see Figure 1 below), C G D N had, until this point, concerned itself predorninandy with 'public science' and 'basic research'. Approximately 70% of N C E core funding supported fundamental, discovery-based research, with 20% going to early-stage development of technologies with commercial potential (the remaining 10% supports networking and administration). But the goal of sustaining the network beyond 2005 accelerated a downward shift to the 'private science' half of the matrix. A key question is how this policy shift affects the public's social and economic return on investment in C G D N and NCEs more generally. 9 Figure 1: Conceptual Matrix Public Basic Science Applied Science Private The tension between the public and private faces o f N C E s became increasingly apparent over the course o f the study. Countervail ing currents o f confidentiality and openness ebbed and flowed around the project. Scientists spoke to me freely, for example, while gatekeepers erected formal blocks to access. The contradictions give an indication o f the normative and ethical boundaries that are constandy negotiated i n these networks. A t the federal level, the vast majority o f people w h o designed and implemented the program i n the mid-1980s had disciplinary roots i n the sciences. M o s t held P h D s and were associated wi th the Research Counci ls . In interviews, their commitment to a scientific culture o f openness prevailed. In contrast, 'career bureaucrats' remained guarded, refusing to provide key materials o n the grounds o f commercial a n d / o r cabinet and /o r third party confidentiality. Access was formally denied. The fact that the research was sponsored by one o f the three federal funding councils ( S S H R C ) carried no weight. The word ing o f the formal denial sidestepped an outright claim that N C E files were exempt from disclosure. B u t access w o u l d require implementation o f the provisions o f the Access to Information and Privacy (AIP) Ac t s and every individual document wou ld have to be requested by name. N o t only was this quite impossible without prior access to the files, the delays and costs w o u l d have been 10 unmanageable. The nature o f the problem is demonstrated i n the fol lowing extracts from correspondence (e-mail, January 21, 2000). Because of the sensitivity of the files in this case, we really have no option but to 'do it by the book'. This means that in order to gain access to documents in N C E files, we will have to ask you to submit formal Access to Information Act requests.. .Many documents within [NCE files] would have to be reviewed on a line-by-line basis to identify information subject to exemption. And in many instances a decision about the operation of a particular exemption could only be made in consultation with other federal institutions, with networks, and with any other parties affected by the disclosure. Canada's information commissioner has criticized precisely this type o f strategic use o f the Access to Information A c t by public servants. H e speaks o f 'the stubborn persistence o f a culture o f secrecy i n Ottawa' (Reid 2000b) and complains o f too-frequent recourse to claims o f third-party 'commercial sensitivity' to avoid the release o f documents (Reid 2001). W h e n public information disappears behind a screen o f privacy erected by public servants, questions are bound to be raised about accountability and the abuse o f power. 7 A t the network level, the contrast between the exaggerated discretion o f professional staff and the openness o f network scientists was marked. A n d the balance o f power between scientific officers and professional staff appeared to be highly delicate, given the goal o f commercia l sustainabiHty by 2005. C G D N ' s scientific director, Michae l Hayden, belongs to both cultures. H i s instincts were to be open but his posi t ion required h i m to attend to the concerns o f staff. Hayden was the first person I interviewed in the pilot stage. H e was an enthusiastic participant and his support for the study never wavered. A s my design o f the study developed, Hayden assured me all involved w o u l d cooperate fully. Bu t despite his endorsement, professional staff at the network's 7 This is not an isolated case. My experience confirms that of another doctoral researcher who attempted to explore a similar topic in Ottawa during the early 1990s. Claire Polster was seeking financial and statistical information on the proliferation of federal support programs for industry-relevant university science; some of the data required for her study were denied to her. Other data were not tracked, and what was tracked often proved inconsistent and unreliable (Polster 1993) 11 administrative centre, where I 'd hoped to be based, initially refused access. Commerc ia l sensitivity was the formal reason given: 'many o f our interactions wi th industry involve the element o f confidentiality and an "outsider" may impact those discussions negatively' (e-mail, M a r c h 31 1999). Hayden suggested timing might be the problem; professional staff were simply 'too busy right now ' but they would co-operate when the workload moderated. T o accommodate the delay, I reordered the study and undertook the federal phase next, returning to the network several months later. A t that time, Michae l Hayden arranged for m y participation in the annual scientific meeting and the International H u m a n G e n o m e conference. H e also asked professional staff to arrange an 'internship' for me i n the various facets o f network governance and to facilitate my access to network documents. Aga in , staff were s low to comply. A further ten weeks o f refusals, negotiations, delays, reversals, and interventions were required before a compromise was reached and l imited access granted. There wou ld be no internship and access to materials was curtailed. B o a r d and committee minutes and commercial files were denied to me. I was not allowed to photocopy or remove any o f the materials provided, nor could I attend board, committee, or staff meetings. O n l y information that staff considered ' i n the public domain, i.e. financial and annual reports.. .funding proposals and interim reports' (e-mail, M a y 17 2000) wou ld be provided. B y the time I began m y fieldwork at the network's offices, 15 months had elapsed since my initial request for access. Despite repeated requests, I was never allowed to consult board and committee minutes. Eventually I asked for a written rationale. In the response, elaborate framing sequesters aspects o f this public entity as private. 'Management has received a legal op in ion recommending against public disclosure o f Board Minutes . The C G D N Board is a legal entity and as such, holds the right to maintain 12 confidentiality o f its in-camera meetings. Management does not ho ld the right to disclose those proceedings' (e-mail, June 2000). I was able to compensate for the lack o f access to records by p rob ing quite deeply i n m y interviews wi th private-sector and researcher board members. I also found evidence o f board and committee discussions and decisions by triangulating against the materials prepared by the network for N C E site visits. In this way, I was able to form an adequate understanding o f the key decisions over the years. Data Collection & Analysis The majority o f data for the study was derived from in-depth interviews and participant-observation, supplemented by analysis o f documents and financial and statistical reports. The preliminary phase o f the study lasted from Fa l l 1998 through Spring 1999.1 collected and analyzed documents, then interviewed C G D N officers i n Vancouver and network researchers i n Vancouver , E d m o n t o n , and Calgary. A t the same time, involvement i n a separate study 8 o f industry l iaison offices ( ILOs) i n four universities (two i n B C and two i n Alberta) allowed me to solicit information o n network commercialization practices and network-university interface issues from the 1 5 I L O officials I interviewed. The next phase, extending from Fa l l 1999 through Winter 1999, focused o n the federal level and the officials responsible for the N C E program. D u r i n g a week-long fieldwork visit to Ottawa, a total o f 19 individuals 9 involved i n the program's initiation, development, and ongoing maintenance were identified and interviewed. His tor ical details o f pol icy formation and program-building were sought, 8 'Academy-Industry Relations in North America,' Dr Donald Fisher, principal investigator, 1998-2001. Funded by SSHRC. 13 as wel l as the rationale behind certain 'design features', such as the twin criteria o f scientific excellence and commercial relevance. A t the same time, documents and reports spanning the N C E ' s history and pre-history were collected from the program directorate. These materials included annual reports; program evaluations; public relations materials; newsletters; and various committee reports. Particular attention was paid to the acquisition o f program-wide information o n partnership and intellectual property arrangements, company creation, and funding patterns. The final phase o f data collection encompassed the C G D N case study, wh ich extended from Winter 1999 through Fa l l 2000, wi th follow-up visits to June 2001. In M a r c h 2000,1 attended the annual scientific meeting i n Vancouver , one o f the network's key cultural events. The purpose was to present a paper introducing m y study; conduct and solicit interviews; observe interactions; ask questions; and generally familiarize myself wi th the science and business o f the network. Direct ly after, I represented C G D N as a volunteer media relations officer at the International H u m a n Genome Project's annual conference, wh ich the network was co-hosting. These meetings were invaluable introductions to network culture and science, and the vast 'industry' that molecular biology has become. In addition, over the course o f the study, I made site visits to three research labs i n Toron to and several to the Centre for Molecular Medicine and Therapeutics, i n Vancouver , for interviews and observation. B u t the core o f m y fieldwork centred o n the network's cramped administrative headquarters i n the ' N C E Bui ld ing ' , at the Universi ty o f Bri t ish Co lumbia . Here, for a period o f eight weeks, I observed the workings o f the network from a makeshift desk i n the hallway. O v e r the course o f the study, I interviewed a selection 1 0 o f board members and private sector partners and all current and former professional staff. In selecting wh ich o f the 50+ network researchers to interview, I focused o n the 'founder population' , i.e. the 16 scientists who remained 9 In the interim, the scope of the aforementioned SSHRC study had been extended to include NCEs, so this phase of my data collection process overlapped with that of the larger study. Data from 15 of the 19 interviews were shared. 14 active i n the network, o f the 21 who had signed the original 1988 proposal. E leven o f the 16 were interviewed. F o r balance, I also contacted two o f the five founders who had left the network and three more-recent recruits, two from the start o f Phase II (1994-5); another f rom the start o f Phase III (1998-9). In total, the C G D N phase o f data collection incorporated 40 formal interviews wi th 31 people. Interviews were semi-structured, a l lowing scope for reflection and opin ion . Informants were first asked to describe their recollections o f the network-building process, then answered a series o f questions about the science produced i n the network; culture and relationships; commercialization practices; governance; and whether they had noted any problems or 'sticking points ' over the years. The relative weight o f these questions was adjusted to reflect the informant's role i n the network. The majority o f interviews were conducted i n Toron to , Ottawa, and Vancouver—three o f the network's four main nodes. I was unable to visit Montreal , the fourth major centre, but interviewed two researchers f rom M c G i l l , one by telephone and another during his visit to Vancouver . Throughout the study, I attempted to compensate for the 'single-case' focus by identifying and interviewing other knowledgeable individuals wi th interests in the N C E program. These included 'insiders' involved i n networks other than C G D N , and 'outsiders' such as university technology managers and pol icy consultants. The purpose was to generate a cross-section o f fact, opinion, and experience about N C E s from which shared patterns could emerge—patterns that would not be discernible i n a single case." Access was controlled by staff; I was not permitted to contact board members and industry partners independently The technique, originally developed by Glaser and Strauss, is called 'maximum variation'. See Merriam (1998: 62) for a brief and useful description In all, a total o f 74 formal interviews 1 2 were conducted wi th 65 people i n nine Canadian and two U S cities (Figure 2 below). C G D N professional staff were interviewed twice, at the beginning and m i d - point o f the study, to check changing conditions and perceptions. Michae l Hayden was interviewed three times: a wide-ranging discussion at the beginning o f the study helped define my general focus; another at the mid-poin t dealt w i th the human genome program and the network's involvement in genomics; a third during fieldwork covered specific questions that had arisen and shifts I had noted. C G D N ' s current N C E program officer was interviewed twice; once, i n Ottawa, i n October 1999, and again i n Vancouver during the annual scientific meeting i n M a r c h 2000. O f these, 30 were shared with the previously mentioned SSHRC study. 16 Figure 2: Formal Interviews Conducted People Interviews Senior policy makers 4 4 N C E Directorate 7 7 N C E Program Officers 6 7 C G D N 'founder' researchers —Current 11 14 —Former 2 2 C G D N 'new* researchers 3 3 C G D N Professional staff 4 9 C G D N Private Sector 5 5 Non-NCE scientific networks 3 3 University administrators 2 2 University technology managers 15 15 Policy Consultants 3 3 Total People/Interviews 65 74 Initial analysis o f the data began during fieldwork. Da i ly write-up o f field notes helped me to reflect o n what I was discovering and identify questions for subsequent fol low up. Af te r fieldwork, during the intensive analysis o f the data, I continued wi th the practice o f daily written reflection. These notes reminded me o f where m y thinking had been i n relation to the study and suggested directions I might explore. They proved invaluable i n helping me structure the eventual write-up. The materials I had collected included financial and statistical reports. M y background as a professional accountant allowed me to analyze financial and performance data using generally accepted accounting principles and conventions. K e y ratios were calculated i n an attempt to determine the program's economic costs and benefits, and comparative rates o f publ ic /pr ivate participation and reward. Such calculations are unable to account for social dimensions o f the research questions, since social costs and benefits resist quantification. Nevertheless, these indicators can suggest the underlying social calculus and it is in this spirit they were sought. 17 The policy and program material was analysed and written up first. Several conference papers and articles were produced from these historical and interview data. 1 3 This process had the effect o f 'stabilizing' a large part o f the evidence. The 'macro ' level o f the program's composi t ion and policy context could then be set aside i n favour o f a m u c h finer-grained analysis o f the network's micro- level practices. The material lent itself naturally to this bifurcation, leading me to question theoretical claims that actor-networks could not be bound wi th in structural frames. Next , network interviews were sorted into four broad categories: 'network scientists', 'professional staff, 'board and private sector', and 'other'. Provis ional code-books were developed from iterative readings o f the transcripts i n each category, wh ich were then coded and recoded using software tools o f my o w n devising (rather than a commercial qualitative analysis program). O n c e I was satisfied the codings were consistent, each category was sorted by main code and sub-codes. T h e n all categories were combined i n a single database and sorted. A numerical weight was assigned to the codes according to frequency across categories. The dominant codes became headings to wh ich less- frequent codes were assigned o n the basis o f 'family resemblances'. These then provided a framework to guide the structure o f the dissertation. In turn, these dominant codes were collapsed into broad interpretive themes, to aid theory-building. Chapter Outline In this chapter (1) I have provided a broad overview o f motivat ion and methods. Chapter 2, extends the discussion o f publ ic /pr ivate , basic/applied, and the public interest. I focus o n the fundamental tension between 'open science' and proprietary knowledge and set up the two conceptual models wh ich guide the study. In the second part o f the Chapter 2,1 discuss some o f the analytical tools 1 3 For example, Atkinson-Grosjean, J. 1999c, 1999d, 1999e, 2000a, 2000b, Atkinson-Grosjean, et al. 2001, Fisher, et al. 2001, Atkinson-Grosjean 2002 18 that will be brought to bear, from actor-network theory and science studies more generally. Chapter 3 addresses the historical and structural factors contributing to the development of the N C E program. The C G D N case study begins in Chapter 4 where I describe the network-building activities of this group of medical geneticists and the institutional identity they constructed. Chapter 5 demonstrates the way the network evolved a culture and sense of community, critically examines the rhetorical construction of the network's research program, and points to the authentic locations of 'network science'. These two chapters represent the 'public' face of the network; the following two chapters move to the 'private' side of network identity. Chapter 6 describes the trajectory from 'public' to 'private' and 'basic' to 'applied' in terms of the network's development of intellectual property and construction of a commercial portfolio. Chapter 7 develops a typology of network researchers based on their alignment along the public/private, basic/applied dimensions. The last chapter summarizes the study and its findings, derives a number of conclusions and policy implications, and makes recommendations for future research. In summary, what follows is an enquiry into the material and epistemic spaces of the N C E program in general, and the Canadian Genetic Diseases Network (CGDN) and its scientists in particular. Detailed descriptions of the social, cultural, and material mechanisms at work draw authenticity from the voices of federal public servants, network officers, private-sector partners, university administrators, and scientists themselves. I trace the trajectory of the N C E program and C G D N over time, attending to the ways federal policies are translated into specific research projects, practices, and institutional arrangements and recording how scientists embrace, resist, or ignore these initiatives. The purpose is to achieve a greater understanding of changes in the organization and motivation of academic science as well as the way these changes affect the public's manifold 19 interests i n the science it funds. Close examination o f h o w Science is planned and produced and the Public Interest is served i n this one particular case w i l l contribute to the development o f science studies and policy research more generally. C H A P T E R 2 : C O N C E P T U A L A N D A N A L Y T I C A L T O O L S The conceptual framework o f this study relies o n the relationship between two sociological and epistemological distinctions: the publ ic /pr ivate and basic/applied divides, and this chapter commences wi th a review o f their relationship. The space where these dimensions intersect is particularly relevant to this study and I examine various attempts to describe it. D o n a l d Stokes (1997), for example, calls the space 'Pasteur's Quadrant' . Others speak of'strategic research', 'emergent science', or 'Jeffersonian science'. 1 4 I w i l l introduce two models that present opposing interpretations o f the relation between the divides: the open science mode l and the overflow or network model . The tension between these contrasting approaches to public and proprietary knowledge runs throughout this dissertation. In the last part o f the chapter, I introduce the analytical tools I w i l l use to understand the conduct and culture o f science i n networks. 1 4 See, respectively, Godin (2000-3), Callon (in press), and Holton & Sonnert (1999) 21 I. Mapping the Divides Public and Private The publ ic/pr ivate demarcation is one o f the core sociological distinctions. Norber to Bobb io (1989) calls it one o f the 'grand dichotomies ' o f western thought. Y e t like other such dichotomies this one begins to collapse o n closer examination, becoming not one but a number o f related oppositions that nest one wi th in the other like Russian dolls (Starr 1988). Is the stock market, for example, public or private? F r o m one perspective it is a mass o f individuals pursuing private interests; but from another, it is a public social and cultural aggregation. Wha t do we mean by 'the private sector'? Usually, we mean private businesses, large and small. Y e t many o f the largest corporations are 'public companies' , owned by mill ions o f shareholders, some individual , some huge and institutional. Bu t huge institutional investors are themselves often 'public ' , in that they represent the pensions and investments o f mil l ions o f people. Wha t do we mean by 'the public sector'? Many publicly owned institutions and agencies are 'private' i n the sense that they are exempt from direct, or even delegated, public control ; for example, c rown corporations; universities; even departments and bureaucracies o f the state. Wha t does it mean to speak o f 'public ' and 'private' life? F o r individuals i n 'public life' we designate whole areas exempt from public scrutiny (private matters o f conscience, convic t ion, family, and morality). But when these aspects o f private life impinge o n or attract the public interest, they enter the public domain and become 'public knowledge'. Does my body belong to me? I f so, I should be able to control what happens to my genetic material. B u t legal cases have been fought and w o n by researchers who have taken cell lines from unsuspecting patients and patented them for profit, rendering bodies 'publ ic ' by acts o f 22 privatization. O n discovering their colonizat ion, patients fought not for the right to privacy but for the right to profit for and from themselves. 1 5 What about ownership o f the human genome? In the vast undertaking to map it, public researchers raced against a private company (Celera Genomics) wh ich sought to patent and profit f rom 'the stuff o f life'. Because results o f the public effort were held in c o m m o n i n the public domain, Celera was able to use them to advance their o w n project. The controversy raised awareness o f the role o f patent law i n privatizing public research. Patents make knowledge private by circumscribing ideas wi th property rights, so i f a public university takes out a patent o n a publicly funded discovery, is it 'privatizing' that knowledge? O r is it securing the ownership o f that discovery for the public domain? These questions without answers help to illustrate that publ ic/pr ivate is a negotiated, discursive space rather than a fact o f the wor ld . Bu t two core ideas help connect the many different meanings. These are, as Paul Starr, states, 'that public is to private as open is to closed, and that public is to private as the whole is to the part' (1988:2). In the first sense, public and private oppose each other along the dimension o f accessibility. That is to say, the openness and transparency o f public space, public life, and publ ic disclosure contrast to the opaqueness and concealment o f private space, private life, and personal communications. In the second sense, 'publ ic ' is synonymous wi th ' common ' , as i n public op in ion , public health, or the public interest; this sense has merged wi th the sense o f 'official ' o r 'state'. Thus , to Starr, 'public ' can carry three contrasting meanings from wh ich 'privatization' represents corresponding withdrawals. In the first sense, 'publ ic ' means open and visible, as i n public life and 1 5 The classic case is Moore vs Regents of the University of California, see Boyle (1996). John Moore sued researchers and their university for stealing his cell line (uniquely resistant to hairy-cell leukemia) for profit and without his consent. He lost the case. 23 social relations while 'private' means a withdrawal from sociability and the decline o f public culture. In the second sense, we invoke the 'general public ' or the public-at-large, to speak o f public action and civic concerns i n contrast to private concerns and the pursuit o f self-interest. The third sense o f 'public ' is the domain o f c o m m o n (state or community) ownership, as opposed to appropriation by an individual or group. These senses o f open, closed, and c o m m o n w i l l reappear throughout this study. The locus classicus o f the publ ic/pr ivate distinction can be found i n Greek and R o m a n thought. It represented the separation o f the private household and its economy (oikos) f rom the sphere o f collective public institutions—the polls or respublica. Collectively, heads o f households constituted the 'body pol i t ic ' or public realm (Arendt 1959:56). A s Arendt explains, a physical space, a boundary or no-man's land, separated private households. The boundary demarcated one property from another, and marked o f f the household from the city. Arend t identifies the spatial significance o f this boundary wi th that o f the law. In the same way that the law harbored and protected the public domain that was poli t ical life, fences sheltered and protected the private property o f households (Arendt 1959:57). Between the poli t ical (public) and intimate (private) domains, Arend t interposed a third space: that o f the social. B y feudal times, publ ic/pr ivate distinctions i n property and affairs had developed a certain taxonomic and ideological slipperiness. The emerging concept o f the corporation under R o m a n and C a n o n L a w is a case i n point. A corporation interpolates between the individual and the collective, the poli t ical and the economic; i n a sense, it is bo th and neither public and private. After the church invoked the corporate form to sever itself f rom state control , the principle o f incorporat ion spread into secular law, where it established the rudiments o f a public sphere free o f ecclesiastical control (Huff 1997). Thus , 'we find i n the 1 2 t h and 1 3 t h centuries the widespread emergence o f a vast array o f legally autonomous [corporate] entities that were bestowed wi th a composite bundle o f legal rights and wh ich presumed the legal authority o f jurisdiction, that is, legitimate legal authority over a limited territory or domain ' (Huf f 1997:28). These newly incorporated (literally, embodied) entities included cities and towns, merchant guilds, charitable organizations, professional associations and universities (ibid.). Subsequendy, according to Huff , corporations contributed to the rise o f the public sphere by faciUtating the extension o f trade i n the high middle ages. The original trading companies were extensions o f the private economy o f the family, i n that assets and investments entrusted to the company were commingled wi th family assets. The developing legal theory o f the corporation made it possible to disentangle familial and business affairs, mstalling a chstmction that converted what was previously private (oikos) into public (the market). H u f f argues that corporate law made it possible to differentiate between individuals and the corporate body. The corporate collectivity was construed as a single, legal person. A distinction n o w existed between ownership and jurisdiction, especially concerning assets, liabilities, and debts. B y providing for allegiance to the corporat ion rather than to individuals, the continuity o f the enterprise was ensured. The historical development o f these concepts , according to Huff , provided for the emergence o f distinctive public and private spheres o f action and interest. This separation laid the foundation for the emergence o f modern science as a 'public ' institution wi tb in 'publ ic ' universities by establishing a 'neutral space' o f thought and action. A s H u f f explains, The medieval intellectual elite o f Europe established an impersonal intellectual agenda whose ultimate purpose was to describe and explain the world in its entirety in terms of causal processes and mechanisms. This disinterested agenda was no longer a private, personal, or idiosyncratic preoccupation, but a publicly shared set of texts, questions, commentaries, and in some cases, centuries old expositions o f unsolved physical and metaphysical questions that set the highest standards o f intellectual enquiry.. .A disinterested agenda of naturalistic enquiry had been institutionalized... It thereby laid the foundation for the breakthrough to modern science (Huff 1997:33). 25 The science that emerged from the Renaissance took place i n relatively small, interdependent communities o f practice where scientific advance rested o n the veracity o f individuals. It depended o n a culture o f honour, epitomized by the posit ion wi th in the social order o f the 17 t h century Eng l i sh gendeman-scientist (Shapin 1994). The product ion o f scientific knowledge was, and remains, according to Shapin, a mora l enterprise built o n mutual trust. Personal trust is the 'great civility' and the currency o f an 'economy o f credibility' i n the conduct o f science. Within such small interdependent groups as the 'core-sets' of specialized scientific practices, the economy of credibility is likely to flow along channels of familiarity. The practitioners involved are likely to know each other very well and to need each others' findings in order to produce their own. Here...the pragmatic as well as the moral consequences of distrust and skepticism are likely to be high (Shapin 1995a:269) Thus trust i n the public institution o f science rests o n trust i n the private morality o f its individual practitioners. The 'publ ic ' nature o f scientific knowledge rests o n the collective construction o f a collective good, under conditions requiring reliance o n the work o f others. W i t h i n this 'moral economy o f truth' public and private, scientific and social, become inseparable. Similarly, Habermas (1989) conceived the public sphere as a social space, first emerging in 17 t h century Engl i sh coffee-houses and salons, where 'private' individuals came together to engage in rational-critical debate and thereby further the 'publ ic ' interest. Habermas distinguishes this 'authentic' public sphere from the 'public ' realm o f state interests. The authentic public sphere is a dimension o f private life: 'a public o f private people ' who came together to further the ' c o m m o n good' . In Habermasian terms, however, the c o m m o n good and the public sphere itself are undifferentiated. A s i n classical Greece, where w o m e n and slaves were confined to the home, rational-critical discourse i n the public domain was a white, male, bourgeois prerogative as was the 26 'scientific revolut ion ' itself. T h e legacies remain, as w i l l be seen i n the empirical section o f this study. 1 6 Basic and Applied W i t h the onset o f modern science i n the 17 t h century, questions o f public and private begin to map onto distinctions between basic science, applied science, and what lies between. These distinctions are part o f an ancient argument that has its roots i n the classical differentiation between theoria and praxis m early Greek thought ( G o d i n 2000-3:3; A r e n d t 1959). The path o f theoria travels f rom Plato, through Descartes and N e w t o n . The path o f praxis from Aristot le , through Montaigne and Bacon. T o u l m i n (1990) shows h o w the rationalism o f early modern science came to dominate the experiential and empiricist values o f Renaissance humanism. F o r 16th century humanists, the central demand was that thought and conduct should be reasonable (rather than rational) tolerating social, cultural, and intellectual diversity. B u t after the Enlightenment, says T o u l m i n , ideas became decontextualized. Scientists began to conduct 'pure research'—a careful and systematic search for the abstract universal laws through which G o d governed nature (see also Latour , 1993 for a parallel discussion). A fundamental part o f Francis Bacon's critique o f institutionalized scholarship in the 16 t h and early 17 t h centuries was its ignorance o f the concerns o f industry and commerce, the crafts and trades. Consequendy, an important part o f his call for reformation involved bringing the two together so that i n the reformed academy 'the sounds o f industry' w o u l d be heard 'at every hand' . 1 7 1 6 For an interesting discussion on historiographical approaches to the relation of public sphere and private life, see Dena Goodman's (1992). A definitive critique of the inadequacy of the liberal model of the public sphere descibed by Habermas is available in Fraser 1997 1 7 Thanks to Stephen Straker for this point 27 A c c o r d i n g to Benoi t G o d i n , 1 8 the w o r d 'research', meaning thorough examination, emerged from French origins i n the 16 t h century. The concept o f ' pu re research' was first used i n the mid -17 t h century, to distinguish abstract theorizing from 'mixed research' dealing wi th concrete subjects (Kl ine 1995:196). It came into general use towards the end o f the 1 9 t h century, as part o f a contrast pair, the opposing element being industrial or 'applied' research. Thomas Henry Hux ley (1880) had an aversion to the pure/appl ied distinction, stating I often wish this phrase 'applied science' had never been invented. For it suggests that there is a sort of scientific knowledge of direct practical use, which can be studied apart from another sort of scientific knowledge, which is of no practical utility, and which is termed 'pure science'. But there is no more complete fallacy than this. What people call applied science is nothing but the application of pure science to a particular class of problems (quoted in Kline 1995: 194) Huxley was making a nice distinction, ignoring the fact that 'technology', particularly i n industry, had its o w n distinct history and trajectory. Others recognized the linkages between 'pure' and 'applied' research, or disputed the proper place o f each. A s early as 1840 Prussian chemist, Justus Leib ig , sought to establish a university program that w o u l d combine the search for pure knowledge wi th product ion tiraining for students; he was strenuously opposed by faculty (Turner 1982). Leno i r (1998) describes a number o f late 1 9 t h century G e r m a n initiatives to l ink the demands o f the pharmaceutical industry wi th the interests o f academic science, first through consulting and contracting arrangements, then the establishment o f independent institutes. N o b l e (1977) traces the connections between U S academic engineers and industrial research problems from the early decades o f the twentieth century. V e b l e n was complaining about too-close relations between universities and local industries as long ago as 1918. Well-documented debates" from the interwar years address the propriety o f ahgning academic and industrial research and patenting publicly- funded research. Conflicts o f interest and commitment were not u n c o m m o n ; there were disputes 1 8 In this section, I draw quite extensively on Godin's series of working papers (2000, 2001, and ongoing) for the Observatoire des sciences et des les technologies, UQAM. His project constitutes a history of attempts to measure the impacts of scientific research. 28 about intellectual property ownership and concerns about o n the proper role o f the university. A s we grapple wi th similar concerns today, the continuities argue against claims that a radical break i n moral and organizational culture is i n progress. The terms 'pure' and 'applied' dominated the discourse unti l the 1930s, when 'fundamental' research came into occasional to avoid the moral connotations o f ' pu re ' (Kl ine 1995:196). Subject-matter, e.g. theoretical or applied physics, defined what was pure or applied rather than the motivat ion o f the researcher, as is the case today. The phrase 'basic science' was first coined by Julian Huxley (1934) (grandson and intellectual heir o f T . H . Huxley) as part o f a typology i n w h i c h 'pure' and 'applied' each contained two categories: 'background' and 'basic' for the first; 'ad hoc ' and 'development' for the second. Bri t ish socialists like Huxley , and his colleague J o h n D e s m o n d Bernal were inspired by the apparent success o f ' p l anned ' Soviet science. In The Social Func t ion o f Science (1939), Bernal advocated state steering o f science through socioeconomic controls and goals. In contrast to this image o f social engagement, Michae l Polanyi and others w h o opposed 'Bernalism', founded the Society for Freedom i n Science to defend the ideal o f a 'pure science', unfettered by social constraints (Polanyi 1940; Sheehan 1993). A c c o r d i n g to Polanyi (1962:62) 'you can k i l l or mutilate the advance o f science [but] you cannot shape it ' ; any practical benefits are incidental and unpredictable. The dialogue between Bernal and Polanyi o n social direction and autonomy i n science is the origin o f our continuing debates about the relative allocation o f resources to basic and applied research (David 1995). The same debates were being engaged i n the interwar period i n the U S , and the 'Polanyi ' posi t ion dominated. A t the time, academic science was controlled by 'a tacit oligarchy o f eminent scientists 1 9 See, for example, in Weiner 1986 and 1989; Geiger 1988 & 1990; Noble 1977. 29 who shared a number o f ideological convict ions ' (Geiger 1990: 19). A m o n g these convictions, according to Geiger, were the beliefs that: (1) society should support basic science, because society benefited from its discoveries; (2) funding should be reserved for the 'best' scientists, because their productivity was established; (3) who the best scientists might be was a matter for the best scientists themselves to determine, and (4) government funding carried the taint o f politics, so private support was preferable. Rober t K . M e r t o n captured the Polanyi Zeitgeist i n The Normat ive Structure o f Science (1942). Mer ton defined pure science by its characteristic methods and institutional structure, and also by the distinctive cultural values and mores that bound the behaviour o f scientists. In combinat ion, these clearly demarcated 'science' f rom 'technology'. The Bernal posi t ion o n socioeconomic relevance was adopted by Harley Ki lgore , a N e w D e a l senator from West Virg in ia . K i lgo re wanted publicly supported science to be politically and socially accountable. H e suggested that the sole criterion for public funding should be 'manifest social utility' i n the product ion o f knowledge (David 1995). Vannevar Bush , an engineer and former president o f M I T , who headed the wartime Office o f Scientific Research and Development ( O S R D ) , took the Polanyi and M e r t o n side o f the debate. Bush (1945) po l i t i cked M e r t o n and Polanyi's v is ion o f a freestanding science governed by a system o f b inding universal norms that underpinned the mora l authority o n wh ich it rested. H e adopted Julian Huxley 's term 'basic research' to describe what this autonomous university-based collective produced, and articulated a 'linear mode l o f innovat ion ' to l ink basic research to eventual socio- economic returns. The 'pipeline' is the dominant metaphor o f the linear model . Fundamental discoveries are fed into one end o f the pipe and move through various stages o f development until they emerge onto the market at the far end o f the pipe. The resultant growth fuels the economy and returns taxes, to maintain the cycle (see Figure 3 below). The linear mode l was a powerful argument for 'market failure' i n that basic science was viewed as a public good, requiring public funding and the 30 open dissemination o f research results. It was argued that government investment i n basic research must be preserved, and science left to regulate itself, i f the pipeline was to fuel the innovat ion process and produce wealth. These arguments were the foundation o f the postwar 'social contract for science', 2 0 a contract secured by a promissory note o n the eventual but completely unpredictable technological and social spin-offs o f basic science. Figure 3: The Linear Model of Research: WWII to mid 1970s Basic research was 'performed without thought o f practical ends' and wi th the sole purpose o f contributing to 'the understanding o f nature and its laws'. A c c o r d i n g to Bush , i f basic research is contaminated by premature considerations o f use it loses its creative edge. B u t i f left alone, it provides the raw materials for innovation and becomes, at a distance, 'the pacemaker o f technological progress' (1945:19). Thus , i n the form o f technology transfer, basic science generates social and economic returns o n the state's investment—but only i f scientists are allowed to pursue it, wherever it leads, without government controls. Government 's role was simply to support university researchers wi th the resources they needed to produce knowledge. 2 0 See David Guston's extensive work in science policy and the social contract, for example Guston (2000a); Guston and Kenniston (1994) 31 Scientists viewed Bush's 'Endless Frontier ' as 'a charter for pure science' (Ho l ton and Sonnert 1999:53). It enshrined the basic/applied dichotomy i n U S science policy, and entrenched the 'ideology o f the autonomous researcher' (God in 2000-1:9). Bush argued that 'the responsibility for the creation o f scientific knowledge - and for most o f its application - rests o n that small body o f men and w o m e n w h o understand the fundamental laws o f nature and are skilled i n the techniques o f scientific research' (Bush 1945:7). O n l y peers could decide the value and merit o f research. Consequendy, 'there was no need for governments to worry about the evaluation and measurement o f science and scientists, and to track the output o f research' ( G o d i n 2000-1:9). Politicians and policymakers initially refused Bush's gambit. The Nat iona l Science Foundat ion, for example, was not established unti l 1950, wi th far more restricted levels o f authority and autonomy than Bush had anticipated. Bu t i n the late 1950s, i n the aftermath o f Sputnik, the linear explanation o f the relation between basic science and application became compell ing. B u s h had argued that without significant investment at the source o f the knowledge pipeline, no innovations wou ld issue from the mouth , and the nation wou ld fall behind its competitors. Sputnik seemed to demonstrate the truth o f this claim. Fears o f Soviet dominance o f 'the space race' generated immediate revisions i n the U S federal research budget. The 'golden age' o f state-sponsored research had arrived. The Spaces in Between Setting up a dichotomy between basic and applied dissolves deep connections between the search for solutions to practical and technical problems and the search for fundamental understanding. A s D o n a l d Stokes (1997; 1995) argues, and as the historical record suggests, basic research has never been divorced from application, and distinctions between research directed to useful ends, and research directed to the advancement o f knowledge, are deeply misguided. Stokes suggests that a large propor t ion o f university research i s—and always has been—both useful and fundamental. H e suggests that the basic/applied dichotomy renders this significant segment o f the research spectrum invisible, and that the linear model 's one-way flow obscures the number o f basic research questions arising from purely technological phenomena. In furthering his claims, Stokes (1997) employs an iUuminating typology. H e classifies fundamental 'understanding-based' research as 'Bohr 's Quadrant ' , and applied 'use-inspired' research as 'Edison 's Quadrant'. Research that is both useful and fundamental resides in between, i n 'Pasteur's Quadrant' . 2 1 Pasteur's research commitment , according to Stokes, was twofold: not only to understand the microbiological processes he discovered, but also to exert practical cont ro l over their effects i n products, people, and animals (1997:71-2). 'The mature Pasteur never d id a study that was not applied while he laid out a whole fresh branch o f science [microbiology]'. (1995:5). In Stokes's view, it is this dual commitment to understanding and use that characterizes m u c h o f university research. 'Every one o f the basic scientific disciplines has its modern form, i n part, as the result o f use- inspired basic research. W e should no longer allow the post-war v is ion [of Bush] to conceal the importance o f this fact' (Stokes 1995:6). In further contrast to Bush's one-dimensional linear model , Stokes (1995:7-8) sees the rise i n fundamental scientific understanding and the rise i n technological know-how as two loosely coupled systems. Instead o f the latter being dependent o n the former, each progresses along largely independent trajectories, w i th no intervention from the other. Bu t at times, Stokes argues, the mutual influences are profound and can go i n either direction, wi th use-inspired basic research often cast i n the l ink ing role. A t that point they conjoin i n a 'seamless web' . Whi l e it is a commonplace that new technologies w i l l be increasingly science-based, the under-appreciated concomitant, argues Stokes, is that 'more and more science w i l l be technology-based' (1995:8). 2 1 A similar formulation, found in Holton and Sonnert, 1999, adopts "Newtonian Science', 'Baconian Science' and 'Jeffersonian Science' as the ideal types. The latter emphasizes the role of state patronage in promoting scientific advance. 33 What goes unsaid but is nevertheless clear f rom the discussion is the relation o f 'understanding' and 'use' to 'public ' and 'private'. I f B o h r is the former and E d i s o n the latter, Pasteur occupies the shifting space between public and private. Clearly, as w i l l be seen throughout this study, today's biomedical sciences epitomize these 'spaces i n between'. In my empirical findings, physician- scientists describe m u c h o f what they do as translational research, a concept that fits the intermediate space between bench and bedside, laboratory and market. A second concept, transitional research feeds the findings o f translation back into basic questions, as Stokes predicts. Po l icy instruments, such as the N C E program, that are geared to both scientific excellence and commercia l relevance, address research in Pasteur's Quadrant. The implications o f Stokes's insight are being explored by others. 2 2 The mode l is reproduced below. Figure 4: Stokes' s Quadrant Model of Scientific Research Research inspired by: Considerations of Use? N o Yes Quest for Fundamental Understanding? Yes Pure Basic Research (Bohr) Use-inspired Basic Research (Pasteur) N o Research directed to particular phenomena (Wissenschaft) Pure A p p l i e d Research (Edison) Source: Stokes (1997) In the fol lowing section, I summarize two opposing theoretical perspectives towards policies on university research, bo th o f wh ich can lay claim to the space between basic and applied, public and private. The 'open science' model , grounded i n evolutionary economics, argues that commercial exploitation o f proprietary knowledge by public universities undermines the pursuit o f use-inspired basic research. T h e 'overflow' or 'network' mode l grounded i n science studies, argues that the genie 2 2 Stokes had a long and distinguished career in US science policy. He died of leukemia shortly after Pasteur's Quadrant went to press. Work has continued in Branscomb, et al. 1999; Nelson 1996; Nelson and Romer 1998; Holton and Sonnert 1999; Branscomb, Holton and Sonnert 2000; Sonnert and Brooks 2000). 34 is already out o f the bottle, that institutional distinctions are largely irrelevant anyway, and that the resulting state o f affairs (inter-sectoral fluxes, flows, and circulations) is largely beneficial. II. 'Open Science' or 'Science that Overflows'? In 1954 Jonas Salk, o f the Universi ty o f Pittsburgh, announced he had developed a vaccine for pol io . In a television interview, he was asked why he had not taken out a patent o n an invent ion clearly wor th mil l ions. Salk replied, ' H o w can you patent the sun?' (Zalewski 1997:51). Salk's point—that no one should o w n or profit f rom discoveries about the natural world—has been overtaken by events. Patents are n o w used routinely to translate university research into proprietary knowledge, as part o f a systematic effort to turn universities towards the market by 'capitalizing' their o w n research (Etzkowitz , et al. 1998). Th is is where basic/appl ied and publ ic/pr ivate dimensions overlap. Universi ty intervention i n the commerciahzation process is highly contested o n bo th social and economic grounds. The first questions the social costs o f commodifying universities and their knowledge, holding that these (public) institutions should remain outside the (private) system o f market exchange. 2 3. O n e argument is that while the costs o f advancing basic knowledge are socialized—taxpayer supported—the benefits f rom its application are privatized, i n the form o f intellectual property rights (Noble 1997). Some make an ethical argument that when research is publicly funded, neither researchers nor their universities have mora l rights to proprietary control over resulting products (for example see G o l d m a n 1989). These are powerful debates and I o n l y touch o n them here. N o t e however, that the posi t ion o f social critics is aligned, rather curiously, wi th the second line o f contestation wh ich advances the economic interests o f industry. 35 This 'open science' mode l problematizes the new commercial role o f universities and university- researchers as impediments to industry and therefore to innovat ion and wealth-creation The focus o n intellectual property rights creates tensions by redefining the role o f universities. Once relatively open suppliers o f ideas to industry, they become more closed and costly sources o f information (Rappert and Webster 1997). The Open Science Model Articulated by Dasgupta & D a v i d (1994) as 'the new economics o f science', the open science perspective advocates a return to 'no-strings attached' public funding o f basic science; a recommitment to the open publication o f results, and removal o f expectations that universities should be involved i n commercialization. Essentially, this mode l seeks to ' turn back the clock' to the linear understandings o f the post-war G o l d e n A g e discussed above, when universities produced 'public ' knowledge, industry exploited it, and an arm's-length relationship kept the two sectors at a healthy distance (see Figure 3). Us ing Starr's formulation, discussed earlier, 'public ' knowledge produced i n universities is c o m m o n property. In the classic formulations o f Richard N e l s o n (1959) and Kenne th A r r o w (1962), 'public goods' are the result o f market failure i n that knowledge is considered to be 'non-appropriable' and 'non-rival ' . A s summarized by K e i t h Pavitt (2000), 'the simple economics o f basic scientific research' are such that basic research generates information that is cosdy to produce, but virtually cosdess to reproduce and re-use. It therefore has the properties o f a public good and deserves public support. I f business firms try to capture all the benefits o f basic research for themselves, either through trade 2 3 For Canadian thinking on this issue, see for example Buchbinder 1993; Polster 1998; Newson 1998. For the US, see Sheila Slaughter and colleagues at the University of Arizona, for example Slaughter and Leslie 1997; Slaughter 1998; Slaughter and Rhoades 1990. Simon Marginson (1997) is a good source for Australia. 36 secrecy or property rights, knowledge remains under-explored or under-exploited. Thus state support for basic research can be justified o n the grounds o f economic efficiency (Nelson 1959). Y e t as N e l s o n (1998) and N e l s o n & Sampat (2001) have recendy shown, universities are now patenting and licensing a 'non-trivial fraction' o f what wou ld previously have been placed in the public domain. W h e n a university owns patents and licenses, transaction costs for industrial development are increased because companies must n o w pay for techniques and materials that were previously freely available. Industry's costs also increase when university researchers spin-off patented discoveries into their o w n companies, then license subsequent products to larger firms.24 Thus , again referring back to Starr, transaction costs reduce accessibility. Industry prefers, therefore, to maintain university research i n the public domain. N e l s o n (1998:2) remarks that 'the large pharmaceutical companies, i n particular, have begun to complain vociferously that since they and the public pay for this research through taxes given to the university, it is not fair for them to pay again for access'. A s wel l , patents are said to restrict the diffusion o f knowledge that promotes innovation. Traditional.methods o f knowledge diffusion from universities to industry—journal articles, meetings, conferences, and so on—are held to be more efficient (Cohen, et al. 1996). Since barriers to access decrease overall wealth, arguably it is more efficient for government to subsidize the product ion o f fundamental knowledge and give it away 'for free' (Nelson and Romer 1998:59). Flor ida & C o h e n (1999:590) argue that although the role o f the university i n the knowledge economy is 'not yet clearly articulated, identified, or understood', inherent tensions beset their dual pursuit o f both commercial alliances and the traditional 'quest for eminence'. A more balanced view o f the university's new role i n the economy is required, they say. Instead o f posi t ioning universities For an extended discussion on the economic costs and benefits of patents see Mazzoleni & Nelson (1998) 37 as engines o f economic growth, a more nuanced perspective w o u l d reframe the university as 'an enabling infrastructure for technological and economic development' . 2 5 In this vein , a recent empirical study o f university patenting i n the U K (Rappert and Webster 1997) 2 6 concludes that the construction o f a 'regime o f appropriation' i n the academy, while effective in the short term, may i n the med ium to long term constrain the overall rate o f return. The authors argue that university patenting and intellectual property rights can unintentionally compromise the commercial potential o f research, and that i n securing patents the university positions itself as a potential competitor to private-sector firms. Further, university patents may present an obstacle to future development i f the patent coverage has been poorly framed or filed prematurely. Starr's dimension o f open/c losed appears i n disclosure restrictions associated wi th the securing o f intellectual property rights; these may prevent research results f rom entering the public domain in a timely fashion. Universi ty commercialization activities can be perceived as impeding the cumulative advance o f the research enterprise by increasing wasteful duplication o f effort, and reducing the l ikel ihood that current findings w i l l contribute to future work (Nelson and R o m e r 1998). Disclosure restrictions are by far the most significant economic cost associated wi th university patenting and licensing (Cohen, et al. 1998; Blumenthal , et al. 1996). Restrictions i n licenses are pervasive. A recent U S study (Blumenthal 1997) found that 82% o f companies surveyed require academic researchers to keep information confidential to allow for the filing o f a patent application, while some 4 7 % have agreements wi th universities that al low for even longer delays. Addi t ional ly , 30% reported that conflicts o f interest had arisen wi th universities, and 34% had experienced intellectual property disputes wi th academic researchers. The study confirmed that participation by researchers in commercialization is associated wi th both delays i n publication and refusal to share research results 2 5 As will be seen later, CGDN has recently redefined its mission in precisely these terms. 2 6 see also Packer & Webster 1996,1995; Webster & Packer 1996a, 1996b, 1995 38 on request. Industry-supported and market-oriented academic researchers were more than three times as likely to delay publication as those w h o had no industry support. Similarly, i n a survey o f technology managers and faculty at the 'top 100' R & D - p e r f o r m i n g universities i n the U S (Rahm 1994), 39% o f managers had experienced situations where firms placed restrictions o n the sharing o f information between faculty. A l s o , 7 9 % o f managers and 5 3 % o f faculty reported that firms had asked for R & D results to be delayed or kept f rom publication. In addition to restricting the flow o f knowledge, disclosure limitations also generate real and potential conflicts o f interest that can damage public perception o f the research enterprise. Ano the r issue receiving attention i n the literature is the so-called 'patent-scope' problem. This refers to the practice o f taking 'broad patents' o n basic biomedical systems technologies, such as recombinant D N A or monoclona l antibodies. Especially problematic are rights claimed to 'whatever useful may come' f rom the patenting o f D N A fragments. Critics (Nelson 1996; N e l s o n and Romer 1998) argue that the use o f broad patents to commercialize 'publ ic ' scientific research, and the policies promot ing that commercialization are unsupportable. Especially i n the biomedical sciences, when discoveries are converted into proprietary products the amount o f prior public investment required to br ing them to fruition is not taken into account. Biotechnologies bui ld o n years o f publicly-funded research i n 'pure' molecular biology; they continue to draw o n advances i n 'public ' science. A s N e l s o n says, modern biotechnology is a canonical example o f a field where science and technology, public and private are inextricably mixed (1996:141) A l l o w i n g those w h o placed the last brick o n the w a l l — i n patent terminology, the first to 'bring to practice'—to privatize the whole system seems not only unfair, but unjustifiable. In more general terms, broad 'pioneer' patents appear to act as a disincentive to further development because o f the l ikel ihood o f patent infringement, and the legal costs o f defending such 39 mfringement. The effect is analogous to an 'act o f enclosure' over a wide area o f the intellectual landscape. N e l s o n argues strongly that patent scope should be kept as tight as possible. T o the response that broad patents are necessary to encourage inventors to innovate, N e l s o n points to technologies that have been developed without such protection; for example, semiconductors, transistors, and integrated circuits. H e states unequivocally: We believe that the granting and enforcing of broad pioneer patents is a dangerous social policy. It can, and has, hurt in a number of ways.. .And there are many cases in which technical advance has been very rapid under a regime where intellectual property rights were weak or not stringently enforced. We think the latter regime is the better social bet (Nelson 1996:137). In that it underutili%es scarce resources, the situation has been described as an 'ant icommons' (Heller and Eisenberg 1998). ProUferating patents and licenses 'upstream' b lock each other, and impede researchers 'downstream'. Rather than stimulating innovat ion and diffusion, therefore, a tangle o f fragmented and overlapping patent claims impedes the advance o f knowledge. Researchers must obtain licenses and pay royalties to all w h o ho ld interests i n the 'upstream' basic technologies (Nelson 1996). A s a result, and paradoxically, an increase i n intellectual properly rights can lead to a decrease i n useful products. In a 1998 report, the House Committee o n Science i n the Uni ted States' Congress acknowledged the 'chi l l ing ' effect o f university patenting, staring that 'a review o f intellectual property issues may be necessary to ensure that an acceptable balance is struck between stimmating the development o f scientific research into marketable technologies and mamtaining effective dissemination o f research results'. Rosenberg (1998) emphasizes the continuing economic importance o f sustaining basic research, rather than directing i t into specific and narrow commercia l applications. H e shows that the majority o f R & D funding (80%) is spent o n already-existing products; i.e. o n improvement, not innovation. H e cites telephones, transistors, lasers, and computers as examples o f the essentially unpredictable 40 nature o f the technological outcomes o f basic research investments. Similarly, N e l s o n & Romer (1998) point out that basic academic research produces a multitude o f new, publicly available ideas that everyone can share, thereby stimulating innovation. The enforcement o f university intellectual property policies, they argue, chokes o f f this important source o f innovat ion. They fear that 'instead o f offering new and different opportunities for the Pasteurs o f the university, pol icy makers may try to convert bo th the Bohrs and Pasteurs into Edisons ' (1998:45). Modern-day Pasteurs must continue to find a place i n the university, they say, i f progress is to continue. ' I f badly designed policies interfere wi th this interaction, they can do great harm'. In summary, the conditions o f knowledge product ion are such that the details o f institutional and organizational differences between the public and private sectors 'really do matter' i n the open science model . Paul D a v i d argues that the integrity o f science and the scientific method depends on 'mamtaining an ethos o f openness and cooperation among researchers, supported by the presupposition that the reliability o f scientific statements is a collective product requiring independent verification, and consequendy conformity wi th some behavioural norms regarding the disclosure o f their findings' (1995: 13). A s noted earlier, these institutionalist economic arguments mirror those o f social critics o f university commercial izat ion, indicating a developing consensus wh ich may be significant for future policy. B u t for another influential mode l , demarcations such as publ ic /pr ivate and basic/applied are basically meaningless and intellectual property is just one o f the many 'intermediaries' i n a knowledge product ion system constituted by flows, circulations, and network linkages. The Overflow Model 41 The opposing view to the open science model, (lacking an umbrella term; I will call it the overflow or network model) argues that changes to the knowledge production system over the last two decades are radical and irreversible, and constitute a productive force for the good. Callon (in press:3) states that the open science model defends 'Cold War institutions' that have now 'had their day'; they constitute obstacles to science's ability to contribute to economic development. Especially in the biosciences and information and communication technologies (ICTs), tight coupling and multiple linkages between state policy, university research and industry receptors, is the new norm. Pubuc/private and basic/applied distinctions are beside the point here; what matters is the extent of the connections. The model is process-based; its intellectual antecedents can be traced from Heraclitus through Alfred North Whitehead. What this model attempts to describe may be closer to the historical reality than the open science model, the 'purity' of which can be seen as an artefact of post-war affluence. As suggested earlier, there was a long tradition of cross-sectoral linkages in the interwar years and before. However, the shift in degree of cross-sectoral interactions today is a marked departure from earlier times. Michel Callon" supports the argument that the state should invest in basic research, and he is concerned about the increasingly problematic confrontation between the logic of disclosure and free circulation of ideas and the logic of proprietary knowledge and secrecy. However, he rejects the economic foundations of the open science model.28 Stories that invoke marketfailure to define science as a public good are wrong. 'The thesis of underinvestment in research [by the market] is becoming more and more difficult to support,' he says; 'public laboratories are one after another falling into private hands, either direcdy through takeovers and cooperative arrangements or 2 7 See for example Callon 1994, 1997,1998a, 1998b, in press 42 indirectly through incentives and research programs' (1994:401). Rather than defining the private domain i n terms o f withdrawals from the public domain, as Starr does, Ca l lon inverts the question by point ing out that a lot o f effort is required to make scientific knowledge public, whereas almost no work is required to keep it private." T o Ca l lon , science has always been 'potentially privatizable'; to maintain i t i n the public domain requires intensive investments o f energy by scientists and the state, and institutions like universities. In Callon's formulation, wh ich is anchored i n actor-network theory, no a pr ior i distinction separates public and private. Instead we have heterogeneous networks—hybrid collectives—some local , some extended, i n wh ich science is constructed and circulates. The more networks there are, the more scientific innovat ion flourishes. 'Science is a public good when it can make a new set o f entities proliferate and reconfigure the existing states o f the wor ld . Private science is the science that firms up these worlds, makes them habitable. This is why public and private science are complementary: despite being distinct: each draws o n the other' (1994:416). L o c a l networks are private i n the sense o f 'mtimate', i n that the space o f circulation is l imited. W h e n network science overflows the local frame, the space o f circulation opens up. A t the same time, however, the magnitude o f investments required is enormous and tends to generate long and complex chains o f associations. A s the network settles into place so the links and relations become standardized and 'heavy wi th norms'. This tends to produce what Ca l lon calls 'irreversibility' and economists o f an evolutionary persuasion call path-dependence and technological lock- in . In other words, the network becomes self-perpetuating and the space for the circulation o f new ideas shrinks It is at this point that intervention is needed and the hard work o f keeping science public must take place. Strong, stabilized networks should receive no additional public support, says Cal lon . Instead, 2 8 The economic details of the arguments are beyond the scope of this paper, but are fully articulated in Dasgupta and David 1994; also David 1998a, 1998b, 2000, on the one hand, and Callon 1994,1998a, 1998b, and in press on the other. 43 support should go to encouraging the emergence and proliferation o f new networks. It is the variety o f academic research that thwarts the tendency to lock- in . Established networks should be constrained by requirements to disclose the knowledge they produce and by l imit ing the duration o f patent protection. 3 0 B u t Ca l lon (in press) admits that accounting for the 'dual movement ' o f scientific exploration and commercial exploitation is a difficult question, i n that investments i n established and profitable developments have to be encouraged at the same time as new, currendy unprofitable, avenues o f enquiry. In other words, without the incentives o f 'open science', h o w do we ensure a continuing supply o f basic research? T o address this question, Ca l lon directs our attention to fields such as biotechnology and I C T s that i n his estimation successfully balance exploration and exploitation. These fields 'constitute veritable social laboratories i n which new arrangements, devices, and rules o f the game are tried and argued' (3). These areas rely as m u c h o n tacit (applied) as codified (basic) knowledge. 3 ' Ca l lon argues that rules o n pr ior disclosure make tacit knowledge easily appropriable as intellectual property while codified knowledge is not, because i n the latter case disclosure is difficult to contain. T h e main problem wi th the open science model , according to Ca l lon , is that 'it is not allowed to cross boundaries' (7). Whi l e good at describing existing institutions, it has 'nothing to say about the work that transforms scientific knowledge into commercial innovations ' (7). In other words, it addresses only codified knowledge and assumes the same conditions also apply to tacit. Further, it assumes we can draw clean lines between these two forms o f knowledge. In contrast, Ca l lon argues that biosciences and I C T s are 'emerging sciences' that are both autonomous and strongly connected to the market economy. 'Emerg ing sciences' seems to occupy a mid-point o n the cont inuum between taci t /embodied and codified/consolidated. In other words, 2 9 For additional discussion on this point, see Cambrosio and Keating (1998) 3 0 See Cambrosio & Keating & Keating (1998) for discussion of the way monoclonal antibodies moved from local to extended networks 44 they belong i n Pasteur's Quadrant. Subsequent 'translations' align emergent networks and move them towards consolidation. The reverse is also the case. Consolidated networks can unravel and cede to emergent. Whi le more extensively theorized, Callon's mode l bears a close 'family resemblance' to two descriptive formulations that have been circulating i n the science pol icy/science studies literatures since the early 1990s, when government cutbacks i n research funding and enhanced expectations o f commercial exploitation began to fundamentally rewrite the conduct o f academic science. M O D E 2 A N D T R I P L E H E L D C 'Mode-2 ' 3 2 and 'Tr ip le -Hel ix ' 3 3 formulations emerged i n the early 1990s to describe the changing conditions o f knowledge production. The first argues that traditional ( 'Mode-1') ways o f producing knowledge are being replaced by new ('Mode-2') configurations. M o d e 2 knowledge is produced in contexts o f application by new, ttansdisciplinary networks that operate along the periphery o f the academy and extend beyond it. They combine heterogeneous skills and different types o f expertise i n flat rather than hierarchical forms, that shift and recombine as the problem-focus changes. Rather than being accountable to the communi ty o f science, they are accountable to the communi ty at large. Quali ty control extends beyond traditional peer review structures to include the broader set o f practitioners that populates these networks. Mode-1 may be considered analogous to 'Bohr 's Quadrant'. T h e focus o n 'useful' knowledge and the context o f application in M o d e 2 clearly suggests 'Edison 's Quadrant' . In this typology, there seems to be no r o o m for a ' M o d e 3' or 'Pasteur's Quadrant ' . 3 1 Collins (1982) provides a classic SSK analysis of tacit knowledge and scientific networks 3 2 See Gibbons, et al. (1994) and Nowotny, et al. (2001) for the full exposition, and (Jacob 2000) for an excellent summary 3 3 For the model's attributes see, for example, Etzkowitz, et al. (1998) 45 In a complementary fashion, the 'triple-helix' mode l posits the recursive interaction o f academy, industry, and state institutions i n pursuit o f knowledge-based economic development and innovation. Triple-helix proponents argue that these institutional alliances signal a new 'democratic corporatist' form that creates a new 'quasi-public sphere.. . in between representative government and private interests (Etzkowitz 1997a: 149-150). Th is new arena legitimates the state's involvement i n an area that might otherwise be left to the 'invisible hand' o f the market. Bu t Saul (1995) sees little difference between the new corporatism and the goals o f o ld , fascist-era corporatism. These were 'to shift power direcdy to economic and social interest groups; push entrepreneurial initiative i n areas normally reserved for public bodies; and obliterate the boundaries between public and private interest—that is, challenge the idea o f the public interest. This sounds like the official program o f most contemporary western governments' (87-8). Integral to the triple-helix vis ion is an image o f a new type o f university—the entrepreneurial university (Etzkowitz , et al. 1998). In contrast to the 'passive' linear model , where knowledge was handed over to industry for exploitation, the entrepreneurial university capitalizes its o w n knowledge, thereby changing the dialectic between the university and society. The primary vehicles o f change are public/private linkages and collaborations, and dedicated structures to capture, capitalize, and exploit intellectual property (Etzkowitz & Leydesdorff 1997; E tzkowi t z , et al. 1998). Triple-helix proponents firmly locate these collaborations wi th in the productive sector o f the economy (Etzkowitz and Leydesdorff 1997). A g a i n then, the empasis falls o n 'Edison 's Quadrant ' . Fuller (2000) warns against uncritical acceptance o f the perceived dichotomy between new and traditional forms o f knowledge organization, calling it 'the myth o f the modes ' (page xiii). Far from being new, says Fuller, the 'institutional dawn' o f Mode-2 and triple-helix models can be found in 19 t h century Germany's large-scale academy/industry/state collaborations in physics and chemistry. Posit ing radical breaks and new eras obscures the basic continuity i n knowledge product ion and betrays a presentist understanding o f history. R i p (2000) presents the new models as rhetorical ploys ('fashionable ideas') that name features always-already present. They favour descriptions o f ' revolution' rather than 'evolution' , because they are normatively loaded towards entrepreneurial activities and publ ic /pr ivate partnerships. Nevertheless, a programmatic orientation towards the new formulations has been incorporated into the science policies o f most O E C D countries. 3 4 Policy Regimes In order to understand h o w these models are being operationalized, we need a broad framework that w i l l encompass the way our two cross-cutting dimensions (public/private; basic/applied) play out at the policy and program level. A r i e Rip 's concept o f 'policy regimes' fills that role. 3 5 R i p suggests that science policy regimes manage the mutually-dependent 'national research system': a landscape made up o f interactions between research performers, funders, users, markets, and state 'incentive structures'. Po l icy regimes ' lock- in ' to particular trajectories o f institutionalization. In the 1950s and 1960s the linear mode l o f innovat ion and the social contract for science dominated. In the 1970s and 1980s, a flurry o f activity marked 'big science'. Today, we have the 'strategic science' regime that was initiated during the high-tide o f neoliberalism i n the late 1980s. Neol ibera l ideology advocated a comprehensive withdrawal o f the state from the economy. Regardless o f poli t ical complexion, governments 'all abandoned Keynesian policies and. . .pursued fiscal restraint, tax rninimisation, deregulation, and marketization' (Marginson 1997:73). States began to divest themselves o f public utilities, nationalized industries, national airlines, and controll ing interests i n strategic industries. Truly 'public goods'—that is, those wi th costs but no profit 3 4 see Jacob & Hellstrom, 2000, for examples 47 potential—could safely be left wi th the state fTeeple 1995); everything else belonged i n private hands. A t the same time, states adjusted their redistributive functions. Here too, the logic o f the market prevailed. Citizens were to become self-regulating 'enterprises' and market themselves accordingly (Gordon 1991; Rose 1996). Translated into the public service, this reformist spirit became k n o w n as the 'enterprise' or 'entrepreneurial' model , more formally ' N e w Publ ic Management ' ( N P M ) . 3 6 This new culture took as axiomatic market-like principles o f cost-recovery, competitiveness, and entrepreneurship i n the provis ion o f public services (Power 1996). A t the same time, accounting , auditing, and accountability measures normalized the new principles and entrenched them i n the public service ethos. F r o m 1980 on , then, public funding o f academic science began to be contingent o n these same principles, wh ich continue to dominate policy mechanisms. 'Neol iberal science' is Strategic Science. Strategic Science qualifies as the signature policy regime o f neoliberalism across two dimensions: 'steering' (attempts by the state to impose an agenda) and 'aggregation' (institutionalized processes o f agenda-building). Thus Strategic Science has developed 'more or less stabilized rules o f how to proceed' towards the state's goals o f wealth creation and sustainability. A t the same time, an emergent new scientific establishment is 'promising to contribute to [those goals] and forging new alliances wi th policy makers and societal actors o n this basis' (Rip 2001:4 ; see also van der Meulen and R i p 1996:346-7). The Strategic Science regime typically combines concerns for relevance (applied research for the private sector) w i th demands for excellence (basic research to enrich the public knowledge base). 3 5 For the development of Rip's thinking over time, see Rip 1990,1997, 2000, 2001; van der Meulen & Rip 1996 3 6 See Hood 1991 and 1995 for a full accounting of NPM more generally; Savoie 1995 for its influence in Canada 48 These ideas were corning into the policy discourse at the time the Networks o f Centres o f Excellence program was conceptualized, i n the mid-1980s. R i p (2000) speaks o f 'fashions' i n ideas and the 'abstract sponsorship' ideas exercise. Ideas matter. Thei r power lies i n their performativity. They help to 'order the wor ld ' , shaping agendas and outcomes (Goldstein and Keohane 1994). Modes t ideas like relevance and excellence, and b ig ideas like N e w Publ ic Management, Systems o f Innovation, and the Knowledge-based E c o n o m y disseminate widely and become dominant. In describing this effect, I have used the term 'international ideas' (Atkinson-Grosjean 2002). In science policy, 'international ideas' are a combinat ion o f principled and causal beliefs 3 7 held by dominant international 'knowledge elites' about the economic importance o f scientific knowledge, and the best way to harness science to the economy. N e w ideas about science and the economy tend to circulate first i n epistemic communit ies 3 8 o f policy professionals i n international organizations like O E C D , the G 7 , and the W o r l d Bank. These expert communities then 'teach' the new ideas to member states,39 creating convergence around particular regimes or models. 4 0 These organizations also supply the formal and informal structures through wh ich policy frameworks are negotiated and ideas disseminated. I suggest that the broad outlines o f Strategic Science i n Canada emerged as part o f this general internationalizing movement. The material effects o f international ideas can be seen i n the reformulation o f funding priorities; new infrastructures for the exploitation o f intellectual property; and initiatives such as the Networks o f Centres o f Excellence program. 'Excel lence ' is one o f the defining tropes o f Strategic Science. It is not an innocent term. See Goldstein and Keohane (1994) for a full explanation of worldviews and principled and causal beliefs 3 8 In a later chapter I will be describing epistemic communities of scientists, but the term was first used in relation to the international policy community. See, for example, (Ruggie 1975; Haas 1992) 3 9 Martha Finnemore's work is important here, see 1992 and 1993 4 0 A dialectic is at work in that many of the policy professionals are seconded from member states. According to an informed observes, one finds a mutual shaping of policy, between and among the member countries, the Permanent Secretariat, and the expert communities 49 In its fixed sense, excellence simply means 'high quality'; this is unobjectionable. B u t i n its relative sense excellence means 'superior' or 'better than the norm' . Used i n this manner, performers o f 'excellent' research stand i n contrast to a m u c h broader populat ion o f average or marginal 4 ' performers. In their critical review o f the career o f 'excellence' i n U K science policy, Gallart & Salter (2001) point out that 'by its very nature excellence can only be achieved by a very l imited number o f researchers or research groups' (5). These authors fear a 'Matthew Effect ' (Merton 1968) that wi l l direct funding exclusively to researchers and research organisations wi th established records o f excellence. N o t only w o u l d this restrict diversity and capacity i n the research system, it w o u l d cut o f f the important contribution o f 'average' science i n areas such as trairiing the next generation o f researchers, opening up new fields o f inquiry, and offering a wider field o f social choices about wh ich new technologies get developed (Gallert & Salter 2001: 8). M i c h e l Ca l lon has argued 4 2 that concenttating research funding o n established scientists and institutions leads to less innovat ion than spreading funds across multiple sites. N e l s o n & Winter (1982) and R i p (1997) reinforce that variety i n the system ensures possibilities for new entrants, who often sit o n the margins o f traditional disciplines. Similar concerns about exclusion and loss o f diversity were expressed when Vannevar B u s h was developing 'the doctrine o f basic science'. A s Bernard C o h e n recalls, 4 3 there was a fear that setting up a Nat iona l Science Foundat ion wou ld institutionalize 'the monol i thic pressures o f scientific or thodoxy' and support 'only research o f a recognized k ind i n established fields'. In m y later analysis o f C G D N discourse, excellence w i l l emerge as a dominant trope i n the guise o f a performative elitism, wi th themes o f inclusion and exclusion. Actor-network theory ( A N T ) , 'the 4 1 Gallart & Salter (2001) use the term 'mediocre' but do so polemically, to enhance the contrast 4 2 See the upcoming chapter in Science Bought and Sold. Mirowski & Sent (eds) as well as Callon (1994) 4 3 See (Stokes 1995); Cohen was responding to Stokes's presentation and responses are appended to the document. Cohen was disussing the Bowman Report, the foundation document for Bush's (1945) landmark: Science: The Endless Frontier 50 sociology o f translation', provides a way o f understanding these results. A N T helps me describe the way scientists and others i n the Canadian Genetic Diseases N e t w o r k continuously negotiate competing demands for excellence and relevance from the N C E program, while continuously inventing (translating) their network. III. Translating Networks The sociology o f translation describes the politics o f scientific organization and practices using a vocabulary o f power, force, strategy, and negotiation (Pels 1997). A s w i l l be seen, these idioms are especially useful for analyzing the practical arrangements and power relations at work i n the Canadian Genetic Diseases Network . In A N T ' s precursor study, Laboratory L i fe . Latour and Woolgar (1979) crafted 'a poli t ical economy o f truth' by weaving together the economics and politics o f science. The i r 'integrated economic mode l o f the product ion o f facts' explained scientific credibility i n terms o f the accumulation and maintenance o f symbolic capital. A t the same time, however, they portrayed poli t ical competence as central to scientific work, seeing little practical difference between 'polit ics ' and 'truth' (Latour and Woolgar 1979:213, 237; Pels 1997:10). The emphasis o n power was made more explicit i n the work o f M i c h e l Ca l lon , who coined the term actor-network and defined it as a theory o f translation. Using the analogy o f a 'seamless web' , A N T attempts to understand the materiality o f the social and technical relations permeating heterogeneous materials. In A N T , distinguishing between 'facts' and 'artifacts' is neither useful nor relevant: all are actors i n the network and all are treated symmetrically. Since materiality is a relational effect, it is provisional and susceptible to change. Boundaries are fluid not fixed; the emphasis is o n connection, interdependence, mutuality, and flux (Bingham 1996). It is important, therefore, to stabilize actors and actants i n order to maintain the tenuous stability o f the 51 network, wh ich can quickly dissociate without constant attention. Stabilized facts, practices, and artifacts—those under temporary control—are 'black-boxed. ' F o r the moment at least, they are no longer questioned or considered controversial. Power and agency are relational effects o f networks 'acting at a distance' by 'remote control . ' The achievement o f action at a distance is exemplified by the concept o f centres of calculation (Latour 1987) or centres of translation (Callon 1986), where the ability to control actors at the periphery translates into power at the centre. These key A N T ideas have found their way into post-Foucauldian theories o f governmentality, illustrating not only A N T ' s conceptual fertility but also its location between dual 'repertoires o f disenchantment': Nietzsche and Foucault o n the one hand, and Marx and Bourdieu o n the other (Pels 1997). Power f lowing through networks accumulates i n the hands o f actors who are able to enrol the most allies, translate their interests, and act as their spokesman (Callon 1986; Ca l lon & Latour 1981). Power and agency lie i n this ability to intervene between forces and stabilize power relations. The most powerful actors—those who assume a network's leadership and become its spokesperson—are those w h o enrol the largest number o f irreversibly l inked allies (Pels 1997:11). Rather than being delegated by pre-existing groups to speak o n their behalf, spokespersons actually create the groups they speak for, by the very act o f assuming the role o f spokesperson (Cambrosio, et al. 1990:214). F o r example, Latour (1988) shows that Louis Pasteur 'the scientist', w h o made fundamental discoveries i n microbiology and public health, is inseparable from Lou i s Pasteur 'the polit ician' , who skillfully translated and mobi l ized legions o f microbes, farmers, laboratories, and other allies to create new sources o f social power and legitimacy. Pasteur became 'Pasteur', the authorized spokesman and exclusive interpreter for the heterogeneous multitudes he enrolled. F o r Latour, a sociology that concerned itself only wi th 'social facts' and 'social relations' w o u l d miss the most 52 interesting features o f science as a poli t ical practice. The sociology o f science needed to be redefined as the science o f strong or weak associations (Latour 1988:40, see also 1986). A s A N T developed, the linkages between science and politics became firmly embedded, and the concept o f networks so extensive, that everything was explained i n network terms. All social relations, including power and organization, were treated as network effects (Law: 1992:379). In a seminal paper, Lee and B r o w n (1994) argued that A N T 'plays god ' when it claims the ability to k n o w the whole wor ld through networks. They ascribed a 'Nietzschean wor ld-view' to A N T : one which 'simultaneously secures the universal applicability o f its poli t ical metaphorics, and stretches the not ion o f relational power . . .to cover everything' (778). In claiming the right to speak for all, said Lee & B r o w n , A N T risks becoming 'yet another ahistorical grand narrative'. It was this paper that began the reflexive self-questioriing that spawned a 1997 workshop on what 'comes after' A N T 4 4 as we l l as a subsequent book o f the same name (Law and Hassard 1999), and a whole new literature to w h i c h Cal lon 's analysis o f 'overflowing' networks belongs. Despite the 'imperialist' tendencies Lee & B r o w n warn against, it is precisely A N T ' s ' totalizing tendency'—its ability to fully account for the workings o f power i n network relations—that makes it such an appropriate analytical too l for m y case study o f the Canadian Genetic Diseases Network . However , like micro-studies o f science i n general, A N T is less than helpful when it comes to accounting for the structural relations between C G D N wi th the N C E program. Actor-Network Theory and After, Keele University, 1997 53 Structural Issues Relational approaches to the study o f science ask 'how' questions about the micro-level o f knowledge product ion (Knorr-Cet ina & Mulkay 1983:6). The focus is o n detailed, ethnographic description o f local practices, or close historical study o f specific episodes. The key is simply to ' fol low the actors' (Latour 1987) at the actual site o f their scientific work. Explanat ion emerges once description has been saturated, or pursued 'to the bitter end' (Murdoch 1995:731). W i t h such a strong focus o n the local , surrounding institutions tend to become epiphenomenal 'scale effects' o f relational networks. The entire research system can be viewed as a contingent outcome o f the 'powers o f association' attached to networks. Causal accounts are abandoned. Social and normative 'why' questions disappear i n the minutiae o f mundane 'how' questions (Shapin 1995b). Poli t ical-economic issues vanish into the local politics o f research. 4 5 L i k e Winner (1993), K l e i n m a n (1991; 1998), Fuller (1992), and others I find this not only unsatisfactory, but also methodologically unsound. T o me, the micro-focus neglects important already-existing structural and institutional features that constrain individual and collective actors. O n e o f the goals o f this study is to encourage A N T towards something it has long sought to avoid: full engagement i n the agency/structure debate and a more satisfactory accounting o f formal institutions. A N T tends to fall into infinite regress when attempting to account for structural features. Kea t ing & Cambrosio frame the problem as follows: Critics of the changing milieu of academic knowledge production view phenomena such as patenting and public/private research partnerships as evidence of the intrusion of global capital and market ideologies into academic institutions. But in practice-based approaches, as Knorr-Cetina (1995) admits, these wider concerns disappear. 54 the fact that traditional sociological dichotomies (macro and micro, social and technical, nature and culture) are inappropriate tools for describing and analyzing scientific and medical practices .. .has been a leitmotif of many recent contributions to the science studies field. Yet, once the ritual rhetorical ceremony of excommunicating the usual dichotomies has been performed, the question remains of [what] analytical frame...will allow us to move appropriate account of, say, the development of biomedicine in the last half-century (2000:385) I mink we can meaningfully speak o f 'structure'—and study its effects o n the way science is organized and done—without reifying it. O n e way is to use the gerund form: 'structuring'. Ano the r is Giddens ' not ion o f structuration. 4 6 L a w (1992) has proposed 'punctualization' to denote networks that ' run wide and deep—the seemingly macrosocial—[that] can be more-or-less, most o f the time, taken for granted (Law 1992:385). Accep t ing that 'divide talk' is ultimately meaningless, and that continuity overrides all these distinctions, perhaps this is a good enough place to begin the structural (policy/program) level o f my study. B u t i n order to undertake the micro-level study o f the Canadian Genetic Diseases Ne twork , I first had to overcome another methodological p roblem associated wi th science studies. 'Studying up' A s Shapin points out, science studies is 'one o f the few sociological specialities.. .that aims to interpret a culture far more powerful and prestigious than itself. . . [and]... few students come equipped wi th relevant competencies i n the natural sciences' (1995b:293). H e calls this the problem o f 'studying up' . 4 7 B y proposing to enter the social wor ld o f medical geneticists, without being an initiate, I had to deal w i th the issue o f whether or not I could , or should, acquire linguistic competence i n the field. 4 6 There are so many other differences between ANT and Giddens' theorizing that this does not seem practical, but the term itself is still suggestive 4 7 For another perspective on 'studying up' see Bronwyn Parry's (1998) interesting account of her attempt to study 'elite networks' of senior executives in big pharma and biotechnology 55 Latour & Woolgar (1979:27-8) called Laboratory Li fe , their pioneering study o f scienusts-in-action, an 'anthropology' o f science. The study was an ethnographic investigation, grounded i n participant observation, o f one specific group o f scientists i n one specific setting. U s i n g anthropological means, they hoped to penetrate the 'closed-shop' status o f science, and open up scientific claims, by breaking d o w n the mystique o f scientific objectivity. In order to understand the tribes they study, anthropologists usually attempt to acquire linguistic and cultural competence by immersing themselves i n the field. In contrast, Latour & Woolgar made it a methodological principle to maintain their 'anthropological strangeness' i n regard to their subject matter Al though conducting a field-based study, they made a point o f mamtaining critical distance. They decided an understanding o f science was not a necessary prerequisite for understanding scientists' work. O n the contrary, 'the dangers o f going native outweigh[ed] the possible advantages o f ease o f access and rapid establishment o f rapport wi th participants' (29). Thus Latour & Woolgar 's stories o f 'laboratory life' were accounts based o n 'the experiences o f an observer wi th some anthropological ttaining, but largely ignorant o f science' (30). In the land o f science, they chose to be 'the stranger' (Simmel 1950), a mixture o f presence and absence, proximity and distance (Shields 1992). Bu t to what extent can strangers, ignorant o f the 'native language', expect to penetrate the meaning o f activities they observe and document? Certainly strangers may be able to observe without bias but, o n the other hand, they may utterly misinterpret what they observe. Al leged misinterpretations by science studies researchers have provided ammunit ion i n the 'Science Wars ' . 4 8 Physicist A l a n Sokal argues that our case studies are often contaminated by 'extremes o f subjectivism, relativism and social constructivism'. 4 ' E v e n science-studies scholar Steve Fuller admits that science studies 4 8 This debate is well beyond the parameters of my study. For more information see, for example, Koertge 1998 ; Segerstrale 2000 and others 4 9 The comment derives from my interview with Sokal for Atkinson-Grosjean, 1997:11-12 56 practitioners often appear to be 'carping from the sidelines' (ibid.) and argues that researchers should acquire at least a basic level of scientific literacy. The solution, according to Harry Collins (2000), who has 'studied up' for decades, is to differentiate the types of competence required. Science studies researchers do not need 'procedural expertise', ability to do the science, but they must develop 'interactional expertise', ability to talk knowledgeably to experts in the field. I set out to gain interactional expertise by immersing myself in readings about medical genetics, and molecular biology, both prior to and during the study. I relied mainly on journals like 'Science', 'Nature', and 'Nature Genetics'. While I found the 'empiricist repertoire' of the scientific sections of these journals almost impossible to penetrate, the 'news' and 'features' sections were couched in an informal 'contingent repertoire' and proved much more accessible.501 also tracked developments in the field by subscribing to electronic lists like Medscape's Molecular Medicine MedPulse and Science Week, as well as activist monitors like Genetic Crossroads and Loka Alert. As with any language, however, I found the best way to learn was to hear it spoken. I gained most of the interactional expertise I needed to complete the study by interviewing informants, participating in informal conversations, and paying close attention to the papers and posters at C G D N and H U G O scientific meetings. IV. Summary This study rests on the tension between two cross-cutting dimensions: public/private and basic/applied; it pays particular attention to the separating ' / ' . This ' / ' represents the overlapping interstitial spaces in which the 'open science' model and the 'overflow model' offer their competing See Gilbert and Mulkay, 1984, for a discourse analytic approach to science studies 57 explanations. T h e 'open science' mode l was the dominant policy regime o f the postwar years. It enacted a social contract for science and a linear system o f innovat ion that justified unfettered government funding for basic science. The 'overflow mode l ' captures the Zeitgeist o f 'neoliberal science'. Examples include 'Mode-2' and 'triple-helix' formulations. In the Strategic Science policy regime, governments are more interested i n funding research wi th direct application than i n funding basic science. They deploy a dual rhetoric o f research excellence and commercial relevance. Funding is contingent o n cross-sectoral partnerships, market applications, and the formation o f research networks. T h e sociology o f translation—actor-network theory—offers ways to understand the complex interactions that take place i n the network forms o f scientific organization that emerge under this regime. 58 C H A P T E R 3 . S C I E N C E P O L I C Y I N C A N A D A A N D T H E N C E E X P E R I M E N T A review of Canadian science over the past century confirms the hypothesized fundamental continuity and absence of radical breaks. Continuity can be seen in longstanding R&D relationships between public- and private-sectors and in the federal government's historical commitment to the commercial relevance of publicly funded science. The broad periodizations and policy regimes discussed in the previous chapter, and the onset of Strategic Science, can be clearly discerned in the Canadian case. In the field of policy studies, analysts account for three mutually interacting influences that shape and constrain the business of policy formation. Powerful ideas, powerful institutions, and powerful interests act as gatekeepers to the process of agenda-setting. These three 'structuring' influences can be seen at work in the historical development of Canadian science policy and public science institutions described in the first half of this chapter. The second half of the chapter focuses on the formulation and implementation of the Networks of Centres of Excellence program as an instrument of Strategic Science policy. 59 I. Historical Influences on Policy Histor ian D o n a l d Phi l l ipson 5 1 suggests the Canadian state has had an abiding interest i n the economic relevance o f science and i n promot ing public- and private-sector interactions. H e suggests three principal reasons why this might be the case. First, consistent wi th interest-based explanations, unti l quite recently 'everybody knew everyone else and everybody that mattered' at the senior levels o f industrial, academic, and government science. F o r a century up to the 1960s, science i n Canada was very m u c h the enterprise o f a small elite group o f men from similar socioeconomic backgrounds 5 2 who held interlocking positions o f power. 5 3 Thei r networks o f influence went 'up' to the politicians, ' down ' to the top Canadian talent in their o w n fields, and 'sideways' to senior scientists i n other fields. Th is is illustrated i n C.J . Mackenzie 's response to a journalist o n whether it was difficult to get government approval when the Nat iona l Research C o u n c i l established a nuclear research unit during the Second W o r l d War . Mackenzie , then President o f N R C , replied, It was surprisingly easy. In those days the N R C reported to C D . Howe [then Minister of Department of Trade and Commerce].... C D . was a particular friend of mine.... We all went to CD.'s office and discussed the idea with him. I remember he sat there and listened to the whole thing, then he turned to me and said: 'What do you think?' I told him I thought it was a sound idea, then he nodded a couple of times and said: 'Okay, let's go.' (B. Lee, The Atom Secrets,' Globe Magazine, October 28, 1961; cited in Porter, 1965:432) F o r most o f the country's history, pol icy making was personalist (Phil l ipson 2000). It operated on social capital rather than academic or scientific capital. Decis ions were made o n the basis o f w h o m one knew. So the story o f Canadian science policy is i n large part the story o f the people who made 5 1 The historical background presented in this chapter relies heavily on (Phillipson 1983) and (Phillipson 1991), but more especially on our personal correspondence. By virtue of his oral history projects in the 1970s and 1980s, Phillipson is an authority on the National Research Council and the evolution of Canadian science policy. He has communicated an enormous amount of background material to me in a series of letters over the period 1998-2001. His collegial willingness to share his scholarship has enriched my understanding and I acknowledge his contribution to this policy history, which in many cases draws direcdy on our correspondence. Parts of this chapter appeared in Atkinson-Grosjean, et al. 2001 and Atkinson-Gros jean 2002 (forthcoming) 5 2 Most were Canadian-born of British extraction, middle-class in origin and Protestant 5 3 See Porter 1965: 507-11. For the operation of the US 'power elite see Mills, 1956 60 it. The evolution o f policy attitudes towards the respective roles o f basic and applied science reflects the evolution i n elite ways o f tbinking o n the topic. A l though the influence o f elite interests has become more subtle i n recent years, it remains a major factor: 'This is Canada. W h e n these people speak others listen. ' 5 4 A second element identified by Phi l l ipson relates to institutions. Boundaries between public and private i n Canadian science are quite unstable and tend to evolve fairly quickly i n institutional terms. Phi l l ipson (1991, 2000) provides the example o f the Ontar io Research Foundat ion ( O R F ) . Founded by the province i n the Depression era as a r ival to the federal Na t iona l Research C o u n c i l , O R F was transformed into a successful autonomous public industrial laboratory, a C r o w n agency, i n the 1950s. Later, it was 'privatized' as a state-owned corporation. Subsequently, the shares were bought by a commercia l company. Ano the r example is the Canadian Standards Associa t ion (CSA) . Founded i n the early 1920s as a government-funded advisory committee o f researchers and industrialists, it was incorporated as a company i n 1940, wi th the approval o f a government preoccupied wi th war research. C S A then moved its laboratories from Ottawa to Toronto . Here , it became a self- financing independent institution, and is still authorised to promulgate and enforce standards. A third element is 'ideas-based'. Awareness o f other national models—predominantly Amer ican and Brit ish—has always shaped what was implemented i n Canada, whether in the early 2 0 t h century or the early 21 s t . In comparison to other advanced nations, we tend to feel we lag scientifically and this has always influenced the projects undertaken. 'The country is dogged by a national inferiority complex ' (Phil l ipson 2000). A s described more extensively earlier, the influence o f policy 'fashions' f rom international forums like O E C D and G 7 can be clearly discerned i n the formation o f Canadian University administrator cited in ReSearch Money editorial; Henderson (2001). 61 policy. Canada's Na t iona l Research C o u n c i l , for example, founded 1916, was an example o f convergence wi th similar bodies in Bri tain and the U S A . Taken together, the interests o f powerful elites and the trade i n international ideas tend to promote convergence around generalized policy regimes. However , the historical particularities o f a nation's institutional and cultural legacies represent a countervailing force for divergence (Banting, et al. 1997). In other words, we put our o w n stamp o n what we adopt. The Networks o f Centres o f Excellence program is an example. Whi le the phrase 'centres o f excellence' was appearing wi th increasing regularity i n the international policy discourse at the time, networking centres o f excellence together was a specific solution to the peculiarities o f Canadian geography (sheer size and diversity) and 'soft federalism' (powerful provinces and the requirement to serve all regions equally). Canada's constitutional arrangements represent a longstanding constraint o n federal science policy. Universities fall under provincial jurisdiction putting them beyond direct federal reach. 5 5 Historically, federal control o f research funding emerged as one o f the few avenues for shaping the 'national' role o f universities within the 'knowledge-production system'. But until at least the 1960s, universities were not major players i n the research economy. The majority o f public science—historically defined in terms o f utility and industrial relevance— was conducted by the Na t iona l Research C o u n c i l ( N R C ) . Public Science in Canada F r o m inception i n 1916, N R C ' s 'public ' mission was to serve 'private' needs by directing its research towards 'the most practical and pressing problems indicated by industrial necessities.' T h e obligation 5 5 The federal government funds university operations through transfer payments to the provinces but it has no direct influence on these institutions and receives little credit for its funding role. 62 to serve industry was literally graven i n stone above the doors o f the laboratories o n Sussex D r i v e i n Ottawa. Publ ic science was defined not as the search for knowledge, but as the search for solutions. A s one o f its first tasks, the N R C set out to gauge the state o f industrial research i n Canada. Survey results showed that only 37 o f the 2,800 firms responding performed research o n an ongoing basis and most o f these employed only one researcher (Thisde, 1966: 29). There was litde for N R C to coordinate, therefore, and a clear national need to develop a critical mass o f researchers. This conclusion motivated the 1917 introduction o f N R C - f u n d e d post-graduate scholarships i n the sciences at selected universities (Thisde, 1966: 26,127). Shordy after, the idea o f constructing institutes for industrial research o n university campuses began to circulate. Bu t this heresy was briskly disposed o f when proponents discovered that university faculty were adamandy opposed to 'bargaining wi th manufacturers'. 5 6 Canadian universities modelled themselves o n the humanistic traditions o f Oxbr idge, where the focus was scholarship and teaching. T o undertake research was unusual; to undertake research for industry unthinkable. N R C ' s views were m u c h the same, arguing that universities w o u l d subvert their role by conducting industrial research. N R C itself became increasingly drawn to fundamental enquiry, i f only to retain its researchers. Between 1916 and 1940, N R C ' s workforce expanded from one employee to 2,000; its annual budget from $91,600 to almost $7 mi l l ion . 5 7 N R C ' s wartime expansion allowed Canada's academic scientists to work closely wi th Br i t i sh and Amer ican colleagues o n the front lines o f basic advances i n knowledge o f microwave techniques, jet engines, digital computers and nuclear power. They were intent o n continuing this momentum into the postwar era but conducting research wi th in Canadian universities was still a 'fringe' activity. F o r example, C D . Howe ' s Office o f Supply and 5 6 The inquirey was conducted by Hume Cronyn's parliamentary sub-committee struck in April 1919. The 'bargaining' quote is attributed to Professor Lash Miller, University of Toronto, Cronyn Committee Proceedings, June 4,1919, p. 99; cited in Lamontagne report, 1970: 31 63 Reconstruction began an annual inventory o f university research i n 1946 but abandoned the project in 1949. Scientists were 'faking the results, to conceal from university authorities h o w much they were diverting from teaching to spend o n research' (Phil l ipson correspondence). Universities were preoccupied wi th educating returning war veterans and other undergraduates. Research was not a priority. Bu t by then, the linear mode l o f innovat ion was beginning to circulate as an 'international idea'. In 1951 the Massey Commiss ion 5 8 articulated the model 's pipeline metaphor i n not ing the importance o f fundamental research i n pr iming the pump that eventually produces industrial products and applications. 'Wi thout fundamental research,' said the commissioners, 'there can be no proper teaching o f science, no scientific workers and no applied science' (175). In the commissioners ' view, basic research was most properly housed i n universities wh ich should be adequately funded to conduct it. T h e Commissioners strenuously opposed the idea that publ icly funded laboratories should undertake research for industry fearing that it wou ld deaden the scientific imagination and stall the advancement o f knowledge. applied research...cannot be expected to add in any way to the knowledge of scientific principles. Occasionally private donors offering research grants require that research projects be approved by them. University authorities generally agree with scientists that these gifts should be steadily refused. (Massey report, 1951:177) F r o m 1952 on , when D r . E . W . R . Steacie took the he lm o f N R C , support o f basic research i n universities became a key Canadian policy goal. 5 ' In line wi th the logic o f the linear model , funding university research was seen as the best way for N R C to achieve its long-term mandate to serve industry. A s Steacie said, 'it is absolutely impossible to have first-rate industrial research without 5 7 Lamontagne report, 1968-77, vol. 1: 61. 5 8 The Royal Commission on National Development in the Arts, Letters and Sciences, 1949-51 5 9 . Steacie left McGill University to become head of NRC's chemistry division in 1939. He was appointed NRC's vice-president in 1950 and president in 1952, holding the latter post until his death in 1962, at which time he was widely acknowledged the leader of Canadian science' (Babbit, 1965: 3). 64 first-rate university research' (1965: 159-160). A s i n the U S , the 1957 'Sputnik shock' had a salutary effect o n research funding, helping to cement the state's commitment to basic science. Federal expenditures devoted to R & D grew from an estimated $5 mi l l ion i n 1939 to over $200 mi l l ion i n 1959. 6 0 But the policy climate began to change i n the decade fol lowing the Massey Commiss ion ' s report. A speculative paper submitted i n 1957 by the [Gordon] Royal Commiss ion o n Canada's E c o n o m i c Prospects envisioned the roles that science might assume i n the distant future, setting the stage for more intense debate o n the status o f science i n national progress and economic development. In 1962, having examined the federally funded research system, the Glassco C o m m i s s i o n concluded that the system had failed. Glassco singled out the N R C for blame, argmng that its (vested) interests i n basic 'publ ic ' research had been promoted at the expense o f applied 'private' research. One of the original purposes of government in devoting money to research was to encourage and stimulate Canadian industry. From being a primary goal this has, over the years, been relegated to being little more than a minor distraction.... At present there is a wide-spread feeling that fundamental research is the only activity adequately recognized within the National Research Council. (Glassco report, 1963, vol. 4: 230, 271) In short, Glassco famously concluded that N R C had 'turned away' f rom industry. A c c o r d i n g to a funding distribution i n the late 1960s, 9 1 % o f the N R C budget was allocated to university research and its o w n laboratories (50% and 4 1 % respectively) while only 9% was allocated to industrial support and information services (5% and 4 % respectively) (Hayes, 1973: 38-39). Comment ing o n reactions f rom N R C ' s scientists and bureaucrats, O E C D noted that 'many, no doubt, recognised that there were grounds for the crit icism expressed by the Commiss ion , but the majority protested against its recommendations' ( O E C D , 1969: 63). Lamontagne report, 1968-77, vol. 1: 64 65 Following Glassco's recommendations, a Science Secretariat was established in 1964 and the Science Council of Canada began operations in 1966. Overall, however, the Glassco framework was fundamentally undermined by a report to Prime Minister Lester Pearson by CJ. Mackenzie, former NRC president, who advised against the substance of the findings. The personalist system protected its own. Nevertheless, the Glassco report established a policy climate more hospitable to the applied/private side of the matrix. A number of government initiatives intended to bring academic research closer to the needs of industry were designed in the 1960s.6' By the end of the decade, the Glassco Committee's main criticisms were echoed in several other policy documents mcluding the Science Council of Canada's 1968 report Towards a National Science Policy for Canada and an extensive survey of Canada's science and technology infrastructure by O E C D examiners (1969) .The O E C D and Science Council reports substantially contributed to the decade-long deliberations of the Senate's Special Committee on Science Policy chaired by economist Maurice Lamontagne, 1968-77. Lamontagne provided an exhaustive analysis of Canada's overall R&D system; the role and performance of federally funded science wherever it occurred; and the culture of science in Canada. At the core of the findings was an attack on the scientific elitism that had driven Canadian science policy since 1916 (Vol. 1: 268). Steacie's proud comment that Canada stands out among the nations by recognizing 'the fundamental fact that the control of a scientific organization must be in the hands of scientists' became an indictment (1965: 119, cited in Vol. 1: 269). Such freedom, the committee argued, 'cannot be justified as a general principle for the organization of scientific progress when the tremendous cost of research has to be met mainly by public funds and when the good and bad effects of science and technology on society are becoming so far-reaching' (Vol. 1: Among these, the Industrial Research Institute Program, established by the Department of Industry in 1966, provided grants to universities to establish institutes where they could work with industry and undertake contract research on their behalf. Legislative tools were also introduced; in 1967 government passed the Industrial Research and Development Incentives Act which was intended to foster academy-industry collaboration in research aimed at solving industrial problems. As well, in 1969 the NRC announced a grants program for universities that emphasized the promotion of industrial development through 'centres of excellence' aimed at fostering a regional balance of scientific and technological expertise. However, plans for this program were vague. 66 270-271). Steps needed to be taken to bridge the gap between science and industry and federal funding should affirm and reflect the priority o f applied research (vol. 2: 521). Lamontagne was enthusiastic about the whole business ofp/anification—econormc forecasting and planning—and its potential for fostering innovation. The latter w o r d entered the Canadian policy discourse about halfway through the 'Lamontagne decade'. Seduced by this emerging 'international idea,' the committee also embraced 'the new quasi-economic discipline o f science policy that went along wi th it ' (Phil l ipson correspondence). Committee members and staff were thus 'naively enthusiastic about both (a) the notional completability o f the Science Pol icy mode l . . .and (b) its polit ical appeal to actual politicians' (PhiUipson correspondence). In polit ics, extensive data is superfluous to the decision making process. Politicians do not wish to be confused by too many facts. A s Cohen , et al. (1972) classically demonstrated, they operate from a 'garbage can model o f rationality'. Consequendy, despite the years o f effort that went into it, the Lamontagne report, too, 'fell dead from the press', failing to find a place o n the agenda o f the Trudeau administration (Dufour & de la Mothe , 1993: 21, ft. 13). The power o f entrenched elites to resist unwanted change is formidable, but so is the power o f new elites to advance change, once the correct tools are in hand. M a n y remained convinced that the role o f public science was to foster industrial innovat ion and economic expansion and that N R C , wi th its focus o n the advancement o f knowledge, represented an impediment to that enterprise. A s a c rown corporation, however, N R C was beyond direct poli t ical and bureaucratic interference. The only way to control it was to systematically strip away its budgets and responsibilities and transfer them to another, more subordinate, agency. 6 2 In 1971, a Minis t ry o f State for Science and Technology ( M O S S T ) was created (as bo th Glassco and Lamontagne had recommended) replacing the existing Science Secretariat. In 1977, N R C ' s responsibility for supporting university research was devolved to 6 2 This is what eventually happened to the Science Council of Canada, disbanded 1992 along with other autonomous agencies 67 a new agency, the Natura l Sciences and Engineering Research C o u n c i l o f Canada ( N S E R C ) wh ich then fell under the administrative authority o f M O S S T . In 1978, M O S S T also assumed authority over the Social Sciences and Humanit ies Research C o u n c i l o f Canada ( S S H R C ) after the Canada C o u n c i l was reorganized. Th is restructuring gradually eroded the autonomy o f all granting councils. Science and technology pol icy edged gradually towards the top o f the poli t ical agenda. The first G 7 summit meeting, i n 1982, revealed the fact that Canada had the lowest R & D investment in the G 7 . 6 3 . A Scientific Research Tax Credit was introduced to stimulate investment. It was a flawed instrument, open to abuse, and required a number o f revisions to correct the deficiencies, but it marked a major policy innovation. A s a result o f the changes introduced then, Canada established—and still boasts-- the most generous R & D investment and tax climate i n the G 7 nations. The fol lowing year, as the Libera l Party came to the end o f its long postwar mandate, several reports established the need to tie government support o f public research to commercia l relevance. In 1984, wi th the election o f a Progressive Conservative government, the m o m e n t u m towards a national science pol icy accelerated, and the neoliberal agenda came into play. After a period o f intensive federal/provincial consultation, a national science and technology pol icy was formally signed i n M a r c h 1987. Details o f InnovAct ion : The Canadian Strategy for Science and Technology—a $1.5 bi l l ion 'package'—were announced the fol lowing month . M O S S T w o u l d subsumed into a new 'superministry'—Industry, Science, and Technology Canada ( ISTC)—a combinat ion that clearly signalled the alignment o f science and commerce. Legislation wou ld provide $240 mi l l ion for a new 'flagship' strategy: the Networks o f Centres o f Excellence ( N C E ) program. 68 II. Evolution of the NCE Program The N C E program is an example of the way international ideas, existing institutions, and socioeconomic interests interact under a policy regime of Strategic Science.64 The policy innovation was to bring ideological concerns for commercial relevance and research excellence together with the concept of distributed research networks to form networks of centres of excellence. Now that 'networks' are so associated with computer imagery, it is hard to remember it was not always the case. By way of policy studies and science studies, the network concept was just then becoming a 'fashionable idea' in its own right, as a way of thinking about the organization of science. This section presents an analysis of the evolution of the N C E program within the policy context outlined above. The data derive from examination of policy documents and interviews with key players involved in the program's formation. Although many of the sources interviewed for this part of the study belong to the scientific culture (most have at least one degree in the sciences and a background in government or university science) here they represent the science policy culture and the 'official' perspective. Most were associated with the federal government, either as past or present employees or policy advisors. The decision to embark on the Networks of Centres of Excellence program was made in an ideological climate that promoted the outright privatization of public-sector functions. Where this was not possible or desirable, public-private partnerships were preferable to mamtaining public- sector monopolies. Most new65 initiatives in science and technology partnerships saw their beginnings at this time. According to Niosi (1995:34-35), Canada's provincial and federal governments launched over one hundred new intersectoral research partnerships during this period. 6 3 This remains a chronic problem. Only Italy has a lower R&D: GDP ratio. Finance Minister Martin has made increasing the ratio a key commitment for the 2001 to 2003 fiscal period 69 A t the provincial level, Quebec's Programmme d'actions structurantes started i n 1984-85 wi th forty networks o f university and government laboratories. Ontario 's eight Centres o f Excellence were established i n 1986. In 1987, Quebec pioneered the Centre d'inidative technologique de Montrea l ( C I T E C ) at M c G i l l University. A t the federal level, Industry, Science, and Technology Canada ( ISTC, later Industry Canada) emphasized public-private partnerships and collaborations. B o t h the natural science and engineering and medical research councils ( N S E R C ; M R C ) actively supported collaborative targeted research. N S E R C started to fund 'big science' networks i n the early 1980s — i n the earth sciences (Lithoprobe) and integrated circuit design (Canadian Microelectonics Corporation). D u r i n g 1987/88, the budget year prior to the establishment o f the N C E , 15 percent o f N S E R C ' s total budget went to targeted research. (For further discussion see Fr iedman and Friedman, 1990, and N i o s i , 2000). In late 1987, delegates to the Nat iona l F o r u m o n Post-Secondary Educa t ion raised the idea o f centres o f excellence that w o u l d emphasize interdisciplinarity and involve networks o f researchers representing several institutions across Canada (National F o r u m 1987). In 1988, the Science Counc i l o f Canada advised that prosperity depended on integrating the university wi th the marketplace (Science Counc i l 1988). Reinforcing this theme, the Nat ional Advisory Board o n Science and Technology ( N A B S T ) recommended that 'greater emphasis be given to funding generic pre-competitive research collaboration by university-industry i n research consortia' ( N A B S T 1988: 76) This complex o f initiatives and recommendations helped provide a foundational platform for the January 1988 launch o f the N C E program. 6 4 Some material in this section appeared in Atkinson-Grosjean (2002) and Fisher, Atkinson-Grosjean and House (2001) 6 5 There were older initiatives. The Pulp and Paper Research Institute of Canada (Paprican), founded in 1925 at McGill University, represents perhaps Canada's most enduring example of a state-academy-industry alliance (C-HEF 1987: 45-6). Another enduring initiative is the NRC's Industrial Research Assistance Program (IRAP), launched in the 1960s, of which more will be said shortly. 70 Models for the NCE Program The N C E program was designed as a hybrid o f two influential models, one governmental and associated wi th industry, one non-governmental wi th no industrial affiliations. The first was N R C ' s Industrial Research Assistance Program ( I R A P ) established i n 1962; the second the Canadian Institute for Advanced Research ( C I A R ) founded i n 1981. I R A P dates from when the N R C still ran along personalist ('old boys ' network') lines. I R A P ' s prehistory was as the Technical Information Service founded by Mackenzie i n C D . Howe ' s Department o f Reconstruction and Supply i n 1945 and reenergized i n 1962 by a retired air marshal named Ra lph M c B u m e y . T I S gave 'knowledge subsidies' to industry i n the fo rm o f technical advice. The 1962 innovat ion added cash subsidies as well . I R A P w o u l d give grant funding to industry for private research, i n the same way that universities received grants for public research. A c c o r d i n g to Phi l l ipson, the idea o f giving public money to private industry 'was such an extraordinary precedent that it took a year's preparation by the Adv i so ry Panel o n Scientific Po l icy and required Treasury Board and Cabinet approval ' (Phil l ipson correspondence; see also Phi l l ipson , 1983). A s wel l as having an innovative approach to industrial research, the I R A P program was organized as a solution to Canada's geographical challenges. Rather than hire technically trained c iv i l servants to give hands-on advice to all sorts o f different industries, i n every region o f the country, I R A P created a mechanism for bor rowing them. Approximate ly two-thirds o f I R A P ' s field agents were locals, co- opted f rom industries, universities, and professional associations i n the region. They were paid by their o w n institutions wh ich received salary support f rom I R A P to release them. A c c o r d i n g to a former I R A P director, these agents constituted a 'field army' ( N R C 0101) w h o knew their regions, closely identified wi th their industrial clients, and enjoyed an enormous amount o f autonomy from the Ottawa bureaucracy. 71 These Industrial Technology Advisors as they were called, were gateways i n extended networks o f resources and facilities. Through them, small and mid-sized enterprises (SMEs) had access to some 130 public and private research- and technology-based organizations that were partners i n the field network. In the manner that J o h n L a w (1992) calls 'heterogeneous engineering', industry clients, their technical problems, technology advisors, provincial labs, federal labs, industry labs, engineering prototypes, and federal money were all l inked together i n long-chained networks dedicated to helping Canadian S M E s innovate. 6 6 The networking mode l that began wi th I R A P was clearly focused o n the technical needs o f industry. In contrast, the Canadian Institute for Advanced Research ( C I A R ) , launched some twenty years later (1981) by D r . Fraser Mustard, a distinguished medical scientist, was a networking mode l concentrated exclusively o n fundamental enquiry. Mustard and his associates promoted the idea o f focusing the basic research effort i n a l imited number o f fields where Canada had a strategic advantage and could make an original contribution. Certainly, elevating the overall p o o l o f knowledge w o u l d benefit industry i n the long-run, but no immediate applications wou ld be forthcoming. C I A R was conceived as an 'institute without walls, ' a network that w o u l d l ink together outstanding researchers i n institutions across Canada. A c c o r d i n g to those involved at the start, the idea came out o f a dissatisfaction wi th existing arrangements and a realistic sense o f the way knowledge works. T o deal wi th complicated problems, some sort o f institutional structure was needed that wou ld override disciplinary and geographical barriers to the full exchange o f knowledge. A s wel l , the geographical constraints suggested that 'the simplest way to try to move fields was to opt for an institutional structure that invested i n people rather than research' ( O T H F M - 2 ) . 6 6 See Callon 1997 and 1998 for analysis of the market significance of these networks; these should be read in relation to Granovetter's (1985) notion of 'embeddness' in relation to economic action 72 C I A R raised funding from federal and provincial governments and from private donations but the funding was 'unencumbered and i n no way strategic' ( O T H P B ) . C I A R ' s mandate was the pursuit o f fundamental knowledge for its o w n sake, without need for 'deliverables' or industry partnerships. Industry was viewed as 'a user o f the knowledge generated, rather than a collaborative partner' ( O T H F M : l ) . Fund ing was used to underwrite networking interactions and to buy-out researchers' time at their home universities so C I A R members could pursue research o n fundamental questions. The only criterion was that, 'five years f rom n o w you're going to be reviewed by an international panel who w i l l see i f you have shifted the wor ld communi ty o n h o w it views that question, i n terms o f its understanding' ( O T H P B - 1 2 ) . In 1986 Mustard became co-director o f the committee that was designing the main features o f Ontario 's Centres o f Excellence program, w h i c h was launched i n June 1987. A c c o r d i n g to a senior c iv i l servant, Mustard predicted that these new research centres w o u l d draw 'key researchers from across the country to Ontario 's universities and Ontario 's centres,' making it extremely difficult for universities i n other provinces to retain the best researchers ( N C E - D H : 4 ) A s a former N C E program officer put it, ' like a vortex all the best science wou ld migrate to O n t a r i o ' ( N C E - E I : 4 ) Earlier i n the year Mustard and one o f his associates i n C I A R , D r . Patricia Baird , had been drafted onto N A B S T . N o t surprisingly, therefore, it was N A B S T that brought forward the idea o f creating C I A R - l i k e national networks i n the fundamental sciences, to counter the Ontar io initiative. The target w o u l d be fast-moving, high-profile, competitive fields that had technological implications i n the relatively short-term. A t that stage, direct links to industry were not part o f the plan. The rationale was that effective strategic or applied research programs required a good fundamental research base. 73 The Minis ter and Depu ty Minis ter o f Industry, Science, and Technology Canada paid attention to the N A B S T recommendations. Clearly, the federal government needed something to balance the Ontar io initiative. The idea o f creating 'virtual ' C I A R - t y p e networks, rather than ' f ixed' Ontario-type centres, was especially attractive 'because there just wasn't enough money to create dozens o f new centres around the country' (civil servant, N C E - D H : 4 ) . The question regarding the relative merits o f ' f ixed' and 'distributed' centres originated i n the postwar K i l g o r e / B u s h debate regarding the creation o f the Nat iona l Science Foundat ion (see Chapter 2) to promote basic research; the issue was whether the N S F should fol low a 'centre o f excellence' mode l or one that favoured a more geographical distribution o f funding. 6 7 While interested i n the network model , the Minis t ry was not convinced that a focus o n excellence i n basic research was the correct route. Government wanted to see far more i n the way o f relevance— technology transfer to industry. The outcome was a blend o f I R A P and C I A R . L i k e the latter, N C E s wou ld invest i n people (researchers), rather than bricks and mortar (universities and hospitals), and wou ld be free to undertake fundamental enquiry. But , like the former, they w o u l d partner wi th industry and concern themselves wi th industry needs. A s wi th I R A P and C I A R , network researchers wou ld be paid by their o w n institutions but wou ld bui ld a strong sense o f belonging to a larger national entity. B u t i n contrast to both , N C E s w o u l d be parasitic o n their hosts (Newson 1994). Universities and hospitals w o u l d receive no compensation for paying the salaries and benefits o f network researchers, provid ing space and equipment, and covering laboratory overhead. N C E funds wou ld flow to the researchers through separate 'network offices' wh ich w o u l d have no duty o f accountability to the university. 6 8 Because their reporting allegiance was to the N C E directorate i n Ottawa, these new networks w o u l d 'float' above existing 6 7 Thanks for this point go to my correspondent, Andrew Russell, of the University of Colorado-Boulder, who is studying the development of computer research in the US during the Cold War. 74 institutions (Clark 1998). They wou ld provide the federal government w i th direct access to provincial university systems, overr iding traditional autonomy ( O T H - D R ) . The networks w o u l d create a national research capacity open to the needs o f industry and the economy. The compromise balancing 'relevance' and 'excellence' was the outcome o f sustained bureaucratic struggles to capture control o f the N C E initiative. The battle between the Minis try and the research councils was so fierce, it quickly became a case-study (Pullen 1990) for the federal c iv i l service training institute. Territorial Struggles and Program Design Al though the federal bureaucracy had been awash i n rumours that a major reform o f research funding was being planned, the prime minister's announcement i n January 1988 came 'out o f the blue and without any consultation' wi th the three granting councils responsible for university research (program officer, N C E - E I : 2). The research counci l presidents quickly forged an alliance to prevent the N C E initiative being implemented without their input. T h e president o f N S E R C assigned two staff members to observe h o w the Pr ime Minister 's Office was handling the new program and instructed his staff to develop alternative plans (Pullen 1990). A senior N S E R C administrator interviewed the consultant hired to develop the program and concluded that the objectives w o u l d be impossible to implement (too many criteria, often conflicting) ( N C E - M B : 3-4). T h e councils discovered, as wel l , that public servants were to review the research applications, wi th final decisions made by the Minis t ry; no peer review wou ld be built into the process. While NCE funds flowed to the networks through university financial systems, the university was just an intermediary 75 This contravention o f scientific norms became the councils ' point o f attack. They argued that peer- reviewed competitions were essential to the program's academic credibility. They insisted that the councils were the only bodies wi th the expertise to run such competitions and to administer the resulting research funding. Wi thou t their endorsement and involvement, they suggested, the N C E program w o u l d receive a chilly reception i n the academic community. I f the government wanted the program to succeed, the Minis t ry could not be allowed to control the initiative. In M a y 1988, a compromise was struck. The peer review process wou ld be deployed strategically. B y cloaking the program i n the 'objectivity' o f peer review, it could be protected from polit ical pressures. This separation could then be used to rhetorical advantage by the government. The Pr ime Minister 's Office announced that the three research councils wou ld run the N C E competi t ion and distribute the funds, while I S T C w o u l d act as the program's secretariat. T h e research counci l presidents and the deputy minister o f industry formed a steering committee, while I S T C retained overall control , albeit ' f rom a distance'. A s a senior c iv i l servant noted, the Minis t ry 'holds the pen ' when wri t ing memoranda to cabinet or making submissions to the Treasury Board and is also 'closer to the centre' than the arm's-length granting councils ( N C E - M A L : 18). Further, two o f the three research councils ( N S E R C and S S H R C ) fall wi th in the Industry portfolio and the Minis ter o f Industry's sphere o f responsibility. Nevertheless, the three counci l presidents exercised considerable poli t ical leverage o n the steering committee, because the Minis t ry had no experience wi th research management i n universities. They were also able to influence the direction o f intellectual inquiry, identifying as targets areas where they perceived a research gap. A s a result o f the compromise, the policy objective was to reshape the culture o f academic science around the dual goals noted earlier: excellence (fundamental research) and relevance (utility to industry). 76 A n Adviso ry Committee (to wh ich Fraser Mustard was appointed) was established i n June 1988 to design and implement the program. T h e committee developed four selection criteria. T h e weighting assigned to each reflected the success o f the research councils i n capturing the initiative. Research excellence was weighted at 50 percent; a 'coherent, focused program o f research' was deemed the most decisive feature ( N C E 1988: 1). Relevance to industry was weighted at 20 percent, as was 'linkages and networking' . The remaining 10 percent covered administrative and management capability. In language reminiscent o f Pasteur's Quadrant, an informant explains that [tjhe strategy was to be pregnant — we needed pure, long-term applied science that was somewhat guided by the needs of industry.... Everyone was grappling with the term 'pure, long-term applied science.' [It] was used to walk the fine line separating science and application (policy advisor; NCE-SS: 2-3) The program attracted diverse support. O n the one hand, it was sold to Cabinet as a regional economic development package. O n the other hand, it was promoted to scientists as an elitist program for producing the best science. In fact, according to one interviewee, it was neither, but merely a means to pu l l together teams o f the very best researchers w h o , by example, wou ld pu l l the rest forward (policy advisor; N C E - S S : 1). The nomenclature of 'excel lence ' facilitated the process ' o f capturing some o f the best researchers i n the country [and] recruiting them as champions for change wi th in the system' (senior c iv i l servant; N C E - D H : 8). Y e t the program was intended to reach beyond demarcations o f excellence and relevance 'to bring i n the whole concept o f research management and cross-disciplinarity' (program officer; N C E - S M : 22). A s suggested earlier, program design was m u c h influenced by the M o d e 1 / M o d e 2 theory o f knowledge product ion developed by Michae l G i b b o n s and colleagues i n the late 1980s and 1990s. G ibbons served as a science pol icy advisor to Industry Canada during this period, and sat o n the N C E selection committees. A c c o r d i n g to one informant, he was their acknowledged 'guru' (program officer; N C E - S M : 13). M i c h e l Ca l lon was also involved i n the early design and 7 7 implementation o f the program, as a member o f the International Peer Review Committee. Thus the conceptual framework for the N C E program seems to have been a hybrid o f M o d e 2 and actor- network concepts. Fo l lowing the receipt o f some 240 letters o f intent, 158 formal applications were forwarded for assessment to an International Peer Review Committee in N o v e m b e r 1988. Composed o f first- ranked scientists, engineers and social scientists, mostly from the U S A and Europe , this committee reported to the Adv i so ry Committee i n June 1989. A s previously stipulated by the research councils, the report was made public. Publ ic disclosure gave some assurance that the decisions were made i n accordance wi th established scientific criteria and were not politically influenced. Sixteen applications were deemed worthy o f funding, nine i n the 'must be funded' category and seven i n the ' recommended for funding' second tier. The Adv i so ry Commit tee endorsed all nine first-tier networks but, for reasons that remain unclear, w o u l d not support two o f the second tier networks. O n e o f these, o n ageing, was the only social science proposal o n the short list. After extensive lobbying by the councils, 'a decision came from above' to include the ageing network (policy advisor; N C E - S S ) . However , it wou ld be funded by the research councils rather than the N C E . The poor showing o f the social sciences was later attributed to selection criteria oriented toward engineering and the hard sciences rather than 'the broad perspective needed to make the participation o f human scientists possible' (program officer; N C E - E I ) . Because they reflected a compromise, the initial selection criteria failed to fully articulate the preferences o f either the research councils or the Ministry. In practice, networking and industrial relevance hardly figured into the equation. A n d because companies made few cash commitments at the proposal stage, it was difficult to assess the extent o f partnerships and linkages (program officer; N C E - M B : 6). Academics inexperienced i n such matters found it difficult to demonstrate such 78 competencies. F o r similar reasons the applications were weak i n defining proposed management structures. Furthermore, the reviewers themselves were not skilled i n assessing this area (program officer; N C E - S M : 1-2). A s a result, the reviewers could not bring themselves to say 'no' to the best science regardless o f the other criteria. They could not displace top quality science with inferior science just because they had a better management structure or because they scored so high on practical application. The other three criteria were ephemeral, intangible, hard to measure or understand. [Reviewers] could not bring themselves to knock out top science on the basis of criteria they did not understand and could not operationalize (policy advisor; NCE-SS: 3) In the end, the reviewers decided to 'gamble o n the best [science] and...hope that [the rest] happens' (program officer; N C E - M B : 6) Mobilizing Networks; Changing Attitudes The N C E program introduced 'two radical and important ' hypotheses according to Stuart Smith, chair o f the International Peer Review and Implementation Committees. A t a November 1989 briefing session for the wmning networks, he told participants that the first hypothesis would test whether collaborative research could be done at a distance using telecommunications technologies. The second w o u l d test 'whether it was possible i n the field o f long-term and fundamental research to force researchers to think about the economic and social impact o f their work, and more particularly about the channels by wh ich the research results w i l l be commercial ized ' (address reported i n N C E program internal newsletter, L ia i son 1 (1) January 1990). The federal bureaucracy had no operational framework for the implementation o f N C E policy. Ot tawa and the networks made up and modified rules and expectations as the concepts evolved. O n e o f the tasks o f the program directorate, i n the early years, was to convince scientists that their responsibilities extended beyond the standards o f traditional funding programs, and beyond the 79 norms o f academic science. Program staff realized that researchers initially viewed the program as just one more funding source for basic science. (See Chapter 4 for the way this attitude manifested at the network level). A policy advisor says 'the scientists didn't k n o w what they were getting into. They just went into it for the money. V e r y clearly at the start, it was just another pot o f money wi th some arbitrary rules that they wou ld pretend to fol low' ( O T H D R : 24). It was necessary to convey the 'expectation that [they] were going to interact wi th industry and that there was going to be some k ind o f measurable outcome from that interaction' (senior c iv i l servant: N C E - J W : 6). F o r the networks, that first phase was all about inventing themselves, consolidating themselves, establishing relationships among researchers, host institutions, and industry partners. Industrial partnerships were s low i n coming. 'There was a lot o f courting i n Phase I and not a lot o f commitment ' (senior c iv i l servant: N C E - J W : 23). The first year, fiscal 1991, was only a partial year. Networks spent most o f their time establishing the mechanics o f administration—systems, committee structures, and so on. After that, only three full years remained before funding ended. A t that point, no guarantees had been given that the program w o u l d be renewed. The program was experimental. A s far as anyone knew, four years total was all they had. That situation changed i n December 1992 when the Mulroney (Conservative) government brought down its final budget. 6 9 In the same speech that abolished the Science C o u n c i l o f Canada and the E c o n o m i c C o u n c i l o f Canada, Finance Minis ter D o n Mazankowsk i 7 0 announced that the N C E program w o u l d be extended. A new competi t ion w o u l d be held i n targeted areas and existing networks w o u l d be able to compete for a second four-year phase o f funding (fiscal years 1995-8). The decision was supported by a positive interim program evaluation carried out between July and December 1992. The evaluation reviewed the effectiveness o f program and network management, 6 9 Mulroney announced his resignation in February 1993. He stayed on as caretaker until Kim Campbell won the leadership contest in June 1993. The party was routed by the Liberals at the polls in October 1993, losing all but two seats 80 the level o f networking, and the nature and extent o f industrial involvement. F r o m the tenor o f the announcement, i t was clear that the latter was deemed less than satisfactory. In order to be renewed, networks w o u l d have to deliver m u c h more i n terms o f commercial relevance and industry partnerships. From the beginning, the need for industry involvement and cooperation in the networks has been stressed. Given the need to strengthen this kind of industry collaboration with the research community, funding is being extended. This will ensure that the most successful of the existing networks continue to contribute to competitiveness. (1992 Budget Announcement) A reduced budget o f $197 mi l l ion was allocated for the four-year period, 1995-98, wi th 25 percent set aside for developing the planned new networks. Modi f i ed selection criteria reflected the shift in emphasis f rom excellence to relevance, and precipitated the dilution o f meaning mentioned earlier. N o w five criteria, a l l equally weighted, had to exceed an established 'threshold o f excellence': • excellence o f the research program : 20 percent (was 50 percent) • ttaining o f highly qualified personnel : 20 percent (new) • networking and industry partnerships : 20 percent (same as before) • knowledge exchange and technology exploitation : 20 percent (new) • network management: 20 percent (was 10 percent). A s a senior c iv i l servant noted, I S T C had successfully 'reorientfed] the program to sometiiing that they were more comfortable wi th . ' ( N C E - J W : 12) The new criteria reflected what they had wanted from the start: a program that fostered more industrially relevant research (senior c iv i l servant; N C E - D H : 6). A rotation o f research counci l presidents helped consolidate this posit ion. T h e new leaders o f the M R C and o f N S E R C were 'very m u c h focused o n developing university-industry Mazankowski's connection with NCEs lasted beyond his political career. In 2000, he became chair of CGDN's board of governors 81 linkages [and] o n having academics work outside o f their traditional environments for interaction' (senior c iv i l servant; N C E - J W : 17). The attitude o f faculty was more ambivalent. The top-down decision to shift priorities represented 'a very serious concern for [some of] the researchers involved ' (program officer; N C E - S M : 9) and considerable turnover among scientists occurred. Some found the program more appealing and enlisted; others 'knew this wasn't the place for them [and] got out ' (senior c iv i l servant; N C E - M A L : 9). Since Phase II, all networks have conducted more applied and less fundamental research. Reduced budgets for the renewed networks forced the scientists to 'focus m u c h more on... lines o f research that were likely to be o f interest to industry'. The research still had basic components but was aligned 'to be o f greater interest to the existing industrial environment ' (senior c iv i l servant; N C E - M A L : 10). W i t h the election o f a Libera l government i n October 1993, the emphasis o n relevance became even more entrenched. B y n o w 'neoliberal ' principles had become a poli t ical or thodoxy as even centrist parties shifted to the right. Shordy after assuming office, the Liberals undertook a massive reorganization o f I S T C . A s i f to conf i rm the subordination o f science to the economy, the department n o w became simply Industry Canada. It assumed a much enlarged portfolio and a mandate to foster Canada's international competitiveness. The following year, 1994, a major science and technology program review was announced, together wi th the intention o f m o v i n g towards a new, national science and technology strategy. Months o f exhaustive consultation and review followed. After some considerable delay, the new national policy—Science and Technology for the N e w Century: A Federal Strategy —was finally announced i n M a r c h 1996 (Industry Canada 1996). The strategy adopted science and technology as a federal priority. Tak ing a 'Nat iona l System o f Innovation' (Nelson 1996) approach, it integrated academy, industry, and government research 82 under the rubric o f job creation and economic growth. The focus was o n the 'strategic investment' o f resources for 'the m a x i m u m economic, social, and scientific returns' (Industry Canada 1996: 9). The principal means o f achieving this was through the strategic use o f public-private research arrangements between universities, industry, and other levels o f government. B o t h the Conservative and Liberal administrations had crafted a climate hospitable to commercial relevance by applying a multitude o f mutually reinforcing policy instruments. Available data indicate their efforts were successful. Industrial support o f university research appears to be advancing more rapidly i n Canada than elsewhere. Table 1 shows that while the propor t ion o f industry funding for university research has increased i n all G 7 countries from 1985 to 1996, Canada's share i n 1996 is significandy higher than other G 7 nations. Table 1: Share of university research funded by industry (%) in 1996,1990, and 1985 1996 1990 1985 Canada 10.4 6.3 4.3 United States 5.8 4.7 3.8 Japan 2.4 2.3 1.5 France 3.3 4.9 1.9 Germany 7.9 7.8 5.9 Italy 4.7 2.4 1.5 United Kingdom 6.2 7.6 5.2 Source (OECD 1998:165) B y separating funding and performance sectors, Table 2 indicates that i n 1996 Canadian universities performed a higher percentage o f national R & D than other G 7 countries, wi th the exception o f Italy. 83 Table 2: Percentage of R&D Expenditures by Financing and Performing Sectors for the G7 Nations in 1996 Financing Sector Performing ! Sector Domestic Business Foreign Business Gov't Other. Internal Business Gov't Univs Canada 48.2 12.7 33.7 5.4 62.2 14.9 21.7 US 61.4 0.0 34.6 4.0 72.7 9.8 14.6 Japan 72.3 0.1 20.9 6.7 70.3 10.4 14.5 France 48.3 8.0 42.3 1.3 61.5 20.4 16.8 Germany 60.8 1.9 37.9 0.3 66.3 18.1 15.6 Italy 49.5 ' 4.4 46.2 0.0 57.7 19.9 22.4 U K 48.0 14.3 33.3 4.3 65.5 14.5 18.8 Source (OECD 1998:166) However , the Canadian business sector remains a l ow performer, suggesting Canada's industries continue to rely o n publicly supported research rather than develop their o w n infrastructure. Overa l l , the new strategy introduced i n 1996 produced a reduction i n federal funding support for science and technology, especially for the research councils. The N C E program was among the initiatives that w o u l d be cut. However , the networks came together, launched a public relations and lobbying campaign, and were successful i n reversing the decision (for details see Chapter 5). A s a result, the N C E program was made permanent i n the February 1997 budget, albeit wi th a 'sunset clause'. The purpose was to allow the program 'to continuously reinvent itself through a constant influx o f new people and ideas' (senior c iv i l servant; N C E - M A L : 11). The networks least likely to survive without government support w o u l d be culled, funding to those deemed to have 'graduated' f rom the program w o u l d be discontinued, and funding for all networks w o u l d be capped at a m a x i m u m o f 14 years. F o r the surviving original networks therefore, Phase III w o u l d be the end o f the line. Policymakers did not intend N C E s to become entrenched and institutionalized. They wanted researchers to be instilled, ' f rom the very beginning wi th a v is ion o f life after N C E funding' (program officer; N C E - S M : 11-12). 84 But as I w i l l demonstrate later, this sunset clause may have been a policy error. Especially for networks i n the life sciences sector, where a 10 to 12-year gap can separate discovery and final-stage clinical trials, the t iming seemed incomprehensible. The change created detrimental amounts o f goal displacement among networks i n this sector. Instead o f focusing o n advancing fundamental and translational research, networks facing sunset focused their attention o n speculative financial projects i n order to replace federal funding. Part o f the intention o f the N C E initiative was precisely to generate this k ind o f cultural change in academic science. The program's biggest achievement, according to one interviewee, has been to establish 'a market orientation i n academic researchers and a predisposition for collaborating wi th the private sector' (program officer; N C E - C A : 6). This included finding and developing receptor capacity i n Canadian industry, securing venture capital, negotiating multiparty intellectual property agreements, and establishing an effective process whereby network technologies could be licensed to industrial partners. T h e numbers o f patents filed and inventions disclosed increased significantly. 7 1 Sophisticated alliances wi th the financial sector allowed some o f the networks to attain experiential knowledge o f business and finance that often surpassed that o f Directorate staff. They knew what was needed to run their o w n programs, and felt constrained by the pedestrian advice o f N C E officials. N o t surprisingly, the networks began to take o n a 'life o f their o w n ' as they claimed increasing autonomy (program officer; N C E - S M : 11). A s one senior c iv i l servant put it: In some fields, however, patenting and licensing are not the normal routes for technology transfer; dissemination occurs instead through traditional routes, such as training and conference presentations. 85 We started to see change where the people who were working in the program had a very strong concept of what it was that they were doing. It wasn't always exactly the same as our concept, but they began to drive the program in certain ways.. .We [government] still set the agenda, but the level of contribution is much higher from the networks now and I would say that many times now we are learning from them as opposed to them learning from us....we started to see a change from us really driving the program to them taking much more ownership for it and starting to push into new directions (senior civil servant; NCE-JW: 29-30) The N C E Directorate became somewhat uneasy wi th the aggressive commercia l ethos that developed i n some o f the networks. They sensed things had gone too far. In its review o f one o f the life science networks, for example, the Phase III Selection Commit tee suggested that the network's research program should be 'directed to goals that are appropriate i n an academic setting' ( N C E - S C 1997). In other words, the network 'should not try to compete i n areas o f research where major pharmaceutical companies are already investing enormous amounts o f money and have a clear research lead and advantage' ( N C E - S C 1997). Bu t these Phase III funding proposals were prepared by networks facing the sunset o f N C E support. They were required to show h o w they w o u l d handle the transition. It was almost inevitable that they w o u l d respond i n commercial ly aggressive ways. In recent years, many o f the networks have formally incorporated to facilitate the management o f their extensive research programs, intellectual property portfolios and partnerships. Incorporation was always Industry Canada's preference. They saw formal, legal structure as a means o f eliminating the mode l o f collegial governance that had guided academic decision making i n the past. Bu t the research councils resisted, preferring to leave the decision up to the individual networks. After initially adopting a 'wait and see' posit ion, most have n o w incorporated. They have also created arms-length, for-profit corporations that use standard business tools such as mission statements and strategic plans. A decision to incorporate raises some interesting conceptual issues. A network is a loose association o f researchers, nodes, projects, and partners. It is the people and entities that make it up. B u t a 86 corporate body has legal powers o f association and personhood. It exists apartfrom the people and entities that make it up. A n incorporated (literally: embodied) network seems almost contradictory. Incorporation institutionaHzes these 'virtual ' entities, cloaking them i n substantive legality. The increasing adoption o f the corporate form signals the approaching funding sunset for 'mature' networks, and their desire to sustain themselves beyond this hor izon. Summary and Discussion In Canada, as elsewhere, national policies promote the integration o f public-sector research organizations into the economic mainstream: public science must move out o f academic and government labs and into the marketplace. Pol icy goals include the commercial izat ion o f research results as proprietary products, and the adoption o f new market-friendly institutional arrangements for the conduct o f research. Pol icy tools like intellectual property rights and publ ic/pr ivate research networks promote the development o f closer academy-industry relations and facilitate what can loosely be called the privatization o f the public knowledge base. Y e t at the same time as promot ing commercial relevance these policies also promote scientific excellence—a combinat ion that may appear at first appear counterintuitive. Bu t Canada has a long tradition, sttetching back into the 1 9 t h century, o f state involvement i n the promot ion o f programs that seek both. 7 2 The Nat iona l Research C o u n c i l was founded i n 1916, largely to address the needs o f industry for research that wou ld advance innovat ion. A t a time when universities were i n the business o f humanistic scholarship and teaching, rather than the advancement o f scientific knowledge, N R C ' s establishment represented the institutionaUzation o f federal attempts to advance 'useful' research. O v e r time, however, this intent was subverted as N R C 7 2 The first federally supported science initiative was the Geological Survey of Canada, founded in 1841, which laid the basis for the mining industry. In the 1880s federal support of astronomy produced longitudinal maps used in building the railways. The creation of experimental farms patterned 87 became increasingly focused o n conducting fundamental research and promot ing the same i n universities. Beginning i n the 1960s, attempts at pol icy reform proposed ways to 'correct' the orientation o f federally funded research and scientific cultures and turn public research towards economic development goals. The scientific establishment successfully resisted these attempts unt i l the 1980s, when the neoliberal turn i n Canada's poli t ical culture established a Strategic Science regime that wou ld harness public science to the needs o f the economy. O n e o f these initiatives established the Networks o f Centre o f Excellence program. A s a hybrid o f the Na t iona l Research Counci l ' s Industrial Research A d v i s o r Program and D r . Fraser Mustard's Canadian Institute o f Advanced Research, the N C E program was dedicated to both scientific excellence and commercial relevance. Because o f its novelty and dual commitments, the program was the subject o f fierce jurisdictional struggles wi th in the federal bureaucracy as the research funding councils and the ministry responsible for industrial and economic expansion fought for control . In the first phase o f the program (early 1990s) the culture o f the research councils dominated and scientific excellence was the primary selection criterion. In terms o f m y conceptual framework, this phase was concerned more wi th basic research performed under 'open science' conditions i n public institutions, or 'Bohr 's Quadrant' . In the second phase (mid 1990s), Industry Canada's concerns for commercia l relevance came to the fore. A s a result, some o f the networks entered into market relations more aggressively than had been anticipated. In other words, these networks 'overflowed' i n pursuit o f applied research for private profit and moved into 'Edison 's Quadrant'. After 1997, when the program became permanent, new networks were selected on more balanced criteria and relevance was redefined i n social as we l l as economic terms. 'Pasteur's Quadrant ' was the goal. after the USA's land grant movement produced innovations suited to a cold climate and large gains in agricultural productivity. Before the end of f h ^ But this goal has been pursued throughout the program's history. Mechanisms have been sought that w i l l couple creation o f knowledge and traditional means o f diffusion, such as journal articles, wi th 'translation' o f knowledge and new means o f diffusion such as technology transfer to industry partners. The two are rife wi th tension and ways have been sought to reconcile, for example, publication norms wi th the protection o f intellectual property rights. O r , when considering who to recruit into a network, to reconcile traditional criteria o f scientific merit wi th strategic judgements o f a research program's commercial relevance. C o n t r o l o f these and other tensions is accomplished wi th in the formal organizational and management structures the program requires networks to adopt. Overa l l , the program sought to promote a broad shift i n the research culture. Inter-institutional, inter-sectoral, cross-disciplinary, and multi-regional collaborations were favoured i n the network selection process. Constructive relations wi th industry and cost-efficient, even revenue-generating, operations were to be pursued. The extent that these goals were achieved is an empirical question addressed i n my case study o f the Canadian Genetic Diseases Network . F r o m the material presented to this point, it is possible to develop a mode l o f Canada's Strategic Science policy regime, and the way the N C E program relates to it (Figure 5). I suggest that this model , wi th modifications for local conditions, may be generalizable to other countries operating under a similar regime. 19th century, several federal government departments had established national laboratories for the exploitation of natural resources. 89 Figure 5: Model of Canada's Strategic Science Policy Regime in relation to the NCE program Interests Ideas Institutions POLICY FORMATION t t Relevance (IC) -» Research Culture <- Excellence (RC) POLICY INSTRUMENTS NCE PROGRAM NETWORK BUILDING i y i. CAPITAL FORMATION Social Economic Human Capital Capital Capital NATIONAL RESEARCH CAPACITY BETTER RECEPTOR CAPABILITY NEW RESEARCH CULTURE Legitimation Source: JAG 2000 The mode l shows the influence o f powerful interests, ideas, and institutions at the agenda-setting stage o f pol icy formation. Once an agenda for commercial relevance and scientific excellence is mobi l ized, competing state agencies (in this case: Industry Canada—IC, and the Research C o u n c i l s — R C ) place countervailing pressures o n the research culture and attempt to influence the 90 development o f policy instruments that w i l l further their interests. The N C E program is such an instrument. The construction o f 'networks o f centres o f excellence' is intended to promote the formation o f human, social, and economic capital, leading to a new national capacity i n research, improved receptor capability i n industry, and a new research culture. These results wou ld then legitimate such programs and encourage the development o f other similar initiatives. In the next section o f the dissertation, I move from the abstractions o f pol icy development to the materiality o f the actual practices and relations policy instantiates. 91 C H A P T E R 4: C O N F I G U R I N G T H E C A N A D I A N G E N E T I C D I S E A S E S N E T W O R K What is 'a network'? Often, we think o f something flimsy or ephemeral, like a cobweb, that can easily tear and drift apart, just webs o f relationships wi th nothing visible anchoring them i n place. 7 3 B u t as translation sociology ( A N T ) has shown, that is not the case. Ne tworks are anchored i n the materiality o f the actors that make them up: i n the infrastructures actors inhabit; i n the resources actors command; i n the allies they enrol; and i n the artifacts and instruments they employ (or, as is often the case, are employed by). A s Ca l lon puts it, networks are 'the very simple counterparts o f the spatial and time persistence o f actors: to translate is to exist' (in press, fn. 7). Thus actors 'come before' networks and actors 'make' networks; powerful actors make powerful networks. This chapter is about precisely that process. Wha t follows is the first part o f my case study o f the Canadian Genet ic Diseases Ne twork ( C G D N ) . The chapter is divided into two sections. In the first I examine the way C G D N 'knitted the first few stitches o f a web that still d id not exist' (Callon i n press, fn7) and h o w it secured itself to the material foundations o f universities. M y entry point is the individual leadership o f the network's Scientific 7 3 Used figuratively, the noun 'network' means 'an interconnected chain or system of immaterial things' (OED). Another usage is an 'interconnected group of people; an organization' (OED). 92 Director . The discussion is then expanded to take i n his enrolment o f a 'core-set' when setting up the network. 7 4 F l o w i n g f rom that, chronologically, is a description o f the network's genesis i n 1988 and the recruitment o f the founding researchers and professional staff. The section ends wi th a description o f the management structure and the formation o f an institutional identity, separate from the university. T h e second section comprises a critical analysis o f problems that have emerged from the way the network has been configured. These have to do wi th issues o f regional distribution, elitism and equity, social reflexivity, and public accountability. I. Power of One T o succeed wilFiin the parameters stipulated by the N C E program, member networks seem to require a strong, even visionary scientific leader; someone who perceives the program as a means 'to animate their v is ion and execute it ' (manager, PS-DS-23) . A c c o r d i n g to A N T , the most powerful actors—those w h o assume a network's leadership and become its spokesperson—are those who enrol the largest number o f allies. Spokespersons actually create the groups they speak for, by the very act o f speaking (Cambrosio, et al. 1990:214). Generative leadership o f this type was c o m m o n to all the networks created i n Phase I, but particularly those i n the life sciences. Strong leadership is consistent wi th the culture o f molecular biology, where the laboratory leader focuses all the resources and recognition o f the lab, and represents the entity as a whole to the lab's various communities. The leader functions 'as a symbol o f the lab, as the lab's information interface, its 'provider' , and as the one w h o plays the games o f the field' (Knorr -Cet ina 1999:254). In C G D N , that spokesperson was Scientific Di rec tor Michae l Hayden. H i s v is ion , communicated in a January 1991 essay entitled 'Science and Dreams' , was To use 'enrolment' and 'core-set' in the same sentence is to mix metaphors from two branches of science studies: ANT and SSK respectively. I will 93 to create a functionally integrated but spatially dispersed intellectual consortium.. .to open new pathways for collaboration and networking while breaking down the old style, conventional, departmental and institutional barriers. This is not business as usual ( C G D N S C A N - 1 : 2) A l l interviewees agreed 7 5 that Hayden was the person most responsible for the network's initial success and that he remains its biggest influence. H e conceived the network, envisioned its framework, and personally enrolled most o f the researchers and staff. H e is often characterized as 'a network i n h imse l f (board member, B - M P - 2 3 ) i n that it is his contacts and force o f personality that stamp the network's style as entrepreneurial and fast-moving. F o r a former N C E program officer 'Hayden is unrivaled as a scientific leader. H e was the right person i n the right place. H e was certainly the most effective o f the scientific leaders I observed' ( N C E - P O - M A L ) . Hayden appears to command the loyalty and respect, even affection, o f colleagues. He has actually made this one of the most, i f not the most, successful networks out of all those centres of excellence that were set up. (Researcher, BR-9-10) It's very strongly led by Michael Hayden. He has maintained the leadership through the whole time. He's certainly done an excellent job. I think it's very much his baby. (Researcher, DC-7) Simply put, Michael Hayden is a wonderful, wonderful, network leader. He always has been, right from the beginning. He's a rare combination—a person that's guided by principle but tremendously goal oriented. He knows what he wants to accomplish and he is tenacious. He won't let go of an objective he believes in, and he believes in the network. (Senior executive, PS-DS-6) Hayden's leadership style is characteristic o f the traditional command-and-control ( 'Mode 1') mode l o f academic science, i n wh ich senior scientists exercise almost total control o f their eponymously named laboratories. This is the mil ieu i n wh ich the current generation o f researchers was socialized. So it is not surprising that Hayden runs the network, i n the words o f a recent recruit, as 'a avoid engaging in the underlying theoretical disputes. 7 5 In many cases the opinion was volunteered, rather than prompted 94 benevolent dictatorship', nor that everybody seems to accept autocracy as the natural order. A s the recruit puts it, this is not a democracy; one cannot run a network like this like a democracy. Michael Hayden makes most o f the decisions. He has the best background. He's the best choice. So it runs quite smoothly (MW- 34-5). A n external observer notes that Hayden provides strong scientific leadership, but that his style is less collaborative and consultative than some. 'Hayden sets scientific directions by force o f personality although he seems to do so without mff l ing too many feathers. N o t necessarily bad, but different from the other two networks I think' ( H C , personal correspondence). O n e o f the N C E program officers—all o f w h o m are scientists themselves—explains it this way. It's not really a dictatorship. Y o u have to understand the scientific community that you're dealing with...It's a highly educated population. A highly critical, opinionated population. We are trained to be very critical o f each others' work. So when you're dealing with that sort o f culture it requires very strong leadership. Others might equate it to dictatorship but it is not. Y o u have to be able to stand strong against all o f the criticism. A n d so the leaders have to be very strong. A n d very firm. Because it's not going to work otherwise. ( N C E - P O - L D - 7 ) Hayden's way, explains a senior researcher, is to put his imprint o n something and set the strategic direction, then hand it over to professional staff and move o n to something else. ' H e has the final word , but those people are n o w so indoctrinated that they run o n their own . They don' t need to go to h i m for everything. A n d it works ' (BG-43) . A veteran staff member agrees. Hayden makes the decisions and sets direction, she says, but, over the years, 'he backed o f f and let us do our o w n thing' (PS-CS-24). A senior science bureaucrat, who was the network's program officer for a number o f years, notes that Hayden indeed d id less hands-on management than most o f the other leaders. 'But when he d id intervene,' she says, 'he had vis ion and a pretty good schtick. H e really got things done' ( N C E - P O - M A L ) . 95 Hayden's willingness to allow the network's professional staff to manage network affairs was, in part, an artifact o f the program's design. A s described later i n the chapter, a major novelty o f the N C E program was that network research was conceived as managed research. G i v e n the large amount o f funding allocated to each network, and the complexity o f l inking so many institutions and researchers together, formal management structures were deemed essential. In effect, each network had two leaders. O n e was the scientific director. The other was a network manager w h o 'made bloody sure they knew what everybody was doing. A n d kept tabs o n everything. W h i c h is very unusual i n a science program' (Policy analyst; N C E 1 5 - 1 3 ) . A s scientific director, Hayden coordinated and integrated all the research projects and programs. Bu t the network's senior executive officer controlled the spending and moni tored the researchers to ensure that all the network's non-scientific mandate points were being met. In accepting the posit ion, says one o f these senior staff members, he knew work ing alongside Hayden wou ld be demanding, but felt confident enough to accept the challenge. T knew that I cou ld work wi th hirn long enough to work it out. Y o u just have to be strong. H e backed me and I backed h im, it worked both ways' (PS-DS-22). Part o f Hayden's success as a leader came f rom his strategic abilities. H e knew h o w to mobi l ize resources, at the last minute, for the highest impact. F o r example, the face-to-face aspects o f funding applications—expert panel visits, presentations to the N C E selection committee, and so on—were orchestrated to m a x i m u m effect. A c c o r d i n g to informants, every ally, every board member, every industry partner, every network scientist was invited to sit at the table. Everyone gave five-minute presentations o n their research and /o r role i n the network, literally overwhelming panelists wi th information and enthusiasm for the science. 96 These funding reviews and site visits were highly polished performances. Everyone was wel l prepared. The whole effort was timed and scripted, without appearing slick. A s the Managing Direc tor describes it, 'everybody was there to back up that this organization was do ing its stuff.. .you can't leave anything to chance, you have to cover all o f the bases' (PS-DS-61). Hayden himself, however, relied o n staff to set things up, rarely focusing unt i l the very last minute. H e caused more than a few anxious moments but people learned to have faith i n his ability to deliver the goods. The fol lowing anecdote, by the N C E program officer responsible for the network i n Phases I and II, provides an example o f his eleventh-hour style. I never saw anybody like Michael for pulling things off at the last minute. I'd talk to him one day and he'd have to do something the next day and he would be totally disorganized. And I'd expect an utter disaster. And, then the next day I'd see him perform and he always seemed to pull the rabbit out of the hat. Yeah, the lights went on and Mike was there. He'd just put in a terrific performance and really inspire people in the network. The night before the selection committee meeting [for Phase II] there was a dinner for Michael Smith in recognition of the Nobel Prize. And Michael Hayden was at the dinner and I talked to him and he was really nervous about appearing before the selection committee the next day and all that went along with it. And I thought 'Oh God! He is unprepared. He is going to bomb,' you know? But when he came in the next day he did a really smart thing. He brought in JG, a private-sector partner, to say what was great about this network from industry's point of view. Hayden was the only person who did that. Everybody else brought in their scientific director and their management person. So his network was unique in that way. And that was exacdy the dimension that the committee wanted to hear. A distinguished member of the selection committee.. .quite an influential guy.,.said 'you know we can't not fund this guy. This guy shakes trees.' And I always remember that and it certainly is true. Michael really did have that impact. (NCE-PO-MAL) Involving so many network members—scientists, board members, and industry partners—in the renewal effort was extremely innovative at the time. N o t all networks took such an inclusive 97 approach. F o r example, a researcher from another life science network 7 6 reported having few companions when he attended a renewal panel. The leaders had invited only three or four scientists to present a synopsis o f what was happening i n that network. ' N o n e o f the other scientists was invited; it was only a handful o f people ' (FT-8). That network subsequendy lost fanding because, to this researcher, they had failed to engage their scientists i n the process. Unl ike Michae l Hayden, that network's leadership 'essentially excluded all the scientists and then tried to move forward. But o f course, they had nothing left. The scientists had abandoned ship' (FT-8). A t C G D N , i n contrast, 'every one o f our scientists was at the review committee meetings. N o one was missing unless their mother was dying. There were no excuses. Y o u had to be there' (Manager, PS-DS-14) . Thus the essence o f Hayden's scientific leadership was to involve others. Hayden extended that concept o f involvement to the wider community. H e calls this 'civic science'. W h e n scientists accept public money, he says, they accept a responsibility to the communities that provide those funds. Science and scientists must not be cloistered; they must participate actively i n society and be fully accountable. The obligation is not so m u c h to the government, Hayden argues, but to the public at large. In return for the privilege o f being funded to practice science, scientists must accept the responsibility o f ensuring that that the communi ty understands what they do. H e says facilitating this understanding is as important as his work o n human health. W e have a responsibility to reach out to the people who support us . . .We are guests o f the public. A n d so we have a responsibility to acknowledge that they are the source o f what we're doing, and why we're do ing i t . ' (MH1-6-8) A l though 'civic science' sounds high-minded, it seems to have more to do wi th furthering public funding o f science, than public understanding o f science. T o use the vocabulary o f A N T , when scientists are astute about enrolling and mobilising the public as allies; when they convey a convincing The researcher also belonged to CGDN, so was able to compare both networks 98 message, the public will pressure politicians to maintain or increase funding levels. The cuts to the basic research budget, in the mid-1990s, he says, occurred because scientists 'were not civic enough. And so people didn't place enough priority on it' (MH1-50A). Seeing what was happening to other programs, NCEs 'had to get out there and make sure [network] research was high up on the political agenda. Governments do respond to the people, particularly around election time' (MH1-50A). The reference here is to 1996. As part of the deficit reduction program, the federal government had decided to discontinue NCEs. The winding-up process had begun; no more fimding would be forthcoming. In response, the networks, led by C G D N , waged a national public relations campaign to save the program. As a senior network manager explains, 'it took about four months but we won. We won big.. .We convinced the government that this was a program that they couldn't afford to let die' (PS-DS-29).77 In other words, through a process of interessement government had been persuaded to define their problem in such a way that the N C E program was the solution: the obligatory passage point for Strategic Science. Since then, according to Hayden, network scientists have been 'tremendously civic'; in every part of the country, 'they are out there talking to the wider community' (MH2-26). Perhaps pardy as a result of the mobilization of public sentiment in this way, scientific research recovered its place on the policy agenda. As the deficits turned into surpluses, former funcling levels began to be restored, then equalled, then exceeded78. Research funding was back on the federal 'radar screen': a major priority item in the budget for four consecutive years (1998-2001). Powerful advocacy coalitions (Sabatier 1988) mobilized to lobby for NCEs. Program funding almost doubled between 1997 and 1999, from approximately $40 million a year at the end of Phase II, to $78 million a year in the 1999 budget. 99 Civic science can thus be seen as a rhetorical strategy that aligns scientists' self-interest wi th the public interest by enroll ing the public as allies i n the network. ' B y doing it, ' says Hayden, 'we ensure our future' (MH1-6) . Whi l e mobi l iz ing public support for science funcling is a legitimate activity, some observers find something slightly 'slick' about the way Hayden packages it. O n e critic, a senior scientist and pol icy consultant, says, ' M i k e Hayden is what I w o u l d call an operator. I do not mean this in a terribly critical way. It is just the sort o f person that he is ' (HC-1) . Ano the r senior scientist criticizes Hayden's ability to present genetics as the solution to a host o f medical problems, thereby ckverting attention f rom the complex 'web o f causation' i n disease o f wh ich genetics is but a minor part ( O T H - B 3 7 ) . Hayden has extended his personal network and entrenched his leadership role over the decade o f the network's existence. L i k e 'Pasteur' (Latour 1988), 'Hayden ' has become the authorized spokesperson for legions o f molecules, machines, and tests; patients, doctors, and researchers; founder populations; government hinders; disease foundations; and pharmaceutical interests. B y interesting and enroll ing powerful allies and mobi l iz ing the rhetoric o f medical genetics i n the public arena, Hayden's science has become a poli t ical practice, a science o f associations, what A N T calls 'politics by other means' (Latour 1988:40). T o understand 'Hayden ' and ' C G D N ' as consolidated complexes o f linkages, it is helpful to map the beginnings o f the network, before any taken-for-granted relationships were stabilized. In the early days, Hayden reached out to senior colleagues to help bui ld the network. H e was enroll ing an elite nucleus o f allies, a core set. 7 7 As discussed earlier, however, there was a sting in the tail of success. While the program itself was made permanent, individual networks would not be. 7 8 For example, within 3 years of its founding in 1998, the Canadian Institutes for Health Research budget was twice that of the MRC it had replaced 100 Enrolling the Core-set Harry Col l ins proposed the idea o f a 'core-set' i n relation to scientific controversies and their outcomes (1981,1985). H e used the term to describe the group o f scientists involved in the resolution o f any given technical controversy. Membership i n the set does not depend o n c o m m o n institutional affiliations or seniority but only o n a mutual interest i n the outcome. A core-set thus can be understood as a web o f interests and associations formed by people o f disparate linkages and alliances. Because o f its descriptive generality, the term has relevance outside controversy studies. Fo l lowing Michae l & Birke (1994), I combine it wi th A N T ' s concept o f enrolment. In January 1988, when Pr ime Minister Mul roney announced funding for something called the N C E program, Hayden, then a young Associate Professor at the Universi ty o f Bri t ish Columbia , immediately saw the potential for a genetics network. A s a relatively junior researcher, however, he w o u l d need to enrol established members o f the genetics communi ty i f a proposal was to succeed. H e telephoned the two top medical geneticists i n Canada: Charles Scriver (an expert o n Tay-Sachs and P K U ) at M c G i l l Universi ty and R o n W o r t o n (discoverer o f the Duchenne Muscular Dyst rophy gene) then at the Universi ty o f Toronto 's Hospi ta l for Sick Chi ldren ('Sick K ids ' ) . Hayden knew neither man personally—they had not worked together at all previously—but he knew their work and he knew their stature. H e told them 'you know, we've got an opportunity here for a network i n the genetic basis o f human disease'. W o r t o n had been thinking along similar lines himself and was wi l l ing to work o n it wi th Hayden. Scriver was more circumspect. Hayden says 'I was really young back then and Charles was like the Father o f Genetics. W h y w o u l d he care? A n d why wou ld he trust me enough to work wi th me o n this?' Scriver was an essential ally for several reasons beyond his scientific seniority. First, he had helped found a wel l -known program called the Quebec Ne twork o f Genet ic Medic ine , twenty years earlier, 101 i n 1969. That network ran a screening program for newborns and a distributed system o f centres providing diagnostic fol low-up, genetic counseling, and treatment. The group had recendy published an article i n Science's first theme issue o n h o w science could contribute to societal initiatives and concerns. Scriver suggests that wi th in this context the network's name and structure attracted Hayden's interest. Second, Scriver had research projects funded under Quebec's Programme d'action structurantes. That provincial program, formed i n the early 1982, appears to have been one o f the prototypes o f the federal N C E program, formed i n 1988. L i k e N C E s , A c t i o n Structurantes projects had to be performed by a team o f investigators. Whi l e industry partnerships were not required, they had to be multi-university and mmti-msciplinary. Scriver was coming to Vancouver the fol lowing week o n a personal matter. Hayden arranged a meeting. The two researchers, separated i n age by a generation, sat o n the steps o f Vancouver A r t Gallery, i n the chilly middle o f February, going over the issues. Hayden summarized the federal announcement and pointed out the similarities wi th what Scriver had built i n Quebec. H e remembers talking about pul l ing together the 'best o f the best' across the country, i n the same way that Scriver had pulled together the 'best o f the best' i n Quebec. H e talked about the rnilHons o f dollars being made available for research. Finally, he asked Scriver whether he w o u l d join i n and Scriver agreed. Hayden calls it 'a pivotal conversation'. Scriver says o f his recruitment, I think Michael recognized an interesting opportunity when he saw it, which has been his trademark all along. He was aware of what we had been doing in Quebec with bringing academic genetics to a societal interface, and he thought that would make an N C E proposal look good A l l three had their o w n personal networks o f colleagues and contacts and technical capacities, and these quickly combined and multiplied the way networks do, sparking from node to node. Hayden, Scriver and W o r t o n were thus the embodied 'centres o f excellence' f rom wh ich the network originally sprang, and they continue to lead the network today. Senior members o f the network 102 called them 'the triumvirate'. Beyond these three founders was the elite group o f scientists they enrolled to craft the init ial letter o f intent and subsequent proposal. W o r t o n recruited two people from 'Sick Kids '—Lap Chee T s u i and R o d M c l n n e s , while Scriver brought i n R o y G r a v e l and E m i l Skamene from M c G i l l . Together wi th Hayden, that made a core set o f seven. This 'group o f seven' met i n a Toron to hotel r o o m for a day and a half to brainstorm ideas. Bu t that first session was followed by a long hiatus as they waited for the government to specify what was expected i n the letters o f intent. R o n W o r t o n takes up the story. The next thing I remember is that I'd planned a three-week holiday for that summer and I'd just bought a cottage the fall before. So this was my first summer in my new cottage. I had never had a three-week holiday before. This was going to be my first lengthy vacation. And I'd been there about a week and a half and I got a call from Michael and he said he'd just heard that NSERC-the leaders of this program at the time—were doing a cross-Canada tour talking about the network model and how to apply and so on. The tour would be in Toronto the following week. That ended my three-week holiday. I went back to Toronto, listened to the presentation and took notes and called Michael and two weeks later I was with him in Vancouver. I guess we spent the best part of that summer putting together the letter of intent.. .and then.. .in the fall, it had to go very fast.. .We only had six weeks between notification of the success of the letter of intent and the requirement for the proposal. The core-set identified and enrolled people i n other universities and hospitals, expanding in multiples from the original group o f seven, to fourteen, and then to twenty-one for the formal proposal. R o y G r a v e l remembers recruiting people into the program dur ing the summer o f 1988. 'I recall there was a meeting i n Toron to , the Genetics Society or something o f this sort, that was N o r t h A m e r i c a wide. It brought a lot o f these people into the city. B u t that was very close to the deadline. W e already had most o f the people identified by that point ' . O n e o f the most novel aspects o f the N C E initiative, one that caught the attention o f scientists, was that research was to be extended across Canada i n lateral, east-west interactions. Th is was not the 103 traditional way Canadian science had been organized. Few national forums brought Canadian scientists together. M o s t connections and collaborations were nor th /south . Canadian scientists tended to meet each other, i f at al l , at conferences i n the Uni ted States. A s a result, apart f rom those recruited from the same institution, people came into the network as strangers, but wi th a new basis for interaction, w h i c h was the network itself. A s one scientist explains, I didn't know who Michael Hayden was and I didn't know many of the scientists who subsequently became involved. It wasn't so much that people stayed on one side of the continent or another. It was just harder to find people throughout Canada. So this network idea became interesting very quickly, because we met new people doing collaterally related things. RG-5 The recruitment process was quite divisive, however, as w i l l be discussed shordy. The rights and wrongs o f who was, and was not, invited to join are still being debated. Four levels o f investigator were specified i n the proposal. Six o f the original 'group o f seven' were designated principal investigators ( P i s ) — individuals wi th 'established international reputations' i n the field o f molecular and /o r human genetics. A l l men, three o f the six P i s were based at Sick K i d s ; two were from M c G i l l , while Hayden was the sole representative from the West. T h e seven scientists at the next level were designated research associates. These four w o m e n and three men (one from the original core-set) were individuals wi th 'established reputations' i n human genetics, many o f w h o m were shifting their research program to the molecular level. O f the seven, four were based at Sick K i d s , one at M c G i l l , while two represented the prairies. Hayden was still the sole representative o f U B C , the headquarters institution. A third level was called young investigators: A l l men, these three young Canadian scientists—one each f rom the universities o f Ottawa, Montreal , and Bri t ish Columbia—were said to have demonstrated 'outstanding creativity' i n the early stages o f their career. The significance o f the final level—core facilities directors—was immediately understood by Hayden, but perhaps not by the 104 others. Directed by four men and one woman , the core facilities quickly became the key to the network's success. In fact, the core facilities came to define what it meant to do 'network science'— they were true 'collaboratories' (Finholt and O l s o n 1997; W u l f 1993). A s w i l l be explained later, core facilities had bo th cognitive (human) and material (non-human) elements. They were a combinat ion o f the directors' technical expertise and interventions, and the material equipment and instrumentation. Because Hayden realized the importance o f these advanced technologies, directors o f three o f the five core facilities specified i n the proposal were based at U B C . In all, the 21 scientists listed as network members i n the 1988 funding proposal represented eight universities and five associated hospitals and /o r research institutes: 7 9 Universi ty o f Bri t ish Co lumbia (including the Universi ty Hospi ta l and the Biotechnology Research Centre); Universi ty o f Calgary; University o f Toron to (including the Hospi ta l for Sick Children); M c G i l l University; University o f Montrea l ( inc lud ing Hop i t a l de Ste. Justine); University o f Ot tawa (including Children's Hospi ta l o f Eastern Ontario) ; Queen's University; and the Universi ty o f Mani toba . Figure 6 be low summarizes the investigators by level, their institutions and locations, as wel l as their research interests. (See also Figure 8, later, for comparison wi th Phase III). All the hospitals/institutes are associated with universities but some are more autonomous than others. 105 Figure 6: C G D N Investigators, listed in 1988 Proposal for Phase I of N C E Program Name Institution City Research interests PRINCIPAL INVESTIGATORS Gravel0 HSC/UT Toronto inherited biochemical disorders including Tay Sachs Hayden UBC Vancouver late onset genetic disorders including Huntington Scriver* McGill Montreal physiological genetics and human genetic variation Skamene McGill Montreal genetic susceptibility to disease Tsui* HSC/UT Toronto cystic fibrosis and gene regulation Worton*3 HSC/UT Toronto Duchenne Muscular Dystrophy and genome structure/function RESEARCH ASSOCIATES Cox" HSC/UT Toronto antitrypsin deficiency and human genetic variations Fielde UC Calgary genetics of multifactorial disease including diabetes Gallie HSC/UT Toronto Retino Blastoma and other genetic malignancies Greenberg1 UManitoba Winnipeg hypophosphatasia Mclnnes HSC/UT Toronto genetic diseases of the retina and inherited biochemical disorders Morgan* McGill Montreal complex phenotypes and population genetics Robinson HSC/UT Toronto lacticacidemias YOUNG INVESTIGATORS Goodfellow3 UBC Vancouver multiple endocrine neoplasia Korneluk CHEO/UO Ottawa myotonic dystrophy Mitchell HSJ/UM Montreal inherited biochemical disorders CORE FACILITIES DIRECTORS Aebersold2 UBC Vancouver Protein Analysis and Sequencing Duncan1 Queens Kingston In situ gene mapping Jirik« UBC Vancouver Transgenic Mice and Gene Targeting Lea3 UT Toronto Hybridoma technology Lee4 UBC Vancouver Electron microscopy 1: Not renewed 1996 (a) relocated to University of Ottawa, Childrens' Hospital of Eastern Ontario, 1996 2: Resigned 1994 (b) relocated to University of Alberta, Edmongton, 1996 3: Resigned 1992 (c) relocated to University of Calgary, 1999 *: Also core facilities directors (d) relocated to University of Calgary, 2000 (e) relocated to University of British Columbia, 2001 106 The last few days before the submission deadline for the proposal were especially intense. In the words o f R o n W o r t o n , it was 'an enormous effort'. I flew with my secretary to Vancouver for the last six days or so before the proposal was due, because it was too awkward to try to manage it from two cities. And this was the early days of computers, they were fairly crude at that time. Their memories were small. But Excel had just become available.. .So, we went out and bought that program a couple of days before I flew to Vancouver. My secretary was reading the Excel manual on the airplane so that when we got to Vancouver, she could do all the spreadsheet work to put the budgets together. W i t h everyone work ing around the clock the proposal was submitted o n time, N o v e m b e r 30 1988, under the tide Genet ic Basis for H u m a n Disease: Innovations for Heal th Care ( C G D N - F P 1988). It was one o f some 158 formal proposals submitted i n response to the original call. The leadership issue had been decided by then. Hayden w o u l d be Direc tor and, by virtue o f that fact, U B C wou ld host the network's administrative offices. W o r t o n and Scriver were listed as Co-Directors . After the excitement subsided, everyone went back to their labs while the process worked its way through the bureaucracy. G i v e n the intense activity o f 1988, the hiatus was something o f an anticlimax. It took almost a year before the successful networks were announced (see Chapter 4 for a description o f activities at the federal level i n the mtervening months). T h e n , o n October 26 1989, the 15 networks were notified o f their awards. The genetics network w o u l d receive $17.5 mi l l ion over four years. 8 0. A s k e d why he thought the C G D N proposal succeeded, one o f the founders responded The N C E review committees looked at our science, first. That's your ticket to get in. Once you've accomplished that, you also have to demonstrate that you have a different outlook within the network than in the basic science system. So, the balance I thought was good. We had the breadth of everything. R G -22 8 0 Because of delays, the first phase was actually only a little over three calendar years, although it spanned four fiscal years. The fiscal year ends on March 31". 107 F o r the new networks, the nine months fol lowing the announcement o f Phase I awards—the gestation period from N o v e m b e r 1989 through July 1990—were chaotic, as federal bureaucrats struggled to put administrative structures i n place. The first tranche o f funding was not advanced unti l Augus t 1990, more than three years after the program was first announced as part o f the A p r i l 1987 InnovAc t ion strategy, and 30 months after the funding commitment was made i n January 1988. The delays indicate the novelty o f the program. Federal systems to implement and manage it had to be developed de novo. In the selection process, most o f the attention had been paid to scientific excellence. In the implementation process, consideration had to be given to the other criteria: linkages and networking; relevance to future industrial competitiveness; and administrative and management capability. These non-scientific elements constituted a large part o f the program's novelty. Taken together, they meant N C E s w o u l d function as 'research economies ' wi th proper management and governance. These elements w o u l d be covered by a 'memorandum o f understanding' as it was then called, an internal agreement governing each network's formal 'powers o f association' 8 1—its management and governance structure, and its public- and private-sector partnerships. C G D N ' s first internal agreement was signed o n July 4 1990. T w o industry partners were s igna tor ies—MDS Heal th G r o u p L imi ted and M e r c k Frosst Canada Inc—as wel l as the 13 institutional partners referred to earlier. 8 2 O n c e the formal agreement was i n place, funding was released and the network could seek staff to fulfil the non-scientific criteria. T h e dynamics o f network formation came into play here too. The network's administrative manager was recruited from industry partner M e r c k Frosst's research planning divis ion i n Montreal . She set up the initial systems. T h e n D r . D a v i d Shindler—a leading science policy advisor—was identified by one o f the network researchers as a 'person o f interest'. 8 1 Note that legal powers resided with the host universities. 108 H e was recruited from Canada's science secretariat i n L o n d o n as the network's Managing Director . W i t h the two key employees i n place, the network's administrative centre was opened at U B C in September 1990. II. Managing the Network The history o f the N C E program has been described as 'the evolution f rom free research to managed research to industrial participation' (policy advisor, N C E - M B : 13). T h e N C E directorate believed that management expertise and governance could 'make or break the networks' and was 'as important as the excellence [of the science]' (program officer; N C E - S D : 3). Management would be one o f the key features that extinguished networks from academic science-as-usual. A s stated earlier, the N C E program was conceived as large-scale managed research. F o r a former program officer, now a policy advisor, 'this was 'a major novelty [and] a shock to many; perhaps it [was] the first culture shock' ( N C E - M B : 9). Bu t an Industry Canada bureaucrat views N C E s as simply 'slighdy more managed or administered' than is usually the case i n academic science; managers simply looked after the paperwork, knocked o n doors look ing for partners, or otherwise freed researchers from tasks that diminished their productivity ( N C E - D H : 14). T h e two interpretations: 'culture shock' and 'normal practice' reflect the cultural differences between the program's governing agencies: the research councils, o n the one hand, and the Minis t ry , o n the other. Stipulations were put i n place that all networks w o u l d have a board o f directors, a scientific committee to organize the research program, and a management team. N e t w o r k boards and committees were to be structured to br ing the expertise o f industrial partners to bear o n research 8 2 Where researchers worked in university hospitals, both the university and the hospital were named as network partners, making the network appear more extensive than it was.. 109 management. Th is industrial representation took time to achieve, however. In Phase I, C G D N ' s board was heavily weighted to academics, wi th U B C ' s D e a n o f Medic ine as Chair . The federal decision to restructure the selection criteria for the Phase II competi t ion put the scientific and non-scientific mandates o n a par. This decision reflected Industry Canada's concern that, i n Phase I, too m u c h emphasis had been placed o n research excellence and not enough on industrial relevance. In other words, unless formal management structures were given equal status, it was far too easy for a network to allow researchers to do 'science-as-usual', that is, to fol low serendipitous directions, and do 'more or less what they wished to do ' ( N C E program officer; C A : 10). The pressure for increased management was also a function o f the increasing size o f network research programs. Management brought an overall v is ion, 'the strategic vis ion for the whole group, which was unusual i n academia' ( N C E Program Officer S D : 10). A s C G D N interpreted the management mandate, 'some level o f cohesion, some level o f network identity, some level o f management, some level o f cooperation' was required (senior executive, PS-DS-24) . In a distributed network, where people do not necessarily see each other, 'there has to be some [management] glue at the core; i f there's no glue there it ain't going to work ' (network administrator, PS-CS) . Bu t C G D N scientists were not used to being monitored by managers. A t least i n Phase I, network funding looked to them like 'just another federal grant; just business as usual' (network administrator, PS-CS-9) . It was the task o f management to persuade them otherwise—that not only the standard o f excellence but all o f the program's mandate requirements had to be met. Managers made the baselines clear. 110 If you fell down on any one of them, you were finished.. .We had to be pretty tough and it was hard. It was painful. We had to kick people out of the network when the work wasn't up to scratch. When they didn't maintain their science, or they weren't doing it the way we saw it had to be done (PS-DS-24). This level o f cont ro l over researchers was possible only because the most senior executives held P h D s . B o t h the original Managing Direc tor and his successor belonged to the scientific culture and enjoyed peer status wi th network researchers. The i r scientific credentials helped to establish their credibility when enforcing accountability. A s members o f the culture, they understood the competitive nature o f scientific careers. Whi l e they reinforced high standards and the orientation to excellence, they also sought to encourage researchers to maintain their science and be acknowledged for it. Tt wasn't just about grants. Bu t to be recognized by their peers for the good work that they were doing ' (senior executive, PS-DS-17-18) The maintenance o f standards paid dividends. B y adjusting to the program's changing demands, C G D N w o n a total o f 14 years funding i n all, the max imum allowable. The network was successful i n each competi t ion, being renewed for Phase II, i n the m i d 1990s, and again for Phase III. After Phase I, m u c h o f the hierarchical partit ioning o f researchers disappeared. In subsequent competitions, all the original associates were reclassified as Pr incipal Investigators. Core facility directors were also listed as principals, reflecting the reality that most ran research programs as wel l as providing a service to other members. The category o f 'junior researcher' disappeared. (Subsequendy, promising young researchers were appointed as 'network scholars' o n a fixed term.) Ne twork documents 8 3 show 33 Pr incipal Investigators at the start o f Phase II, representing nine universities and four related hospitals/institutes. After the Phase III expansion, the network agreement details 50 Pr incipal Investigatorss at 12 universities and eight related hospitals/institutes. 8 3 See (CGDN-FP 1993; CGDN-NA 1994; CGDN-FP 1997; CGDN-NA 1998). Often documents disagree. For example, the funding proposal will list more partner institutions than the network agreement. When there is a discrepancy, I take the network agreements to be the more reliable source, since these list only formal signatories. However, the fact of the matter often lies in between. I l l The hospitals and universities referred to above were rarely enthusiastic signatories to the network agreements. T o them, a network was a problematic organizational entity. G i v e n that Ottawa's original intent was to bypass university autonomy, it was little wonder that conflicts occurred between these reluctant 'hosts' and their unwanted 'guests', as the networks established their institutional identity. A s Michae l Hayden describes the relationship, 'universities didn' t trust the networks. They saw us as a power grab. They saw too m u c h power going to the networks away from the universities. A n d they didn't trust and didn't understand the process' (MH2-1) . Institutional Friction Universities and hospitals that house network offices and researchers are called 'host institutions' but their hospitality is largely involuntary. The legal status o f 'networks' is an important factor i n understanding the host /network relationship. Under corporate law, collectives (e.g. societies or associations) ho ld certain 'powers o f association' not available to members as individuals. Those powers are exercised through the association's officers, professional staff, and governance mechanisms. Legal powers o f association, and legal personhood, require incorporat ion and C G D N did not incorporate unt i l 1998. U n t i l then, i n legal terms, it d id not exist. 8 4 A s a C G D N manager says, 'these are very fragile organizations; they're built o n practically not i i ing. There is very little holding them together except money' (PS-CS-66). U n t i l 1998, then, C G D N was an 'ephemeral organization' (Lanzara 1983:88) existing only i n the interstices o f university accounting systems. Its status i n relation to the university was highly ambiguous. Comment ing o n the network's location o n the periphery, Michae l Hayden says 'we were federal but we weren't i n the mainstream. It was strange' ( M H ) . Bu t from the margins, as 'federal agents', N C E s 8 4 This is one reason Industry Canada, in early planning for the program, wanted to insist on incorporation. As described earlier, the Research Councils resisted 112 were able to mobi l ize significant informal powers o f association. In the absence o f formal identity, they bound C G D N together wi th a willed identity. When you are a network, when you're not incorporated, when you're undefined, when you're an instrument of the university, (the universities consider you their instrument even though you are not.) And when you're trying to do something in between everybody else, it's very difficult to establish an identity. And we worked hard to create an identity. (Senior Executive, PS-DS-64-65) A s the networks developed distinct identities two clear sources o f friction wi th host institutions emerged. The first source o f friction was the financial costs o f hosting networks. Un l ike the Nat iona l Institutes o f Heal th i n the Uni ted States, Canada has never funded infrastructure costs 8 5 for medical research and only rarely allows researchers to charge their salaries to research grants. Whenever a new program was established, universities had to cover the additional costs. B y any standard, N C E overheads were large and expensive for university budgets to absorb. In effect, these institutions supplied the incubation facilities i n wh ich networks could flourish, but received no compensation f rom the program, or recognition for their contribution. A s wel l , it was a case o f 'taxation without representation' since universities had no power to regulate the activities o f networks, wh ich were accountable only to Ottawa. Overa l l public investment i n the program from fiscal 1990 to fiscal 2000 exceeded $650 mi l l ion (see Table 3). B u t this figure does not include university infrastructure or the salaries and benefits o f university researchers. The N C E Directorate conservatively estimated the latter at approximately $100 mi l l ion a year i n 1996 ( N C E A n n u a l Report , 1996-97). U s i n g the growth o f the program since 1996 as a base for calculation, the annual salary figure has likely doubled to approximately $200 mi l l ion a year i n 2001. A c c o r d i n g to one federal informant, by absorbing these costs universities have contributed at least as m u c h as the program itself over the years ( N C E - S M : 19). 8 5 Effective July 2001, a white paper was circulating in Ottawa proposing to allocate a standard percentage of research funding to universities for infrastructure 113 Acknowledg ing the historical under-reporting o f public support for the program, the Direc tor o f the N C E program estimated that 'the additional contributions from both the granting counci l s 8 6 . . . and the universities tends to almost triple the total amount ' (JCG-11). In contrast, the private-sector is credited wi th only $75 mi l l ion , or approximately 10% o f the program's 'official ' $730 mi l l ion cash budget. E v e n this figure may be overstated due to various reporting anomalies regarding cash contributions that w i l l be discussed later. T h e same anomalies prevent any reliable estimate o f ' in -k ind ' contributions from industry partners. Wi thou t full estimates o f cost, it is hard to calculate the program's cost/benefit ratio. Table 3: Total cash contributions to NCEs, 1990-2000, in C$M (excludes in-kind gifts and overhead support) Agency C$ % NCE Grants 509.5 69.9% Federal Agencies 27.3 3.7% Administration/sundry 14.2 1.9% Sub-total-Federal 551.0 75.6% Provincial Agencies 45.8 6.3% Subtotal-Government 596.8 81.9% Universities (direct only) 8.5 1.2% Other—hospitals and tax-exempt foundations 48.4 6.6% Sub-total-public supported institutes 653.7 89.7% Industry contributions 75.0 10.3% Total Cash 728.7 100.0% Source: compiled from N C E annual reports, 1990-2000 Perhaps understandably, universities resented their expensive and uncontrollable guests and did what they could assert their institutional authority. A c c o r d i n g to one C G D N informant, the initial reaction was 'the government has forced these damned networks o n us. . .why should we even talk Comprising prior funding of fundamental research by the research councils, in the form of grants to network researchers for the basic element of 114 to these network guys? Wha t do they br ing to the table?' (senior researcher; RW-35) . O n e way for universities to manage the intruders was through bureaucratic controls. A s already stated, prior to incorporation C G D N had no legal capacity to hire employees, make contracts, or receive funds. In all such arrangements the host university acted as surrogate, as i f the network were a minor chi ld , incapable o f forming intent. C G D N ' s researchers were employed by their individual hospitals and universities; network staff worked for U B C . W h e n C G D N wanted to hire D a v i d Shindler as Managing Di rec tor i n 1990, U B C refused. Michae l Hayden recalls He was the guy we wanted [but] the only way to hire him was not to hire him but to get him to take a secondment from his current job. We would pay the Ministry of Foreign Affairs and they would pay him. We did that for five years. It took UBC that long to approve the appointment... [to] become more trusting of the networks (MH-2) The universities wanted the networks brought under university control . A s one network manager describes the situation, 'this was about power and greed. They wanted control o f our budget. They wanted the ability to claim that the networks came under the universities, so that anything the networks accomplished, could be attributed to the universities. It's more money for them, it's more profile for them. It's a case o f the bigger our basket is, the more of a power base we have1 (PS-CS-31). C G D N ' s principals resisted the administrative blocks imposed by the university. Whi l e acknowledging that university budgets were inadequate, they saw no reason to accept the blame and pointed to waste and inefficiencies that 'leaner' structures like networks avoid. 'Universities are under funded, but they are over-headed', says one founding member. 'There is too much infrastructure. T o lay blame onto the networks for some aspect o f it is unfortunate and misplaced' (RG-83) . O n the contrary, he suggests, universities should recognize the networks as assets. their network research. 115 A second cause o f friction between host universities and networks relates to the management o f intellectual property (IP) generated by network researchers. B o t h are involved i n what Merges (1996) has described as a process o f 'creeping propertization' as discoveries that w o u l d otherwise have remained i n the public domain, are 'captured' (privatized) as intellectual property then exploited for profit. In this drive to propertize the products o f science, N C E s and their host universities compete for profits. E a c h seeks to depict itself as the most legitimate agent and skilled representative i n the drive to turn science towards the market. Beyond the drive for profit he several distinct irritants. First, the 'internal agreements' 8 7 that are supposed to govern intellectual property issues are universally described as 'ugly. ' T h e program directorate is trying to set up a template to simplify these complex and unmanageable documents. In the meantime, the agreements are supposed to clarify relationships and IP ownership issues but they do not. This means that each commercialization deal must be treated o n a 'one-off,' case by case basis. Second, over time networks have become more aggressive about intellectual property. A s I describe i n some detail later, the networks had fairly l imited interest during Phase I because program demands i n this regard were modest. Phase II brought increased expectations o n the part o f the program and a matching response from the networks. Since Phase III, the networks have been looking to IP commercialization to carry them beyond sunset o f N C E funding. A s one university technology manager comments, 'the networks are really fighting for our intellectual property.. .the reality is that i f they're going to be self-sustaining, they have to insert themselves into the process' ( U A - S C - 1 ) . Ano the r says, '[these] people are trying to protect their future at our expense' ( U B C - C B - 2). 8 7 The NCE Directorate requires such agreements. They govern all aspects of the relationships between a network and its university and industry partners 116 Finally, there is a sectoral disparity among the networks i n their ability to deliver commercialization services, and i n their approach to technology transfer. A c c o r d i n g to university technology managers, the information technologies and electronics networks tend to be 'fairly hands o f f and laissez faire', while the life sciences networks like C G D N tend to be proprietary and centralized. Because life science networks control their boundaries and members, they been able to make themselves 'obligatory passage points ' (Callon 1986: 205) for I P protection i n a way that university commercialization offices have not. 8 8 In networks, the processes o f interessement and translation ensure that discoveries w i th commercia l potential are disclosed to the network first. Industry Lia i son Offices (ILOs) i n universities argue that N C E s duplicate existing technology transfer infrastructure and add litde value i n the process. In turn, the networks point out that historically universities had no incentive to pursue commercialization nor any particular interest i n do ing so. O n e o f the dr iv ing forces behind the establishment o f the N C E program, they say, was to 'leach out' technologies otherwise langviishing i n universities. Universi ty technology managers argue that they carry most o f the workload for the development o f N C E technologies while receiving litde credit. ' O n any technologies that I've been dealing wi th N C E s , I w o u l d say I've done 80% o f the stick handling' ( U B C - C B - 2 ) . Bu t to a C G D N board member (private sector) university I L O s 'appeared to be uniformly inept or nonexistent or both. The networks were m u c h more competent ' (B-MP-6) . In comparison to 'Johnny-come-lately' narrowly focused networks, I L O s depict themselves as deeply experienced and possessing a 'whole university' vis ion. In contrast, networks hold themselves out as fast-moving, sectoral specialists, mov ing strategically to secure IP. They depict I L O s as lumbering, bureaucracy-bound generalists, wi th no industry experience, trying to handle everything See Nelson & Sampat (2001) and Atkinson-Grosjean & Fisher (1999) for more thorough discussions of institutional constraints on ILOs 117 from astrophysics to zoology. A c c o r d i n g to a former C G D N commercia l director, I L O staff just don't develop a g o o d understanding o f h o w industry thinks, so they don't really understand h o w to find market prospects. 'They mean wel l , and they try hard and they work hard. They often are extremely over-worked for what they get paid. But , you know, we were focused o n our o w n field. A n d that meant we could specialize' (PS-MarglVl-13). Hero ic tales are told about the relative competence and ineptitude o f the network and I L O s . These myths have entered the collective unconscious and seem to be part o f the enculturation process. A classic example is C G D N ' s Alzheimer ' s Genes Legend, wh ich was repeated to me, i n various forms, by board members, researchers, and professional staff. The discovery o f two genes for early-onset Alzheimer 's disease was a b ig find. The university was not \vi l l ing to move fast enough o n protecting the technology so the network took the lead, realizing that ' i f we didn' t patent it—yesterday!—we'd lose it ' (Network Manager; PS-CS-45) . The legend describes h o w the heroic managing director got the genes patented wi th in 48 hours, therefore protecting the technology for Canada. A s recounted by the network's associate scientific director, the authorized version goes as follows: This was well into the N C E process, by now we're talking about Phase II and we're into about the winter of 1995. The researcher called me one day and said 'you know, we've got the Alzheimer's gene finally. I've gone to the university and they don't think that it's worth patenting. They don't think that it's worth anything. They don't want to follow-up on it. What should I do? Do you think the network would be interested in helping me to patent it?' So I called the network's managing director in Vancouver five minutes later and said 'you've got to call this guy and talk to him about the patenting. The university is going to be convinced that they need to be involved in the end, but would you take a lead role here and at least make sure that he doesn't go out and publish the stuff before it gets patented?' 118 And the managing director said he would do something. That was like 5:00 in the afternoon. Ten o'clock the next morning, he phones me back. He is in Toronto, walking down University Avenue, talking to me on his cell phone. He'd flown in on the red-eye overnight, set-up a meeting with the researcher for that morning, and by mid-afternoon, they were well on their way to developing the patent position and talking about the whole strategy for exploiting this intellectual property. And of course, as soon as he got involved, the university realized that there really was something there that they should be involved in. And in the end, it worked out well for everybody. But, I think that was the first time I had seen the network really play a catalytic role in making something happen. (RW-37) Ultimately, this initiative resulted i n what was, at the time, the largest IP deal i n Canadian university history, between Schering Canada Inc. and the Universi ty o f Toron to i n 1997. Schering's initial $ 9 M funded a three-year research program i n the development o f drugs and technologies to treat and prevent Alzheimer ' s . O v e r the long-term, the agreement has a potential value o f $34 .5M, not including royalties. Despite the sniping about the relative levels o f commercial competence, network researchers work not i n 'networks' but i n universities and hospitals wh ich pay their salaries, provide their lab space, and pay their overhead and operating costs. Resulting technologies are owned by the institutions. Thei r ownership o f IP is 'cast i n stone' and they are not about to cede their interests to the networks. Thus networks and universities have to work together or nobody benefits. In game theory terms, it is a classic prisoner's dilemma. O v e r time, both have made concessions and a truce o f sorts has been worked out. Whi le the chapter so far has described h o w the network configured a structure and took o n an institutional identity, the telling has failed to capture several critical areas. The report o f C G D N ' s configuration is shot through wi th power relations and exclusionary criteria. These can best be understood as issues relating to the network's spatial-structural dynamics: the larger 'why' questions o f regional distribution, elitism and equity, social reflexivity, and fiscal accountability. 119 III. Spatial-Structural Dynamics Regional Distribution A s befits a federal program, success i n fostering wide national distribution o f networks and resources is a policy concern. However , the experience o f C G D N shows this goal may not be realistic. W h e n the program was being planned, the 'network' component appealed to politicians because it offset the elit ism impl ied by 'excellence'. T o a Canadian poli t ician, elit ism means geographical concentration. The program was sold to Cabinet 'as an economic development package—a regional economic package. B u t Cabinet was sold 'a b i l l o f goods' (federal informant, N C E - S S - 2 ) . Despite rhetorical claims o f national scope, and significant expansion i n Phase III, C G D N ' s main clusters are still at the three original institutions: Vancouver 's Universi ty o f Br i t i sh Columbia , the University o f Toronto ' s Hospi ta l for Sick Chi ldren , and M c G i l l Universi ty i n Montreal . A n examination o f research and core facility funding allocated to network P i s shows that these three institutions commanded more than 7 0 % o f the network's $33.5 M research budget i n the period from 1991 to 2000 inclusive (see Table 4 below). L o o k i n g at the provincial distribution o f network funding i n the same period, P i s i n Bri t ish Co lumbia received 22%, those i n Ontar io got 43%, while researchers i n Quebec received 27%. The remaining 8% was allocated across all other provinces. Table 4: Funding Allocations by Institution, 1991 to 2000 Totals 1991-00 % University of British Columbia 7,076,592 21.1% Vancouver, BC Hospital for Sick Children (University of 9,486,464 28.3% Toronto), Toronto, ON McGill University 7,343,483 21.9% Montreal, PQ All Others 9,590,292 28.6% 33,496,831 100.0% Source: Compiled from CGDN financial records 120 These figures indicate that the network is tri-nodal rather than widely distributed. In a sense, the 'network' metaphor is misleading; the dominant image is o f 'spokes and hubs' (see Figure 6 below). A Matthew effect (Merton 1968) is at work, favouring those researchers and locations that are already well-established. Figure 7: Tri-Nodal Distribution of Funding Actor-network theory relates the density o f linkages i n particular areas to the activities o f spokespersons and their success at interessement and enrolment. Th is is certainly the case. The tacit or embodied aspect—the 'spokesperson factor'~can be clearly seen when established researchers relocate to another university. N e w clusters begin to form around them, conf i rming the importance o f face-to-face interactions. W h e n Diane C o x relocated from Sick K i d s to the Universi ty o f Alber ta i n 1996, the university had no network members. N o w three P i s are based i n E d m o n t o n as wel l as several associates. In the same year, R o n W o r t o n moved from Sick K i d s to Ottawa, where B o b Korne luk was the sole representative o f the network. The Universi ty o f Ot tawa n o w represents a significant node and StemNet, the new N C E directed by W o r t o n , w i l l be headquartered there. 121 Finally, Le igh F ie ld was for many years the solitary network researcher at the Universi ty o f Calgary unti l R o y G r a v e l moved there f rom M c G i l l i n 1999, fol lowed by Frank J i r ik i n 2000 8 9 . Other spatial and structural factors must be accounted for as wel l , for example proximity effects and institutional context. A s Wol fe (2000) points out, economic geographers have long emphasized the significance o f space and proximity ('territoriaUzation') i n creating the conditions under wh ich resources and tacit forms o f knowledge are generated and shared. T h e phenomenon o f regional clustering among researchers, institutions, and firms is wel l recognized i n the literature o n industrial districts and regional systems o f innovation. 9 0 A s M u r d o c h (1995:743) notes, 'networks are differentially embedded i n particular places and. . .different forms o f organization evolve i n different sociocultural contexts.' I suggest that something similar is occurring wi th C G D N . The combinat ion o f inertia and proximi ty means i t is easier to bui ld linkages wi th researchers i n the same or nearby institutions than wi th those at a distance. The institutional context is another key factor i n faciktating clustering. Aga in , the Mat thew effect is at work. O n e institution begets more. They layer together to create a regional system for the product ion and exploitation o f knowledge. A m i n & Thrif t (1994) call this ' institutional thickness'. The network's To ron to node is a good example, wi th six hospitals and the main university campus wi thin steps o f each other. Bu t an internal 'thickness' is also important. K l e i n m a n (1998) has shown that laboratory practices are shaped by the university's formal structure and context. This context defines the 'rules o f the game'; for example, h o w university resources are allocated and who can command them. Some institutions focus more power than others and can assign more resources to particular enterprises, provid ing a hospitable environment for network activities. 8 9 Field relocated to U B C in 2001 9 0 For an authoritative analysis of the former see Lash and Urry (1994); for a Canadian perspective on the latter, see the articles in Holbrook and Wolfe (2000), also Wolfe (2000) in Rubenson & Schuetze (2000) 122 In summary, if C G D N is indicative, the N C E program supports the institutional status quo by directing resources to existing research 'centres' while 'peripheries' remain marginalized. However, the embodied nature of knowledge is such that if smaller universities can find the means to attract network researchers and their programs, these people become agents of change that attract others. Elitism: Norms of Equity and Exclusion The concept of centres and peripheries is closely linked to that of inclusion and exclusion. Both are cultural oppositions, linked to spatial notions of familiar and strange, presence and absence.91 In this section, I examine the norms guiding enrolment to discover why some 'strangers' became present and included in the network while others remained absent and excluded. To the first international peer review committee, who were 'unapologetically elitist', the term excellence meant that 'we should pull together world class teams of scientists: the very best people who, with support, could pull the rest forward' (NCE-SS-1). Roy Gravel recalls that excellence was defined as the top five percent of scientists in a field, worldwide. Gravel considered that an odd and arrogant statement, Taecause science doesn't work that way. That wouldn't be the way you would identify the cream of Canadian science. And that wasn't a Canadian number.. .so it had no meaning' (RG-8). Nevertheless, given the 'excellence' requirement, the biggest challenge in putting the proposal together was choosing the people. The core-set had to ensure program requirements (for example, geographic distribution) were satisfied, while covering the domains of science that interested them—human genetics, medical genetics; and key technologies. But the program's preference for Mode-2-type interdisciplinarity was An expanded analysis of these concepts can be found in Rob Shields'( 1992) examination of Simmel's (1950) notion of 'the stranger' 123 largely ignored. Ear ly i n the planning, they decided 'that this w o u l d be a network o f molecular geneticists. A n d so anybody w h o was doing cybergenetics, or b iochemical genetics or any other type o f generics were automatically excluded i n order to keep it focused' (RW-19). Th is network would operate almost entirely wi th in traditional disciplinary bounds. Beyond that, a degree o f arbitrariness, capriciousness, surrounded debates about w h o the core-set d id and d id not want to work with. Perhaps this was inevitable given the need to select only a couple o f dozen people f rom across the country. However , i n designating a handful o f people as superior scientists, 'excellent' enough to be i n the network, they left an implicat ion that those excluded were somehow inferior. T h e process left a legacy o f ill-feeling. L a p Chee T s u i still regrets the elitist direction. ' In retrospect,' he says, 'I think we should have included everyone. T h e whole community is very small, and i n the end about 7 5 % became a part o f the network. So there was a small number o f people w h o d id not get in . I just felt it wasn't really necessary to go through the agony when the numbers were so small ' ( L C T ) . A s R o n W o r t o n describes the process, The biggest challenge was not in determining who we should choose, but who we should not choose. We made that determination with difficulty, and somewhat arbitrarily. There were some pretty good scientists in the country that we excluded.. ..For whatever reason. Maybe we felt their publication rate wasn't high enough, or they weren't well enough known, or we didn't like the way they did their science, so we excluded them. And in the early days I got phone calls from some of my friends who said 'I'm really angry that you guys did not include me in the network. Why did you not include me?' And when you're asked a question like that, it's almost impossible to answer. It's about standards and focus really. RW-20 The network is a k ind o f elite club, where membership is increased by invitat ion only. The inner circle—the priorities and planning committee—'sits around the table.. .and throws names o n the table and discusses them' (RW-20). Often, names are put forward by other members, but even wi th those bona fides not all are selected to come in . Few outside the inner circle understand the selection process. W o r t o n says merely that they try to identify people whose research looks really interesting and is complementary to the existing research program. 124 O n e member, a junior researcher back i n 1988, thought the decision to include h i m in the network was circumstantial. H e had trained at Sick K i d s under R o y Grave l and was located i n Ottawa, wh ich gave the network an opportunity to add a node beyond the Vancouver , Montrea l , To ron to triangle. H e says, 'they tried to cover all possible aspects. Scientists i n different parts o f the country. Scientists that were young and scientists wi th a lot o f experience. So when they went d o w n the list, I guess I ended up [included]' (RK-2) . H e recalls that M i k e Hayden used to joke that they needed at least one person i n Ottawa to deliver the funding proposals. F o r a similar reason—to get wider geographical representation—Hayden contacted a researcher at the Universi ty o f Mani toba who wou ld represent genetics researchers i n the prairies. Another , at the University o f Calgary, self-selected: T heard they were doing this and I wrote them a letter, I guess it was to M i k e Hayden, and said I 'd like to be part o f it. A n d he said "we l l send me your C V " and I d id and they invited me i n ' (LF-2) . O n e person from the group at Toronto ' s Sick K i d s remembers 'it was initially extremely exclusive. A n d then it widened out a little bit to include those people who had a particularly h igh ranking i n M R C and I was one o f those' (DC-9) . In a recent Nature op in ion piece, a molecular biologist and a zoologist argued that the life sciences are i n danger o f losing their originaUty (Lawrence and L o c k e 1997). The authors perceived an homogenizat ion o f op in ion , wi th fewer independent schools o f scientists finding novel approaches to problem solving. Scientists are 'playing safe' by fol lowing established lines o f inquiry, rather than taking intellectual risks. The authors believe this situation is perpetuated, i n part, by the dominance o f 'star' scientists at conferences and i n the literature, and i n the inherent conservatism o f the peer review process. In other words, as argued i n Chapter 4, by l imit ing selection to elite scientists, these networks tend to l imit the variety that feeds more risky innovation-led research. 125 Another anomaly relates to gender. W o m e n P i s say that the role o f female scientists i n the network has always been equivocal. 9 2 O n l y five o f the original twenty-one members were women , and all the original P i s were men. O f the total research and core facility funding allocated in the period 1991 through 2000, w o m e n researchers received 11 percent rather than a proport ional 24 percent. The two founder members w h o were not renewed, i n 1996, were both women . A s one o f the five female founders points out, 'some very senior w o m e n scientists were not i n the network, at all. They were not invi ted ' (DC-38) . T h e propor t ion o f w o m e n has increased slighdy over the years. In the Phase III proposal, submitted i n 1997, eight were listed as members. In 2001, one o f three new P i s was a woman as wel l as three o f five new junior researchers called 'network scholars'. A l l five w o m e n founders were interviewed and all made some reference to gender issues. Mosdy , they saw the problem as systemic rather than specific to the network but expressed a degree o f exasperation at the general lack o f concern shown by the network's male core set. M o r e than a frustration wi th gross numbers was the fact that w o m e n were not represented i n the power positions. A s one says It was very strongly male dominated. And we [women] have had little involvement in [running] the organization. I'm not even sure that [the men] notice, particularly. The women used to joke about it. But there's a problem that way in our field, in Canada, in general. There's a core of people who are very supportive of each other, in and out of the network. And it's very difficult because you're not a Tauddy' of the guys. I'm not suggesting it is a major complaint or anything, but it's simply a fact. I think it's better now for the younger investigators in the network.. .but the senior women are scarce. D C 38-40 The network made no serious effort to attract females, says another, 'even though there is a lower percentage o f w o m e n i n the network than is generally the case i n human genetics i n N o r t h Amer ica . ' (LF-32). A recent report by the Nat iona l Science Foundat ion tends to support this assertion: unlike i n the physical sciences, about half the doctorates i n biology are awarded to women . E v e n i n the 9 2 Knorr-Cetins (1999) found the same in her ethnography of a molecular biology lab. 1 2 6 1980s, one i n three biology doctorates was awarded to a woman. 9 3 Th is researcher also finds it curious that all o f the individuals dropped from the network have been women. O n e o f those former P i s explains that it is simply much harder for a woman to succeed i n medicine and science. 'The nature o f the [science] system is that it's run by men. If w o m e n ran the system it would be very different. So there is no question there is a sexist component to it. It is just because men make the rules' ( C G 15). T h e w o m e n find the elitist ' invitation only ' approach particularly troubling, and compla in o f a lack o f transparency i n the selection process. They can find no logical explanation for w h o is ' i n ' and who is 'out' o f either gender. Names have been proposed, but to little effect. T don't exactly k n o w what happened to those suggestions, but apparently they were looked at by the [leaders] w h o decided not to invite them' (LF-3) . Exc lud ing people placed a question mark over their career, especially as the network grew i n academic prestige. 'People began to wonder . . .why didn't they invite me, y o u know? It's the coalit ion o f top geneticists i n Canada, we l l why haven't they invited me?' (woman manager, PS-CS-81) . W h e n the network was starting out, ' i f you were left out, it didn't matter too much . B u t . . .the bigger the network got, the worse it was to be left out ' (woman P I , D C 5 0 ) . Certainly several wel l -known Canadian geneticists have been excluded. O n e says 'it gave the impression [then], and probably still does today, o f being a k ind o f an elitist club, and one i n wh ich I didn't b e l o n g ' ( C G - 1 3 ) . W i t h the exception o f Lap-Chee T s u i visible minorities are also notable by their absence. The network's board, its scientific and professional leadership, and principal investigators are uniformly white. Whether or not this reflects the field o f medical genetics as a whole , the homogeneity o f race and gender perhaps indicates a profound social, i f not scientific, conservatism at the heart o f this reported in Chronicle of Higher Education, 23.02.01 127 network. This conservatism is also reflected i n the absence o f social reflexivity and public accountability. Accountability as Social Reflexivity A c c o r d i n g to G i b b o n s et al. (1994), one o f the defining elements o f new network forms o f organization is their social reflexivity. Rather than being accountable to the communi ty o f science, these networks are accountable to the communi ty at large. It is a pluralist framework, where the pushes and pulls o f the agendas o f relevant social actors condi t ion the decisions and policies that emerge. Thus , argue G i b b o n s and colleagues, public interest groups, lawyers, social scientists, as wel l as natural scientists, have a voice i n the governance o f M o d e 2 networks and, more controversially, i n the composi t ion o f research teams. This broad representation is deemed essential because o f the risks and issues inherent i n contemporary science and technology. Similarly, Ca l lon (1999) has noted the emergence o f 'knowledge co-product ion ' models i n wh ich patient groups establish themselves as 'partner associations' wi th research groups, and establish parity between lay and expert knowledges o f the disease process. Bruno Latour also emphasizes the social accountability and reflexivity o f 'new' network formations. H e argues that i n a culture o f 'open science', where autonomy is sacrosanct, there is no direct connection between scientific results and the larger societal context. B u t i n the type o f culture Ca l lon describes as 'overf lowing networks' there is a new deal w i th society—a type o f collective experiment i n w h i c h science and society are mutually entangled for mutual benefit. H e concludes that 'scientists n o w have the choice o f mamtaining a 1 9 t h century ideal o f science or elaborating— with all o f us—an ideal o f research better adjusted to the collective experiment on which we are all embarked' (1998:209). 128 Recently, N o w o t n y , Scott and G i b b o n s (2001: 258-9) extended the reflexive elements o f their original Mode-2 formulation even further, arguing that scientific knowledge must be 'socially robust' as we l l as conventionally 'reliable'. Whereas reliable knowledge has traditionally been produced i n cohesive and restricted scientific communities (Mode-1), social robustness depends o n 'sprawling socio-scientific constituencies wi th open frontiers' (Mode-2). Socially robust knowledge is superior to reliable knowledge, they argue, first, because it has been tested and retested i n contexts o f application and, second, because it is the 'underdetermined' outcome o f 'intensive (and continuous) interaction between results and their interpretation, people and environments, applications and implications ' (258). The more open and 'comprehensive' the knowledge community , the more socially robust the knowledge produced. Further, public contestation, controversy and conflict.. .are not to be shunned on grounds of principle. Rather, they are a sign of a healthy body politic and part of the process of democratization.. .Space has to be made for what people want, what their needs are, and.. .even contradictory responses and claims (258) T o the extent that the N C E program was apparendy seeking to create the type o f networks envisioned by Gibbons , 9 4 Ca l lon , and Latour, presumably wi th a broad understanding o f public accountability, Michae l Hayden's not ion o f civic science seems impoverished. A s I rwin (2001) has shown, the construction o f the scientific citizen is a far more complex process than Hayden suggests. F o r Hayden, the sub-text seems to be that the public (non-scientists) are useful when mobi l ized en masse but must otherwise be kept at arm's length, lest their ignorance and /o r interests impede the research enterprise. Th is is a classic example o f science/non-science boundary work (Gieryn 1995). A s Wynne (1999) points out, the lay public is often assumed to lack the 'epistemic capacity' required to judge science. O n e o f the network's board members commented, for example, that 'the public is 9 4 Again, note the advisory connection between the NCE program and Gibbons and, to a lesser extent, Callon 129 generally quite ignorant o n the subject o f genetics. I don't say that wi th any negative sort o f connotations. It is just a fact o f the matter. W h y wou ld they not be ignorant? It is a very complex science' ( B - M M - 1 4 ) . Because o f their ignorance o f the science, it is assumed the public has nothing to contribute to the network, despite the ethical issues and broad social questions that accompany research i n medical genetics. 9 5 A t the same time, the network states 'no satisfactory policies w i l l emerge i f public concerns about genetics i n health care are not addressed, and i f those concerns are not fully and objectively researched' (website; July 2001). Similar attitudes were found i n a study o f medical geneticists by K e r r and colleagues. 9 6 The study showed that these scientists view science as a 'gold standard' that clearly demarcates 'good and value free research f rom il logical or politically distorted opin ion , wh ich they paternally attribute to an undifferentiated lay publ ic ' (Glasner 2000:11). M o r e troubling, i n giving apparendy objective assessments o f risks associated wi th the new genetics, the experts i n this study 'simultaneously disguis[ed] the extent o f their o w n social location and vested interests' (ibid.). The demarcation o f lay and expert knowledge and interests can be clearly discerned i n the fol lowing remarks made by a senior network manager (a science P h D ) i n response to a question about the potential for appointing a lay member to the board. I mean what would a lay [board] member do? They would just ask us what we were doing. Well we can't explain that. We don't have time. So we try to pick intelligent members who at least understand the field a little bit. Public interest science is just politics. I want to tell you that right now! That's politics and I don't want politics in my network. If somebody has an agenda about organic foods or genetic engineering, I'm not interested. What I am interested in is: are we curing disease? Are we solving a social problem? We're just as capable of looking at the risks and balances as anybody else. But in the end, would you rather have a cure for Alzheimer's or not? Which is better? A n d people agree that, in the end, finding the cure for Alzheimer's is certainly a greater social good than being in favour or against clinical trials, or animal rights, or whatever. 9 5 For example, the goal of integrating genetic therapy into the health care system is to predict and prevent disease; predictive capacity requires population-wide genetic testing and stratification based on genetic variants, an issue that carries significant social "baggage' in the form of eugenics. 9 6 Kerr, et al. 1997 reported in Glasner (2000:11) 130 The fact is that it would have been very disruptive to have grandstanding on the network board. Of any kind. The interests of the organization have to be paramount, not the individual agendas of board members. And if you have a board that has a bunch of people with individual agendas on it—public agendas, private agendas, political agendas—then you are going to have a dysfunctional board and a dysfunctional organization. You are going to lose that cohesiveness that is so important. You're not going to be able to function. Because they are going to block you and then you're not going to be able to carry out your program., So we had federal program officers on the board; we had foundations, we had industry, we had universities, we had intelligent people—medical people, physicians—that were thinking about all of these things. PS-DS-54-6 Apar t f rom the evident paternalism, this network appears compelled to equate the public 's legitimate interest i n the conduct o f the biosciences wi th anti-science or fringe activities. The reaction is exaggerated: i f the public is given a voice, rationality w i l l be lost; when scientific problems arise, we must 'trust the experts' to solve them. Br ian Wynne (1999) calls this approach to problem-solving 'deterrriinistic uncertainty', i.e. when problems caused by science are deemed reducible only by the application o f more science. Categories o f 'lay' and 'expert' are mtrinsically problematic and socially constructed." Scientific discourses exert normative influence over the public domain and attempt to 'reshape the wor ld i n their image'. Wynne (1999) calls it 'a profoundly unaccountable and unreflexive process'. Recent work i n the public understanding o f science (PUS) shows that exclusionary discourse underpins much o f the public 's mistrust o f scientific expertise. Barnes and Edge (1982:237) suggest that 'the tragedy o f expertise' is its ultimate contingency. In a high-trust, high-risk area like medical genetics, the absence o f external voices wi th in the network means the absence o f fundamental questioning as to what might be an appropriate place for genetic approaches to illness. A s one prominent critic points out, 'it's a major social hazard that 131 nobody is look ing at those ethical, legal, and social questions wi th in C G D N . Because there is an implici t assumption that all this w i l l be good for us. A n d we need to ask: w i l l it be?' ( O T H B - 2 1 ) . Langdon Winne r (1993), speaking o f the politics o f technological change, has raised these questions i n a wider context. The 'problem o f elitism', according to Winner , is a question o f the way powerful actors and groups skew the agenda ' in ways that favor some social interests while excluding others' (1993:370). The powerful define the rules o f the game and the allocation o f resources. Winner urges those who study the social aspects o f science and technology to ask what about groups that have no voice but that, nevertheless, will be affected by the results of technological change? What of groups that have been suppressed or deliberately excluded? How does one account for potentially important choices that never surface as matters for debate and choice? (369) Thus taking C G D N as an example, claims that networks are more publicly accountable appear insupportable. A l t h o u g h the idea o f a 'new deal' between science and society is appealing, it is not apparent that it works. Far f rom expanding the public sphere, network arrangements can be viewed as contributing to its erosion. In addition to deficiencies i n public accountability, deficiencies i n fiscal accountability also need to be examined. Accountability as 'value for money' The N C E program was conceived under a neoliberal agenda o f public sector reform that was fuelled by a rhetoric o f fiscal accountability. Results- or performance-based approaches tie funded science to key economic and social outcomes. It seems both responsible and logical to account to the public 9 7 For a sample of recent discussions see Epstein 1999; Haraway 1999; Irwin 2001; Yearley 2000 132 for the use o f their funds. Bu t accountability goes beyond use to value. A s k i n g i f money is.'well-spent' involves asking i f it is effectively spent, and i f it could be more effectively spent elsewhere. Put specifically, are programs delivering value for money9'? C a n they demonstrate cost-effectiveness? The p roblem o f ensuring that public programs remain accountable and return value for money can be understood as a 'principal-agent' p rob lem o f delegation and information asymmetry." The state (principal) delegates provis ion o f research that w i l l fuel innovat ion to university scientists (agents) who are induced by incentives (research funding) to comply wi th the regime o f Strategic Science. But especially i n technical areas, agents always k n o w more about delegated tasks than principals. This asymmetry o f information makes it difficult for the state to reassure itself o f the integrity and productivity o f the scientists they are funding (Guston 2000b:33). O n e solution w o u l d be to regulate research performance direcdy, but that means state control . The neoliberal preference is for refined forms o f 'remote control ' or steering that induce internaHzation o f the state's expectations. Through these mechanisms o f governmentality (Foucault 1978), 1 0 0 'normalized' subjects come to control themselves according to previously established understandings o f what constitutes 'the n o r m ' (Hacking 1990). Governmental i ty requires fidelity devices that w i l l measure and induce compliance, and provide 'discursive validation' that agents are doing what principals expect them to. Largely, these devices are accounting tools: budgets, cost/benefit analyses, ratios and comparisons, statistics, financial and compliance audits. 1 0 1 Accoun t ing tools are far from unproblematic. Whi l e appearing impartial, they 'Value for money', or 'comprehensive' audits are fundamental to NPM (Power 1995) and have now been adopted -at least in principle—by all federal and provincial auditors general 9 9 For a fuller elucidation see David Guston'srecent work, e.g. 1999, 2000a, 2000b 1 0 0 The pos-Foucauldain governmentality literature is extensive, but see, for example, Burchell et al, 1991; Barry et al, 1996; Power 1995, E r i c s o n & Haggery 1997 1 0 1 For more on accounting's 'calculative practices' and 'rituals of verification' see Power 1995; Porter 1995; Miller 1994 133 selectively 'construct the wor ld ' f rom a complex web o f social and economic considerations and negotiations. T h r o u g h its surveillance and control capacities, and its ability to determine financial norms, accounting has the power to create a new 'factual' visibility and discipline performance (Hoskin & Macve 1993; Harris 1998:137). Embedded layers o f accounting and accountability induce the required compliance. These types o f reporting relationships govern relations between the N C E program (principal) and C G D N ' s administrators (agent); and between C G D N administrators (principal) and network scientists (agent). The network's head office thus acts as an intermediary that helps assure state-principals that scientist-agents are fol lowing the policy agenda. 1 0 2 It becomes a 'centre o f calculation' (Latour 1987) for the accumulations o f facts to send to Ottawa. Fo l lowing this logic, reported data gather 'positive modalities' and become harder to resist as they move away from their conditions o f product ion (the lab) to the network office (the centre) and then to the program directorate i n Ottawa ('centre o f centres'). A t each stage data are recombined and reinscribed. The N C E directorate seeks to control the network by specifying what 'makes up ' the numbers (Hacking 1990). B u t network administrators reinterpret the directions i n instructing scientists what information is to be supplied. T o illustrate, C G D N w o u l d report as network accomplishments almost everything their (university- and hospital-funded) researchers achieved, f rom scientific breakthroughs, to publications, external grant funding, and the raising o f venture capital by researchers i n network spin-offs. This over- reporting was so prevalent that many o f the 'official ' network statistics I consulted proved unreliable for the purposes o f this study, because they failed to conform to the guidelines set d o w n by the N C E Directorate. A serious example is that networks were supposed to report as 'cash contributions' f rom partners, only funding that flows direcdy through network accounts. In many 1 0 2 In an international comparative study, Atkinson-Grosjean & Grosjean (2000) found that the proliferation of such intermediary agencies was a generalized feature of higher-education systems under neoliberalism. 134 cases, C G D N reported funding that went direcdy to network researchers. The network's legitimate interest i n those funds was minimal , but because they flowed to members they were reported to Ottawa as contributions received by the network. A l s o , researchers were asked to report almost all their research activities as network activities, for the annual statistical report. A s one complained, It seems sort of ridiculous, talking about all of these accomplishments, when in fact you know maybe 5% of them were funded by the network. And yet they want to hear about all [of them]. So every year I have the same argument, like: Vhat do you want me to do? Write what my student MF did last year? Because that's all that you funded.' And she says 'oh no, put it all in.' And I say Svell, why should I?' And it's gotten, quite frankly, a little bit ridiculous, given the amount of money we get versus the accountability and justification. I mean what do you do? Write your whole program down and attribute it to the network? .. .1 mean I would say things jokingly like 'I think we should just spend all the money on.. .having great meetings in ski resorts. I'd get more out of it than you pretending to send me money and pay for my student.' RK-65-71 The directorate is not only aware o f reporting anomalies but may have contributed to them. A s shown earlier, for the program as a whole, additional public funding is under-reported while aggregated private sector contr ibut ions—both cash and in-kind—are over-reported. A s early as 1938 the U S Nat iona l Resources Committee called such practices 'w indow dressing' ( G o d i n 2000-3:16). Today, we more often label it 'spin' . The purpose is simply to make results look better than they are, to protect budgetary resources and allocations. The N C E program's first fun-time director was appointed January 2000. H e says that the problem has been brought to his attention and agrees that, 'yes, maybe some better discipline should be fol lowed. . .that's something that we w i l l be look ing at' (JCG-14). In September 2000, the Directorate instituted an audit requirement, meaning networks n o w have to submit externally audited annual reports. Since that directive, C G D N has restructured its administrative staff. Responsibility for financial and statistical reporting has been assigned to a new staff member wi th appropriate quakfications. 135 Summary Discussion This complex chapter has attempted to capture the way C G D N forged an institutional identity and organizational structure under multiple constraints, including: demands for both scientific excellence and commercial relevance under managed conditions; resistance from local host institutions; the traditional structure o f basic research and conservatism o f researchers; and the sheer novelty o f doing something that had never been done before. N o w , after more than a decade has elapsed, C G D N ' s successes are clear. But , equally clearly, some have been achieved at the cost o f consequences perhaps unintended by program architects. The concentration o f resources i n C G D N creates a hegemony. The network defines the field o f medical genetics i n Canada. Non-members are 'othered'. Careers can be affected. Y e t no objective criteria for membership exist. Instead, membership is an ' invitation only ' affair, wi th in the arbitrary remit o f the same elite inner group o f scientists that has controlled the network from the start. Power relations are asymmetrical; they concentrate i n the most powerful actors and i n the centre (s) they control . It is, quite literally, a self-reproducing ' o ld boys ' network. Relatedly, network resources flow to the power centres rather than being distributed to scientists across the country. The consequence o f exclusion and concentration is reduced diversity wi th in the Canadian 'science system'. A s a concomitant, there is no r o o m i n the network for 'lay' representations. The 'public interest' is constructed and defined i n the abstract, wi th in expert discourses that exclude authentic voices o f interested publics. That being the case, and i n the spirit o f 'value-for-money' accounting, we can ask about the extent o f public investment i n the network (as wel l as i n the program more generally) and about the returns o n that investment. In the ten years f rom 1990 to 1999, C G D N ' s six original Pr inc ipa l Investigators received between $1.4 mi l l ion and $1.8 mi l l ion each in network funding, while the 15 other founders 136 received o n average between $800 thousand and $1 mi l l ion . These are modest amounts, o n an average annual basis, but it must be remembered that network funding is incremental funding. Ne twork researchers also receive direct support f rom non-profit disease foundations, research councils, and industry contracts while their home institutions underwrite salary and direct costs. B y the time o f federal exit, i n 2005, C G D N w i l l have received i n excess o f $60 mi l l ion i n direct N C E program funding. This figure does not include provincial and industry contributions, commercial revenues, or university subsidies to network researchers. It is impossible to tease out o f this complex o f funding sources what results are attributable to the network and what w o u l d have happened anyway. The same is true o f the program as a whole where, as already shown, public investment exceeds $650 mi l l ion . In other words, there is no reliable way to determine whether or not C G D N and the N C E program deliver direct Value for money' . Bu t the p rob lem wi th accountability frameworks is that they seek to capture and evaluate only those dimensions that can be quantified, objectified, and made accountable. Non-quantifiable and less tangible practices are literally not taken into account. A t the same time, other elements assume new weight because they can be quantitatively evaluated: quantity (not quality) o f research publications; numbers o f patents held; dollar value o f research contracts. In short, by focusing o n readily quantifiable inputs and outputs we risk neglecting more complex social variables that resist measurement but are, nevertheless, valid outcomes. I am ih inking, i n particular, o f the construction o f intangibles such as 'network culture' and 'network science'. The next chapter examines the way the network forged a scientific culture and community and a scientific legacy. 137 C H A P T E R 5 : C U L T U R E A N D S C I E N C E Forms and practices o f scientific culture and communi ty 1 0 3 were i n place wel l before Robert Boyle convened an 'invisible college' i n O x f o r d and L o n d o n i n the m i d - 1 7 t h century. In the mid-1960s, Derek Price (1963) borrowed and extended Boyle 's metaphor, reminding us that small, informal collectives o f closely interacting scientists are the principal means o f scientific advance. Subsequendy, D iana Crane (1972) defined an 'invisible college' as an informal interpersonal network based o n shared scientific interests, rather than geographic proximity. A s Phi l ip Agre (1999) points out, 'so-called invisible colleges are i n many ways more visible to the researchers than the physical campuses where they organize their places o f work' . The distributed and informal nature o f scientific interaction is also captured i n the term 'communities o f practice' wh ich describes self-organizing, self-selecting groups o f colleagues whose members are informally bound together by their shared expertise (Lave & Wenger 1991). No te the family resemblance wi th the scientific 'thought-collectives' identified by L u d w i k Fleck (1979). These communities, characterized by intellectual interaction and the mutual exchange o f ideas, constitute This section draws in part on Fisher, et al (2001) 138 the 'carriers' o f a field's knowledge and culture. Similarly, Kxiorr-Cet ina (1999) speaks o f the very different 'epistemic cultures' o f molecular biology and high-energy physics. Together wi th actor-network theory these concepts, drawn f rom the wider field o f science studies, w i l l help us understand the development o f a distinctive culture and communi ty i n the Canadian Genetics Diseases N e t w o r k (Part I o f the chapter), and the nature o f what might be termed 'network science' (Part II). I: 'A Nation of Colleagues' The cooperation and collegiality have just been incredible. It's created a nation of colleagues that is totally unbelievable. (Michael Hayden, Scientific Director. MH2-21) A t the end o f its first year o f operation, C G D N listed among its achievements the development o f 'an ethos and c o m m o n understanding o f what it means to be i n a network' ( C G D N - A R 1991: 8). The use o f the term ethos indicates an interesting ambivalence. It draws around the network the cloak o f Mer tonian ideals relating to the normative structure o f science. B u t at the same time it invokes the new ideal o f 'network science' wi th its emergent (counter-) norms such as patents and industry partnerships. T h e rhetorical purpose o f the c la im was to persuade N C E bureaucrats that C G D N took the program's non-scientific requirements seriously. Ano the r claim about network ethos can be found two years later, i n the proposal for the second phase o f funding: 'we have created a nationwide department o f h u m a n molecular genetics' ( C G D N - F P 1993, emphasis original). T h e subtext here is recognition o f Ottawa's intent to change the overall research culture i n Canada, network by network, by overriding university boundaries and autonomy. E v e n i f we are to take the idea o f a 'network ethos' seriously, the claims were premature to say the least. E thos can be understood as a cultural achievement, and the development o f culture takes time. 139 As well, an interesting question can be posed about whether culture can be induced by the imposition of a network model, or the provision of funding. But in examining CGDN's history, we can see that very gradually, and taking on a different tenor in each of the three funding phases, a distinctive ethos or esprit de corps (CGDN-FP 2001) did, in fact, emerge. CGDN's 'induced' epistemic community anchored itself in the production of a discursive space of face-to-face interactions that promoted trust and reduced competition. Inducing Solidarity Although socialized in 'invisible colleges', network researchers were confused about, and initially resisted, the whole concept of 'mandatory networking'. No real agreement suggested what that might be, or how it might be accomplished. The network's professional staff had to invent virtual and face-to-face ways of meeting program requirements. They had to grapple with the complexity of somehow linking together a dozen institutions, two dozen principal investigators, as well as post- doctoral fellows and graduate students. And the reporting requirements meant that networks couldn't just say they were doing networking; they had to prove they were doing it to the N C E directorate. So ways had to be devised of enticing scientists to comply. The method they implemented was to make principal investigators' funding conditional on participation in network activities. Subsequendy, it was hoped, Pis would realize the manifold benefits of voluntary participation. Almost all network researchers interviewed commented on this creative relationship between network funding and network-building. For example, Although the other aspects of the network have been much more important, you wouldn't have pulled the people together without the bait of the funding. We would have said, 'I haven't got time to just go and talk with these people.' But you'll go and talk when you know that if you don't, you won't get your funding. And then you find it is really worth while having talked to them and it is really fun. BG-17 140 The biggest value of the network is not the funds that they give us, but the networking opportunities and the collegiality and so on. Although, I have to say that i f we didn't have funding for our labs in addition, we'd probably say, 'Oh, I'm so busy, I don't think I'll go to the annual meeting. I don't really need to be there.' Whereas, if we're funded by the network, we have an obligation to be there. RW-17 The network funding was not a significant propor t ion o f a network researcher's total budget. O n l y a small component o f their research program wou ld come into the network. Usually the component that w o u l d profit best f rom the collaborative opportunities. Other aspects stayed outside. E v e n i n the early phases, when the network was less extensive, the funding allocated to researchers probably never amounted to m u c h more, o n average, than 15% or 2 0 % o f their research budget. This would have been enough to perhaps support a senior technician or post-doctoral fellow. Pu t another way, 'out o f perhaps 15 to 20 projects i n my lab, maybe two or three were covered by network funding, the rest were covered by other kinds o f funding' (RW-16). Bu t a mora l obligation was attached to the network funding. It got people 'to buy-in to the network concept and become part o f it ' (FJ-21). It helped to overcome the resistance to leaving the lab for yet another meeting. A n d it was this face- to-face aspect that quickly became far more important than the virtual aspects o f networking. The latter soon became taken-for-granted, an enabling technology 1 0 4 to further the personal relationships and communi ty o f practice that was being forged. A s a policy advisor explains, The network mechanism...forced people to get together face to face, because of the funding provided.. .Face-to-face meeting is really important, especially early on. You need a lot of personal interaction to make that networking work. And after that you can do it by e-mail and telephone and fax and all the rest of it, but in the beginning you really have to have the face-to-face communication. ARA- DR-49 The face-to-face communi ty that became the Canadian Genet ic Diseases N e t w o r k began to take shape i n 1991, at the first network meeting. Another enabling technology is the conference call. Board and committees frequently 'meet' by telephone 141 Face to Face Community As the main forum for interactions and exchange, the network's early scientific meetings laid the foundations of network culture and community. Unanimous about the cultural importance of these meetings, scientists considered them one of the main benefits of belonging to the network. The first meeting, held at Whistier, BC, in May 1991, set the format for those that followed. Because of the N C E requirement to dedicate 10% of the budget to networking, full costs of attendance were covered for Principal Investigators and Core Facility Directors. These individuals could, in addition, nominate three members of their teams for full subsidy. For example, students and fellows funded by the network or working on network projects could attend cost-free. In rare cases, a technical support member of the group could be included if their contribution was deemed to constitute fundamental research. In molecular biology, where rewards usually go to lab leaders (Knorr-Cetina 1999), subsidizing conference travel for junior researchers was so unusual as to be unique. Each participant was expected to present and discuss their results, either through a poster (students, fellows) or an overview lecture (Pis). As a result, delegates to the Whisder meeting faced a busy three-day schedule of scientific sessions, workshops, and discussion periods. Approximately 100 participants attended from across Canada mcluding board members, external collaborators, and industry partners, as well as network researchers and special guests. Concurrent workshops debated, among other issues, the topics of 'Industrial Relationships' and 'Search for the Gene'. This routine may seem much the same as any scientific meeting or conference. Scientists get together and give papers as matter of course. But there are significant differences. First, as one of the researchers explains, 'a network provides you with access to a completely different and much broader group of people than you would ordinarily associate with at meetings' (FT-3) Normally, scientific meetings are segregated by narrow research interest. In contrast, network meetings are 142 broad, covering the field o f generics i n Canada. Second, f rom the start, the n o r m was 'full disclosure'. T h e meetings were intended to encourage in-depth discussion o f interesting, early-stage research results, often prior to journal publication. Sensitivity to priority, i f nothing else, wou ld have precluded this level o f frankness i n a 'normal ' scientific meeting. A t the same time, however, even i n these first meetings, a countervailing force emphasized confidentiality. Unless you were a network principal—that is a researcher or partner (industrial or institutional) listed i n the network's Internal Agreement—you were required to sign a confidentiality agreement. Intellectual property rights had to be preserved i n order to fulfill the network's commercial mandate. So those ' ful l and frank' discussions had to take place behind closed doors; participants were advised that discussing results i n a closed forum o f colleagues d id not constitute disclosure for patent purposes.' 0 5 E v e n so, researchers were cautioned to apply 'normal discretion i n disclosure o f scientific data' ( C G D N - A S M 1991). In practice, however, it soon became clear that 'normal discretion' was not required. It is totally different than going to a meeting where you have to be careful what you say because someone will rush off and do your experiment and publish it before you get to it. BG-20 In the network, you're not in competition. And so you can confide and get some valuable feedback from these people, right? It's nice to get up there and maybe brag a bit about the stuff that you've got before it's published. It isn't like you feel T can't say anything because Frank in Vancouver's gonna scoop me' (RK-65) It's one of the strengths of this network that we're all in this together. It's difficult out there. The more that you can discuss things, in confidence, the better. You have to be confident that the person you talk to is not going to spill the beans. The trust relationships and the reliance on individual integrity is very important. PS-SH1-20 Debatable but not tested 143 The third factor that marked these meetings as different was the social cohesion they engendered. Despite all the scientific gravitas, the social aspects remain particularly v i v i d for most people. A s k e d what she recalls about the first meeting, one o f the founders, a distinguished scientist, says, 'we went skiing up o n the glacier all together. It was great' (BG-31) . The second and third meetings, i n M a y 1992 and June 1993 respectively, were held at the Far Hi l l s Inn, V a l M o r i n , P Q . A g a i n , her recollection o f the Quebec meetings is that 'we had afternoons off. W e went h ik ing . . .We d id p l ays - skits and things. A n d we had fun' (BG-31) . Few more effective ways can be found to bui ld trust and loyalty—and the foundations o f future collaborations—than to play together and bui ld personal relationships. When you know somebody personally, because you've met them at these network meetings, then you are much more liable to approach them, to work with them. It increases the potential for collaboration. LF- 42 For me the network has meant a lot of relationships with people that I wouldn't have met otherwise, so I have a whole circle of friends now that I wouldn't have had. That's just on a personal level. FJ-37 I have a strong sense of belonging to the network. What I do is defined within my grant applications. How I feel is defined in my interactions with the network. RG-38 So the network communi ty was about openness and sharing, o n the one hand, and bui lding a sense o f solidarity and belonging, o n the other. Th rough the annual scientific meetings, everyone i n the network knew something about what the rest were do ing and that facilitated a climate for collaboration. A Climate for Collaboration Network scientists became familiar wi th each other's research from hearing presentations on work- in-progress. Th is annual 'overhearing' enabled synergies to happen. A s one researcher explains, 144 'going to the network meeting, it's a very easy, fast way o f getting a survey o f who's doing excellent research i n Canada i n our field. A n d that saves a heck o f a lot o f time for us al l ' M W - 3 0 . Perhaps kstening to somebody talking about a particular gene, a researcher w i l l realize that they have a piece o f the same puzzle. O r perhaps they need to find someone wi th particular skills, to help them wi th a project. In either case, they can make contact, confident that their overture w i l l not be rejected. In other words, to bor row a felicitous phrase from one P I , the network acts 'k ind o f like a blanket purchase order o n collaboration' (BG-19) . The whole game is sitting open on the table and then you can reach in any direction. Anyone who gets a call from another person within the network has a sense of obligation to talk and participate and collaborate... It is like asking your brother or sister for something as opposed to someone with whom you don't really have the same relationship. They can't say 'sorry, I'm too busy.' O r 'sorry, you're competing with me.' BG-19 I know those people well. I've met them many times at network meetings. I've heard them talk. A n d i f there was anything I needed or wanted, I certainly wouldn't hesitate to pick up the phone and expect that I would get a very positive response. DC47 The fostering o f trust and reciprocity o n this scale was a unique experience for network scientists, w h o were more used to a culture o f competi t ion than one o f co-operation. Reducing competi t ion and enhancing the ability o f network scientists to work together constituted an advantage for the entire collective. It should be noted, however, that the absence o f compet i t ion was i n part an artifact o f the selection process. Researchers were chosen for the complementarity o f their programs. N o two teams were work ing o n exactly the same thing. So i n the network, as one P I says, 'we're not i n competi t ion, because we're doing different things. We're tied together wi th the c o m m o n interest, but we are distinct' (MW-42) . 145 Being collegial also included work ing for the c o m m o n good, and trusting communi ty decisions. Through the years o f meetings and network-building, a process o f sedimentation took place. C G D N began to setde into the shape it had claimed at the start—a communi ty o f colleagues, w i th a shared ethos and a c o m m o n understanding o f what it means to be i n a network. O n e researcher comments that, 'as a gtoup o f geneticists we really got to k n o w each other m u c h better than w o u l d have happened otherwise' (LF-13.) Ano the r says that the network created value through 'personal contact, personal motivat ion, driving the science' (RK-61) . O v e r time, members began to identify themselves as network researchers. A l m o s t by accident, they agreed, government had 'got it right' and produced a capacity to do 'national science'. A s Hayden comments, 'it's quite unusual to be led from Ottawa. Bu t this was real leadership' (MH2-2) . F o r T s u i /whether by design or by accident, the federal government somehow had the foresight to create these k ind o f networks. [Now] we are leading the w o r l d ' (LCT-23) . The beneficial effects o f this foresight o n the conduct o f science was noted. Because of the networks, across Canada we are doing science in a manner that I don't think could possibly have happened before.. . A very large piece of the scientific community is [now] involved in promoting collaboration—inter-university and interdisciplinary, not just geographic. That is a very positive thing. RG-78 The network is like a national lab without the consequences—the bureaucracy, the 9 to 5 mentality. Here, it's academic, competitive, but then we get together and we figure we're all part o f this same process. R K - 64 We created research groups that would not have existed otherwise, that spanned the country. O r involved different components of the country where we might not otherwise have encountered each other. These are cross-country collaborative interactions. RG-28 However , the network did not evolve quite the way the program's architects envisioned. They had anticipated large-scale, cross-country collaborations. F o r whatever reason—^institutional logistics, 146 egos, distance—that did not happen. And, despite mutual goodwill, the number of researchers who built one-to-one, bench level collaborations was less than the potential would suggest. We don't interact on a project by project basis as much as was hoped we would. I think we fail a little bit there, just because there is too much to do and no time BG-12 There are some collaborative projects within the network. But, it's not as heavily networked as it could be, I think. FJ-40 I have not been one of the ones who has interacted.. .perhaps as much as some other people. Because I don't really have a collaborative project with anybody in the network.. .it's not because I'm not interested, it simply hasn't been beneficial DC46 Still, by creating; the intellectual and collegial infrastructure described above, the network allowed individuals to formulate different questions and approach their science differendy. So even in the absence of hands-on collaborations, researchers benefited from their interactions in the network. Says one network researcher, 'I don't think we would have done that project in quite the same way if it wasn't for the network' (BR-4). Another confirms that we have changed in the way we ask questions and, therefore, the questions that we answer and what we publish. I know that for me—the kind of science I was doing, the directions I was taking—it's very, very clear that I do things differently than I would have done before RG-80 But because each phase of funding added new researchers, institutions, and industry partners, the capacity for collaboration and the nature of the network community was not static. The orientation changed over time. 147 Phase Transitions W h e n the network was renewed for Phase II, wi th its enhanced emphasis o n commercial results, it meant more industry partners' 0 6 and more emphasis on commercial potential at the annual meetings. Y e t the overall ethos stayed much the same. Largely, this was because the core-set remained unchanged and because the expansion had been relatively modest, f rom 21 to 33 researchers, and from 11 to 13 institutions. So the growth was easy to absorb. That was not the case i n the transition from Phase II to Phase III. W i t h the expansion to 50 researchers i n more than 20 institutions, intimacy was almost impossible. A l m o s t all founders felt the culture changed radically at that point and that something important was lost. A s one comments, ' i n the early days I knew everybody and now I don't. That happens when a group gets big enough. It means that we're n o w more o f a conglomerate than a bunch o f guys work ing together' (RG-24) . A comparison between Phase I and Phase III follows i n Figure 8, showing growth i n numbers o f investigators and institutional partners. Details of industry partnerships appear in Chapter 7 148 Figure 8: Growth in Partner Institutions and Principal Investigators Comparing Phase I to Phase III Phase III Phase I PRINCIPAL INVESTIGATORS 50 21 UNIVERSITY PARTNERS -Alberta • X -Calgary y y -Laval • X -Manitoba • y -McGill y -McMaster • X -Montrea y • -Ottawa y -Queens X y -Toronto y y -UBC S y -UVic y X TOTAL UNIVERSITIES 11 8 HOSPITALS & INSTITUTE PARTNERS y -Biotechnology Res. Centre, UBC X -Children's & Women's Hlth Cntre UBC y X -Children's Hosp. East. Ontario, Ottawa y y -Hopital Ste-Justine, Montreal y y -Hdpital Saint Francois d'Assise, Laval y X -London Health Sciences Centre y X -Mount Sinai Hospital, Toronto y X -Hospital for Sick Children, Toronto y y -Montreal Children's Hospital y X -Montreal General Hospital y X -Ottawa Hospital Research Institute y X -Robarts Research Institute, London y X -University Hospital, Vancouver X y TOTAL HOSPITALS & INSTITUTES 11 5 Earlier, I discussed h o w the elite recruitment criteria that were applied i n the first two phases caused a fair amount o f debate. M a n y were uncomfortable wi th the emphasis o n exclusivity. However , the wisdom o f this approach was that it produced a strong and cohesive culture. A s a result, when the approach was reversed i n Phase III, it tended to undermine what had been buil t to that point. O n e o f the founders had spoken strongly i n the past about including all qualified scientists. B u t when that eventually happened, he found the effects disturbing. 149 We had such stringent criteria in the beginning and then, in order to get the Phase III funding, we had to open it up again. Wide open. That was a most difficult decision for me. I was not very happy about opening the thing wide because it was so indiscriminate. Some people were recruited just for their name. They didn't really have any interest in the community . They are part o f the network and as yet I still haven't seen any contribution from these people. LCT-13 Because so many people and institutions were n o w members, mamtaining the same level o f familiarity was impossible. T h e mechanisms o f interaction that worked so wel l i n a relatively small group stalled when numbers grew. People were disappointed that they could no longer get to k n o w each other i n the same way. Fear was expressed that a more corporate, commercial ly oriented style o f doing things wou ld undermine collegiality. E v e n the tenor o f the scientific meetings—the great bmding mechanism o f the past—was affected. The meetings haven't been great. A l l scientific talk; no play. This year's meeting was held in the middle of Vancouver, in a small hotel, where there was nothing that you could do together for fun. A n d it was tied to another huge conference. So everyone had been away from home too long, and were too tired to play together. BG-30 It is immediately obvious when you go to a network meeting, that this is not.. .the style that we have been used to. These are meetings where the commercial aspect of what we work on is stressed. That's probably the biggest thing. A n d then the scientific content comes second. M W - 6 N o t only were the meetings different, the sense o f commitment was different. W h e n researchers were recruited for Phase I and Phase II, it was for the long term. Renewal o f funding was not guaranteed, o f course; competitions were fierce and anxiety o n that score was high. B u t no one sensed a finite hor izon. In those early years, funding could be lost i n only two ways: either the whole N C E experiment w o u l d be cancelled, i n wh ich case all the networks were i n the same situation; or a network wou ld not be renewed because its proposal wou ld be judged inferior to others, and that was the luck o f the draw. N o third contingency, no sunset provis ion, appeared unt i l Phase III. It came as a complete shock and a bitter irony that when the program was made permanent, in 1997, removing fears o f overall cancellation, it was at the cost o f continuity for individual networks. Thus 150 researchers recruited for Phase III came i n knowing that, at best, they w o u l d be wi th this group for a m a x i m u m o f seven years. Together wi th the sheer numbers o f new recruits, the sense o f finitude l imited 'buy-in' . In fact, by this point, several scientists were members o f two or even three networks. So the relationships, and the willingness to trust, were not there i n the same way. This was manifesdy the case i n attitudes to the annual scientific meetings. In the past, attendance had been mandatory, not discretionary. B u t to many o f the Phase III recruits it was 'just another meeting'; they d id not bother to attend. A s one o f the managers complains, 'the m i n i m u m that we ask is that you come to the annual scientific meeting. T h e o ld groups f rom Phase I and II are always there... [but]... there is a m u c h weaker understanding [among the new recruits] o f why they need to be there. Some o f them from the new g ioup just didn't come ' (PS-CS-80). The funding bait was so diluted, because o f the number o f researchers, that it no longer offered sufficient inducement. A s wel l , many o f the associations written i n to the Phase III proposal were strategic. The purpose was to simulate dynamic expansion; actual connections were tenuous at best and i n some cases divisive. F o r example, pr incipal investiagtors had been recruited from M o u n t Sinai Hosp i ta l i n Toron to but historical disagreements marred relations between this team and their neighbours across the street at Sick K i d s . The most recent concerned the administration o f funds for G e n o m e Canada, the new umbrella body for genome research. Genome Canada is very much the legacy of C G D N . And we [Sick Kids] worked very very hard to get the government to do that. And I think it is just a crying shame that we at this institution, the place where most of the genetic diseases work is done, are not being given the job of making sure the money goes to the right places. It is going to go to Mount Sinai. It has been diverted. There is a lot of political stuff that goes on. If Mount Sinai is going to use the money for genetic disease, that would be great. But it sounds like it is going to be diverted to doing all kinds of rubbish that has got nothing to do with genetic disease. BR-53-7 151 In a climate o f tenuous connections and actual rivalry, the authority to compel attendance was lacking. A s a result, enculturation into the network was minimal . A t this late stage o f the network's development, the best way to describe it may be as an 'imagined community. ' Benedict Anderson (1983:1-7) coined this term i n developing a theory o f nationality and 'narion-ness' but it provokes some interesting thoughts when applied to this network as it presendy stands. Ander son proposes to define nationalism as an imagined political community [that is] imagined as both inherently limited and sovereign (5-6). It is imaginedbecause most members w i l l never meet their fellows 'yet i n the minds o f each lives the image o f their commun ion ' (6). A n d e r s o n suggests that all communities are imagined, once they exceed the possibilities o f face-to-face contact achievable i n pr imordia l villages. Wha t distinguishes communities is not their reality, he says, but their style o f being imagined. It is imagined as limitedbecause it has finite, though elastic, boundaries beyond wh ich lie other nations. It is imagined as sovereign because nations dream o f being free. A n d it is imagined as a community because it is conceived as a deep, horizontal comradeship. I suggest these attributes are applicable to the imagined communi ty that is the Canadian Genetic Diseases N e t w o r k today. In this section I have explored the idea o f the network as a communi ty and a culture. In the next, I investigate the type o f science produced by this community. II: Network Science? Grounded i n laboratory practices and commercial motivations, molecular biology is an example o f a 'practical science'. Div is ions between the creation o f knowledge (theory) and its applications (practice) are largely rejected. Mean ing collapses into application, and truth value collapses into use and exchange values. 1 0 7 The focus is converting lab results into profitable new therapies. In this 1 0 7 The phrase 'practical science' was R.G. Collingwood's and these points were made by Evelyn Fox Keller in a lecture at St John's College, UBC, March 2000. For a political economic perspective see Mackenzie, Keating and Cambrosio (1990) 152 section, I w i l l review what happens when individual research programs i n molecular biology (medical genetics) are brought together under the banner o f 'network science'. Science is normally conducted i n a highly competitive environment; individual labs are pitted against each other i n races for resources and priority (Merton 1957). A t the same time, within a laboratory and under the direction o f its leader, people co-operate, share resources and ideas, and publish together. In a sense, C G D N extended the boundaries o f 'the laboratory' to include everyone (and everything) i n the network. 1 0 8 A l l members o f the network were considered colleagues; all had access to the network's technologies. In the long run, this 'extended lab', proved 'more important to the scientific enterprise that a lot o f the rest o f what C G D N does, because this is where the new ideas and approaches that power everything else w i l l be generated' (Expert Panel Report ; C G D N - E P 1997:15). The ethos o f trust and cooperation allowed network researchers to reduce competi t ion. They helped each other wi th scientific problems, reviewed each others' papers, exchanged students, and advised each other at all levels. These tangible and intangible aspects o f belonging made the network a coherent and cohesive entity. It provided an organizational structure, albeit loose, that contributed to the product ion o f first-class science. Bu t whether this science could be described as a distinctive form o f 'network science' is an open question. In m y initial reading for this study, I found i n network and program documents descriptions o f a clearly defined network research program, divided into projects and themes, wi th teams o f researchers work ing together under the direction o f project leaders. I imagined the discussions at the start o f each phase, about what 'we' were going to do next. I imagined scientists work ing together, according to plan, to discover genes and therapies. O n closer examination, as I w i l l explain, the 153 reality o f network science proved elusive. Ne twork science was not where I expected to find it, in the 'network' research program. B u t it was very m u c h i n evidence elsewhere: i n the services provided to members by core facilities and their directors. In order to approach these questions, I first needed to develop an understanding o f the Med ica l Genetics field. Medical Genetics: An Overview The science o f C G D N is medical genetics, the field that studies the relationship between human genetic variation and diseases. Genetic disorders are classified into one o f three types: single gene disorders, chromosome disorders and multifactorial disorders (Prater and Newlands 1999). Single gene defects are caused by mutant genes, usually a single critical error i n the genetic code. M o r e than 4000 single gene disorders have been described. Chromosome disorders are due to an excess or deficiency i n the number o f genes contained wi thin an entire chromosome. T h e most c o m m o n example is D o w n Syndrome (Trisomy 21), wh ich is an extra normal copy o f chromosome 21. Multifactorial inheritance is responsible for a wide range o f disorders, believed due to multiple genetic mutations. Some cancers, coronary artery disease and diabetes meUitus are included i n this group. A mutation is defined as any permanent change i n the nucleotide sequence o f D N A . Mutations may occur i n somatic or germline cells, but only germline mutations are inherited. Somatic mutations, however, are responsible for many medical problems. F o r this reason cancer and coronary artery disease are often considered 'genetic' diseases (Prater and Newlands 1999). The practical goal o f medical geneticists is to understand the basis for mutations and to use that information to design new therapies for gene-related disorders. The field contains numerous, rapidly Latour (1988) describes a similar effect in the Pasteurization of France. 154 advancing areas o f interest, such as chromosomal analysis; cytogenetics; biochemical genetics; clinical genetics; populat ion genetics; genetic epidemiology; developmental genetics; immunogenetics; genetic counselling; and foetal genetics. M i c h a e l Hayden's research program i n Huntington's disease is one example o f the type o f cross-overs that occur. Hayden's team has identified a marker used i n genetic testing for Huntington's disease. A s wel l as researching the genetic basis o f the disease and testing for it i n patients, they are also invo lved pre-natal testing, and i n studying the psychological consequences o f genetic testing o n patients. The history o f medical genetics and the history o f the gene are mtertwined (Childs 1999). Ke l l e r (1995) traces an arc through three periods. The early 2 0 t h century was dominated by a very powerful discourse o f gene action. Bu t the gene itself remained a statistical entity; a black-boxed construct. In general, medical science paid litde attention. Interest increased when the physical basis o f heredity was established, but mainly among those who studied rare anomalies (Childs 1999). Bu t little progress was made unt i l 1953 when James Watson and Francis C r i c k described the molecular basis o f D N A . The m i d 2 0 t h century was the era o f early molecular biology, w h i c h seemed to provide answers to questions about the nature o f the gene and gene action—the 'genetic program'. A t this point, according to Chi lds , medical genetics began i n earnest, following the functional definition o f one gene-one enzyme. In the 1960s, the development o f the structural definition o f the gene meant that inborn errors o f metabolism could be described i n terms o f protein differences. The comparative youth o f the field can be illustrated by network scientist Charles Scriver., who learned biochemical genetics i n its infancy. W h e n Scriver joined the M c G i l l faculty in 1961, he was the first biochemical geneticist i n Canada, meaning that he was 'the first one formally trained to do that type o f thing and be taken onboard as a person who wou ld do biochemical genetics' ( C G D N - C S ) . 155 In the late 2 0 t h century, the molecular definition o f the gene led to a technological explosion that moved genetic and molecular analysis beyond rare single-gene disorders to complex, multifactorial diseases. The tools o f molecular genetics underwent revolutionary changes. They include the identification and use o f restriction enzymes, c loning for recombinant D N A , vectors, probes, polymerase chain reaction, D N A sequence analysis and protein analysis. The availability o f these tools, and the promise o f genetics, led to the foundation o f the H u m a n G e n o m e Project in the early 1980s. A s the project neared complet ion, molecular biology again changed radically as fields like proteomics and functional genomics came to the fore. The 'new genetics' is revolut ionizing medical genetics. It raises the prospect o f altering the genome to prevent disease rather than treat disease. Vir tual ly all disease progresses as a combinat ion o f environment and genetics ('nature versus nurture'). Medica l geneticists believe 'nature' plays the most significant role and act to intervene. Many believe this prospect raises the spectre o f biological deterniinism and a new eugenics.' 0 9 F o r others, the new genetics ignores the significance o f 'nurture', i.e. the socio-economic determinants o f health and disease. 1 1 0 Whi l e these debates and issues are compell ing, except where they impact direcdy o n C G D N they he beyond the scope o f this study. The next section examines issues o f space and scale i n the molecular sciences and relates these to C G D N . Space and Scale In her comparison o f high-energy physics and molecular biology, K a r i n Knor r -Ce t ina (1999) describes the latter as small-scale 'benchwork science' geared to 'treatment and intervention'. B y definition molecular biology manipulates small objects i n small labs . Th is modest scale was 1 0 9 Richard Lewontin is an authoritative source, see 1991 & 1999 156 illustrated o n one o f m y site visits to a network researcher i n Toron to . T h e team was just setting up a new laboratory i n a university annex. The lab, quite literally, came i n two cardboard boxes. O n e contained a powerful P C , pre-loaded wi th genetic analysis software. The other contained slides, reagents, and biological materials. W e laughed about franchising 'Lab- in-a-Box ' , or 'Lab - to -Go ' . O f course, the physical infrastructure o f the laboratory is provided by the university but the space and benches are generic. Beyond unpacking the boxes, nothing special is required. G ie ryn (1999a & b) has commented o n the standardization o f space i n these labs and the architectural boundary work they embody. I noted similar effects i n m y site visits to different locations. The organization o f space is predictable. F o r example, the labs at the Centre for Molecular Medic ine and Therapeutics are laid out i n such a way that the upper and lower floors are virtually identical. A c o m m o n room/k i t chen is located o n each floor, at one end o f the hallway. This area is the social focus, w i th a lot o f coming and going. Signs o n cupboard doors advertise meetings, seminars, and social events. Groups o f grad students and post-docs chat over coffee and microwaved food at the c o m m o n table. Overheard conversations: 'I had to sacrifice my first mouse last night'; 'I just found a mouse up my sleeve; its tail was sticking out. I thought I 'd lost it'. (The mouse core facility was located at C M M T at this time). The labs are situated around the circumference o f each floor, while the heavy a n d / o r shared equipment is i n the centre. E a c h lab appears to have two work ing benches i n a bay and a computer desk. The building's architectural boundary work discloses no 'public face', not even a functioning reception area. A l l exterior doors are locked and electronically controlled. N o n e is identified as the main entrance to the bunding. The most likely candidate carries a sign advising visitors, i n no uncertain terms, that they are at 'the wrong place'. 'This is not the hospital ' , it says. Those who In Canada, note the work of Patricia Baird e.g. 2000 and Clyde Hertzman e.g. 1999. Both are members of CIAR 157 persist must use the in tercom to ask someone to come and physically admit them. Indifference to (or fear of?) public intrusion was a spatial feature o f the all the network facilities I visited. The sites o f knowledge product ion were not 'open'. These sites, molecular biology labs, house 'biological machines' for the genetic engineering o f knowledge. Knor r -Ce t ina calls these machines 'prolific small-scale factories' for the mass-production o f cell-lines, bacteria, vi ra l vectors, and purified mice, like those the grad students were discussing. These were 'knock-out mice ' , used i n the study o f oncogenes (cancer), that the network supplies from its mouse core facility. ("We put genes into the mice and then send them o f f to the investigators' [Mouse Core Facility Director , FJ-16]). Mouse models ('animal helpers') are research tools. Geneticists engineer them by 'knocking out' particular genes to try to cause cancer. The mice are bred to be exactly the same; a blastocyst injection into the o v u m changes the organism. These mice are not 'natural'; they are constructed i n the laboratory. B runo Latour (1987) talks about the 'purification' o f w i ld nature that takes place i n a lab. ' In her comparison o f the cultures o f high-energy physics ( H E P ) and molecular biology, K n o r r - Cetina (1999) notes that experimentation i n H E P involves large and very expensive experimental devices and hundreds o f scientists. These huge investments demand a long-term communitarian orientation to the management o f spaces and technologies. Thus 'big science' like H E P is largely a collective enterprise. Publications list hundreds o f authors in alphabetical order; discourse is open and free-flowing along 'confidence pathways' that l ink people together; a variety o f spokespersons represent the work. Knor r -Ce t ina calls this a 'post-traditional communitarian structure'. In contrast, molecular biology's 'lab i n a box ' has no dominating technical apparatus that w o u l d focus a community. Instead, says Knor r -Ce t ina , individual scientists occupy separate spatial and epistemic lifeworlds. In contrast to H E P , molecular biology is highly individuaUstic: witness the tradition o f naming labs after the leader (the Hayden lab; the W o r t o n lab). A s described i n Chapter 5, leaders speak for and represent the lab as a whole. They are the focal point for public and scientific recognition. They appear i n the media, give papers at conferences, accept the awards, while those who actually do the work often go unrecognized. Glasner & Rothman (1999; 2000) show that the most prominent and authoritative 'experts' are those who are furthest f rom bench research. A dual system is at work. Teams o f post-doctoral fellows, graduate students, technicians, and junior faculty do the actual hands-on science under the direction o f project leaders, while the lab director attracts the resources and plans the research program. O n e o f the network's core set, L a p Chee Tsu i , is chair o f C G D N ' s Scientific Adv i so ry B o a r d and head o f the International H u m a n G e n o m e Organization. H e says, I'm still in the lab in terms of interactions but not day to day, not hands on anymore. I have to rely on people telling me what is going on. Of course I miss it. But it would be very difficult to go back. Because now I design experiments so complicated I need people to help m e out. LCT-26 G i v e n the dominance o f laboratory leaders, and the fragmentation o f molecular biology, C G D N ' s achievements i n fashioning 'something like' a communitarian network culture, and 'something like' network science, are worthy o f comment. Unable or unwil l ing to overcome embedded epistemic norms, they were able nevertheless to scale-up unti l the network approximated 'big science'. Scaling Up U n t i l quite recently, molecular biology i n Canada was a competitive and fragmented wor ld where solitary researchers, i n small laboratories, conducted small-scale experiments. Interactions were limited, i f nothing else because o f the time and costs involved. A s one o f C G D N ' s investigators recalls, 159 Y o u might see your research colleagues at meetings or even make special trips to go to their lab and discuss research in common. A n d you might even send some grad students around or a technician to leam a procedure or something. But that was a relatively small number of interactions that each lab would have with another lab.. .There was [no] money there. Y o u could [not] justify saying well, I would like to go over and see so-and-so do this, [and] take it out of your operating expenses (Researcher, AD-17). But as the research issues became more complex, it was increasingly clear that molecular biology could no longer operate effectively at a small scale and remain competitive internationally. B y the time Michae l Hayden reached out to colleagues across Canada, i n 1988, it was already unlikely that a medical geneticist, work ing alone, w o u l d find bo th the gene and subsequently the cure for a genetic disease. A more likely scenario for that type o f advance was the k ind o f 'heterogeneous engineering' (Law 1992) that combined medical geneticists and other molecular biologists wi th viral agents, tissues, genetic physicists, pharmaceutical chemists, gene sequencing technologies, 'purified' mice, and bioinformatics. L i k e high-energy physics, biology was becoming 'b ig science'. Lap Chee Tsui , gave a clear description o f the differences. The way we do science is definitely different now than it was say 15 years ago. Back then it was all very small experiments. A n d of course things were very pnmitive too. Medical research has definitely changed- - its scope, the way it approaches things, the knowledge required to run or operate it. It is no longer just a solitary person dreaming up some experiment. It definitely requires quite a lot o f help from other people. A n d i f not from other people, from computers and the internet. Before, the literature and meetings were the only dungs we had. Y o u got all your connections that way. N o w the scope has just broadened so much. To undertake a biological question, you need engineers and statisticians to come in. A single person can't operate effectively in biology any more. I don't know how to put it. Compare biology to physics. In physics diese days, although a few are still doing investigator-driven research in small laboratories, seeking answers to a few very specific questions, the bulk of the experiments are done by big groups, large-scale networks using central facilities. I think biology is moving towards that model. LCT-21-2 Through the N C E program, Canadian biologists were able to aspire to the benefits o f b ig science. N C E s helped the Canadian life sciences earn respect and remain internationally competitive i n medical genetics, protein engineering, bacterial diseases, neuroscience, respiratory diseases and other 160 biological areas. A s one o f C G D N ' s founders comments, 'the network has been very good for the field o f medical genetics in Canada. It has strengthened the discipline. People regard Canada as being a good place to do genetics' (BR-52). Ano the r network researcher compares his experience i n C G D N wi th his experience i n the U K . In England, I [belonged to] a large collection of scientists working on a similar topic. The group is so big it's like a force of nature. In that that type of institute you are immersed in science in a way which we can't do in Canada. We don't have the resources. We can't allocate that much money to do focused research of that type. But that's what we're doing here in the network. We're doing focused research.. .The network allows us to bring together a critical mass of people who think about medical genetics problems, from different perspectives. And I think that's a real strength. MW-39 B u t to begin wi th , beyond the fact that everyone was do ing something to d o wi th human genetics, this 'critical mass o f people' was not focused. It took time to develop an understanding o f what it meant to have a network research program and to weave together the projects o f individual researchers i n some way that made sense. A Network Research Program? W h e n the founding researchers were recruited i n 1988, they were asked to write up a 'wish list' o f projects they wou ld choose to undertake were funding available. Br ian Rob inson recalls that when R o n W o r t o n visited his lab to invite h i m to join the network, 'he said, wel l , have you got projects that you are not doing n o w but you w o u l d like to propose? A n d I said, o h yes. There are always lots o f those' (BR-1). The desiderata o f individual researchers were then creatively combined to constitute the network's research program i n the funding proposal. T o reinforce the point: the 'network research program' was an imaginary, rhetorically constructed from individual research programs for the purposes o f obtaining funding. W h a t was proposed was 161 simply a continuation and expansion o f ongoing individual studies, wi th some o f the expansion being due to network funding. The overall scientific objective o f this composite was to study the molecular basis o f genetic disease and the genetic basis for susceptibility to c o m m o n diseases. The major goal, at that point, was to clone the genes responsible for selected genetic disorders. This w o u l d evolve in later phases, but i n 1988 geneticists were still preoccupied wi th 'gene-hunting'. Little changed once the network was operational. Ear ly N C E assessments crit icized the emphasis o n the individual researcher: 'for the most part, [the science] seems to be too m u c h P l -d r iven and not enough project-driven' ( C G D N - E P 1992: 4). O v e r the years, however, the network became more astute at shading annual reports and statistical materials to convey the impression o f integrated research projects and active lab-to-lab collaborations, despite the relative paucity o f both. W e always said we had research projects, because that's what we were supposed to have, but we didn't really. W e had people work ing o n different diseases.. .So it was pretty hard for us, at the end o f the day, just to describe what our projects were' (Manager; PS-CS-74) . In the original proposal, individual projects were loosely grouped under seven themed headings: (1) identification o f disease genes based on chromosome location, for example cystic fibrosis; Hunt ington disease; myotonic dystrophy; W i l s o n disease; (2) mutation and functional analysis i n Duchenne muscular dystrophy, retinoblastoma and retinitis pigmentosa; (3) genetics and biochemistry o f inborn errors o f metabolism, for example i n Tay-Sachs and Sandhoff disease; (4) analysis o f genetic factors predisposing to c o m m o n diseases in mice and humans, using recombinant congenic strains i n mouse models o f human disease, and amplified sequence polymorphisms; (5) the structure o f human genetic variation, such as thassalemia i n French Canadians, and Tay-Sachs i n French Canadians and Ashkenaz i Jews; (6). construction o f chromosome specific c D N A maps for specific tissues including retinal c D N A isolation and mapping and linkage analysis i n diseases 162 affecting the retina; (7) core technology facilities—the nine technologies offered i n Phase I are listed i n the next section. A t the end o f Phase I, this research program was assessed by an expert panel, based o n self-reports submitted by the network and a 2-day site visit by the panel to the network's head office at the end o f September 1993.'" Descriptions of ' themes ' , 'projects', and 'teams' were accepted at face value as part o f an integrated program. The panel recommended teuriming some projects, focusing others on more competitive fields o f research, and regrouping physicians and scientists into smaller numbers o f highly competitive teams ( C G D N - E P 1993: 11). B u t overall, i n their estimation, the network had achieved 'outstanding progress'. I f there were an international standard i n genetic research, they said, C G D N 'might wel l be o n top o f such an international comparison ' ( C G D N - E P 1993:8). The panel submitted a favourable report to the N C E Directorate o n October 25 1993. In part, that report read The Site Visit Committee noted the outstanding role played by scientists in this network on the international level with respect to the cloning of disease genes and investigating their functions.. .The Committee was also impressed by the collegiality and networking established among the investigators of the network and noted the importance of the establishment of the core facilities as a catalyst in this process. The Site Visit Committee, therefore, enthusiastically recommends that the network continue ( C G D N - E P 1993: Cover letter) O n October 28 1993, three days after the expert panel had submitted its favourable report, C G D N tendered its proposal for Phase II o f the N C E program. Whi le bui lding o n what went before, the research program was restructured to accommodate the research interests o f new recruits. The research emphasis w o u l d now switch to c o m m o n multigene disorders like Alzheimer ' s and breast cancer instead o f the rare single-gene disorders that had been the focus o f Phase I. Acco rd ing to R o n W o r t o n , this was a pragmatic decision made because ' i f we don ' t get into the complex diseases, the reviewers are going to wonder why and they're not going to give us fanding for Phase II ' ( R W - 163 25). E v e n mote pragmatic was the fact that these were profitable diseases. A s another researcher comments, 'the b ig pharmaceutical companies are interested i n these b ig polygenic diseases.. .the diabetes, the inflammatory bowel disease, the sort o f things that tens o f thousands o f people suffer from. Because that is where they are going to make their money' (BR-43). The eight themes for the Phase II research program were: (1) identification o f disease-causing genes; (2) genes and phenotypes; (3) dynamic mutations (novel causes o f human genetic disease); (4) genetic analysis o f complex traits (mouse models o f human disease); (5) genetic epidemiology and populat ion genetics; (6) therapeutic interventions for genetic diseases (new theme); (7) applications o f molecular genetics to health care (new theme); (8) core facilities. The two new themes emerged from the new emphasis o n relevance i n program criteria, that weighted translation o f findings into practice equally wi th excellence o f fundamental research. Theme 6 was a move into gene-based therapeutics and clinical trials; theme 7 into commercial diagnostics. B y the end o f Phase II, the network had adopted i n its reporting a language o f 'key discoveries', 'breakthroughs', and 'commercial impacts'. They maintained metrics o n all , claiming 170 discoveries overall i n Phase II, o f wh ich 100 were related to c o m m o n , multigene disorders. Twenty 'key discoveries' were highlighted, including the isolation o f the first two Alzhe imer familial disease genes by a researcher at the Universi ty o f Toron to i n 1996. The discoverer was new to the network that year, recruited when he was close to the breakthrough after work ing o n the project for a number o f years. E v e n though the discoverer was a new member who allocated only 10% o f his time to the network, C G D N was able to claim credit because he was a member at the time the genes were cloned. Ano the r o f the new Phase II researchers identified 1 1 1 Note that site visits assess all aspects of a network's mandate. In addition to the scientific program, its commercialization activities, partnerships and linkages, management, and training activities are also reviewed. 164 breast and ovarian cancer mutations i n the genes B R A C 1 and B R A C 2 . These too were claimed as 'network discoveries'. O n the other hand, it was one o f the original P i s — a 1988 'young researcher' who had spent almost his entire career wi th the ne twork—who discovered a family o f proteins that inhibit cell death. This breakthrough was quickly patented and spun-out into a company (see Chapter 7). In the new theme concerned wi th therapeutic interventions (#6), researchers had not yet translated findings into applications; rather they had 'created tools for gene-based therapeutics, setting the stage for therapeutic advances i n Phase 3' ( C G D N - F P 1997a: 11). Progress had been made i n biological problems i n hematology that had been barriers to the use o f gene therapy for b lood diseases, and i n the use o f herpes simplex virus (HSV) as a vector for gene delivery. The second new theme, Genetics i n Heal th Care (#7) demonstrated much more translational progress. F o r example, headway had been made towards the identification o f a direct genetic marker for osteoporosis risk, based o n estrogen receptor variants, and o f predisposing genes for risk o f coronary artery disease (atherosclerosis). In addition, one o f the researchers developed a novel technology for rapid, accurate, and cost-effective D N A sequencing o f mutations, that was quickly adopted by the H u m a n Genome Project. A l s o , key advances had occurred i n the mutation analysis o f the gene for Retinoblastoma (Rb), a devastating chi ldhood cancer o f the eye. Because each R b mutation was revealed as virtually unique, efficient methods for mutation analysis were required. This need was translated by the researcher into mutation diagnostic reagents and kits for cost-efficient diagnosis and cascade testing i n families. T h e investigator comments that, without the network, we might never have developed the R B test the way we have. We would have failed, like every other lab in Nor th America, to practically help patients, because the test would have been too expensive, and too difficult. [Without the network] I don't know where I could have got funding to do that research. BG -44 165 The network submitted its progress report on Phase II , together w i th an application for Phase III funding, o n A p r i l 29 1997. In February 1997, the N C E program had been made permanent, but individual networks—^including C G D N — h a d been 'sunsetted'. A t that point, the Phase III funding proposal had been i n preparation for almost a year. In less that two months, it had to be reoriented towards sustainability beyond the exit o f N C E funding. The research program was collapsed into the four elements wi th the most potential for commercial exploitation" 2 : (1) identification o f disease causing genes; (2) pathogenesis and functional genomics; (3) genetic therapies; and (4) genetics and health care. A 2-day site visit was arranged for late June. Subsequendy, the conclusion o f the panel was that fonding should continue for the max imum, allowable period: unt i l M a r c h 31 2005, subject to mid-term review i n 2001. They cited the increasing number o f multiple-authored papers across projects as an indicator that 'the group n o w shows m u c h more evidence o f work ing together as a team', and concluded that the network's evolution had been notfiing short o f 'remarkable, i n that it has not only achieved its stated goals i n fulfilling the mandate established for N C E s , but in almost all cases has surpassed them' ( C G D N - E P 1997:15, 17). Weaving together individual strands to give the appearance o f coherence, such that reviewers were convinced the network had 'achieved and surpassed' the stated objectives, was a considerable rhetorical achievement. B u t whether the credit belonged to the network o r the individual researchers is an open question. It remains unclear h o w much o f the network's research program w o u l d have been achieved i n its absence or h o w to calculate the incremental value the organization added to existing individual research programs. Recognizing these ambiguities, C G D N has recentiy revised its organizational purpose. U n t i l early 2001, the mission was 'to research the diagnosis and treatment o f genetic diseases and to help move see Chapter 6 for detailed discussion of the network's commercial activities in all three phases 166 the resisting discoveries into the health care system' ( C G D N - A R 1999:1). It n o w defines itself, more accurately, as an 'enabling organization' and a 'catalyst' for research ( C G D N - F P 2001: C D 1 ) . Bu t in one aspect o f its research program—the provis ion o f Core Facilities—little doubt existed about the network's contribution. Core Facilities are the advanced technologies and technological expertise that helped network investigators speed research progress and 'breakthroughs'. They were the 'enabling technologies' o n which the network's research program rested. The Core Facilities are what legitimate the network's claims, and justify the not ion o f 'network science'. Core Facilities: 'Where all the spokes converge' The core facilities are a kind of network legacy, I think. They are really the axle where a lot o f the spokes converge. FJ-62 The network's core facilities simulated the technological support infrastructure o f 'big science'. Easy access to powerful and expensive technologies allowed relatively small labs to undertake ambitious projects and compete internationally. In a priority race to identify genes, where every additional day matters, and where specialized technologies may not be available at a researcher's home university, they enabled resources to be dedicated to a particular project i n order to move it ahead rapidly. The network w o u l d fund core facilities when it could balance demand and supply; that is to say, when demand for a novel and /o r sophisticated 'leading edge' technology could be matched to a principal investigator, ready to act i n the capacity o f director, and wi l l ing to offer that technology to other members o f the network. A s discussed earlier, i n defining an N C E the network metaphor itself is less than helpful; the more accurate image is o f 'spokes' and 'hubs'. This was the case with core facilities. N e t w o r k researchers across Canada (spokes) drew o n core facilities and expertise (hubs). T h e hubs supplied the network's 167 material and intellectual infrastructure. Rather than researcher to researcher, collaboration was between researchers and core facility directors—the network's 'master collaborators'. The nine Core Facilities and directors available i n Phase I are listed i n the Figure 9 below. A t M c G i l l , K e n M o r g a n built databases for analysing populat ion genetics and Charles Scriver maintained a longstanding cell bank holding about 2100 cell strains. Alessandra D u n c a n at Queens provided radioactive detection o f short probes. A t U B C , R u d i Aeberso ld supplied Protein Analysis and developed improved sequencing reagents and protocols; Frank J i r ik and Jamey Mar th started to create transgenic and knockout strains o f mice, while G r e g Lee focused o n product ion o f monoclona l antibodies." 3 A t Sick K i d s , the first facility for sequencing small fragments o f D N A was set up i n L a p Chee Tsui 's lab and was heavily utilized from the start. R o n W o r t o n provided somatic cell mapping, to map cells to specific chromosomes. Peter Lea supplied electron microscopy at the University o f Toron to . Figure 9: CGDN's Core Facilities, End of Year One, Phase I (1990-1) Facility Director(s) Institutions Computing and genotyping Morgan McGill Cell Bank Scriver McGill In Situ Chromosome Hybridization Duncan Queen's Protein Analysis Aebersold UBC Transgenic and knockout mice Jirik and Marth UBC Hybridoma Lee UBC Electron Microscopy Lea UToronto DNA Sequencing Tsui UT/HSC Somatic Cell Mapping Worton UT/HSC Source: C G D N - A R 1991; C G D N - E P 1993; C G D N - F P 1988 The status o f the core facilities developed at the end o f Phase II and the begmriing o f Phase III are shown i n the Figure 10 below. B y this point three D N A Sequencing facilities were supported. A new large-scale sequencing site at U B C , a small fragments core at U V i c , plus the original i n Toronto . B y this time, Francois Oulette, based at C M M T , was offering Warning i n computational biology for the importance of monoclonal antibodies as a research tool see Mackenzie, Keating and Cambrosio 1990 and Cambrosio and Keating 1998 168 (bioinformatics) so researchers could develop skills needed to access the new genomic databases being produced by the human genome project. A t M c G i l l , E m i l Skamene screened recombinant congenic strains o f mice to idenify genes control l ing complex traits. Jeremy Squire, at the Ontar io Cancer Institute used F I S H techniques to map genes and c D N A to chromosomal regions o f human and mouse genomes. M o u n t Sinai's Joseph Culot t i isolated mutated c. ekgans gene homologues o f human disease genes. T w o new facilties for the provis ion o f genetically modif ied mice, at McMas te r and M t Sinai, eased the load o n Frank Jirik's existing facility at U B C . A new immunoprobes facility was established by J o h n Wi lk ins , at the Universi ty o f Mani toba , to develop reagents for cell and molecular biology experimentation. A t Lava l , Rejean D r o u i n analyzed the physical state o f D N A in vivo for information o n D N A - p r o t e i n interactions. Three researchers at the Universi ty o f Toronto 's Banting & Best Institute established a facility to isolate and identify interacting proteins. A t Sick K i d s , Joanna Rommens identified transcribed sequences i n genomic D N A i n aid o f gene discovery projects. 169 Figure 10: CGDN's Core Facilities, End of Phase II, beginning of Phase III (1998) Facility Director(s) Institutions Bioinformatics training Oulette UBC/CMMT Complex Traits Analysis Skamene McGill/MGH Fluorescent In Situ Hybridization Squire UT/OCI DNA Sequencing Hayden UBC/CMMT Scherer UT/HSC Koop UVic Genome alteration in C.elegans Culotti UT/Mt Sinai Genome alteration in mice Rudnicki McMaster Jirik UBC/CMMT Nagy & Rossant UT/Mt Sinai Core computing and genotyping Hudson & Morgan McGill/MGH Immunoprobes Wilkins U.Manitoba In vivo DNA analysis Drouin Laval/SFA Protein-protein interactions Friesen, Greenblatt, Pawson UT/B&B Transcribed sequence detection Rommens UT/HSC Source: C G D N - A R 1999; C G D N - E P 1997; C G D N - F P 1997 B y the time o f the Phase III mid-term review (May 2001) the network had instituted a major shift i n emphasis. A s described earlier, the network's new mission was to be a catalyst for research advances i n the wake o f the sequencing o f the human genome. *We are n o w i n the post-genomics age. Many genes involved wi th pathology have been cloned. The focus n o w shifts to the proteome and pathogenic mechanisms' ( C G D N - F P 2001). The core facilities were rationalized into four clusters: (1) Core Technology Platforms D N A sequence analysis; bioinformatics;" 4 (2) Gene Technologies: i n v ivo D N A analysis; genotyping; transcribed sequence detection; (3) Protein Technologies: immunoprobes; proteomics; (4) G e n o m e Alterat ion: c.elegans; mouse. A s before, the highest demand was for D N A sequence analysis. A partial cost-recovery program shifted some o f the burden for facilities maintenance from the network to the users, reflecting the Phase III focus on sustainability. See (Keating and Cambrosio 2000 on the significance of platform technologies 170 A l l participants interviewed agreed that the core facilities, and the skills o f their directors, represented one o f the network's key legacies. Researcher: The core facilities were a real catalyst for promoting interactions. We did a lot of cross- country running about among different labs, but a lot of them centred around core facility usage. RG-29 Researcher: I think a key feature of the network has been the [core] facilities, especially the sequencing facility. There is no way I could have got that sequencing done without the resources of the network (DC-12) Researcher: For me, the high point of the network has been the core facilities. That's been my favorite component of the network. It's been fantastic. RG-89 Core Facility Director: If you want something immediately there is immediate cooperation. When we know that someone is getting close to a gene, and they need this kind of help, we put the secondary requests aside and emphasize this competitive project. LCT-11 N C E Selection Committee: The committee attributed the success of this network to an exemplary collegial exchange of knowledge and its reliance on and extensive sharing of resources, such as the core facilities. Genetic research, especially human genetics, is extremely cosdy to perform. The committee considered that the sharing of core facilities alone represents a significant benefit from the investment ( N C E - S C 1997: 11) The added value was i n setting up an infrastructure for undertaking the technical work that no single researcher could afford to set up independendy, in their o w n labs, but needed to use sporadically. Gene mapping was an example. W h e n the original core facility was set up a backlog o f demand quickly accumulated. A s the director states, ' i f somebody wanted something mapped, they just sent i t to me, and i t was a given that I was going to do i t . . . I f they hadn't been part o f the network, they wou ld have had to organize for just one little probe to be mapped wi th somebody else' (AD-21). A s technologies like this became more and more central to research progress, and demand for them increased, universities and hospitals started to acquire their o w n capacity. A t that point, network resources were redirected to other technologies not yet generally available. Core facilities wou ld also be terminated i f they were not used enough. F o r example, as can be seen i n the two Figures above, 171 seven o f the ten Phase I facilities had been replaced by the first year o f Phase III (1998/9), when C G D N offered 11 core technologies i n 15 locations. In between, other core facilities had been started and abandoned. Between 1991 and 2000, some $8M—approximately 20% o f the network's total program fund ing - was dedicated to core facilities. The system appears to have been a cost effective way o f sharing resources. Some researchers argued that all the network's resources should be directed into such facilities rather than into the relatively inconsequential amounts o f fanding allocated to each researcher. O n e researcher says, ' I always thought that the majority o f [network] activity should go into the maintenance and development o f core facilities, to encourage collaboration' (RK-10) . Ano the r researcher, the director o f a core facility, allocated most o f his o w n network funding towards its support: ' M o s t o f the money I get through the network we've thrown o n the core facility—two people and about 600 mice . . .and various equipment and instruments' (FJ-16). Bu t core facilities were more than just sharing expensive equipment and biological materials; they also represented the pool ing and sharing o f expertise. They were an efficient way to leverage the productivity o f researchers and ongoing research. Rather than duplicating facilities at different sites, resources were concentrated at one site and in one person. A s a network researcher explains, 'it is the expertise o f the people tiiat is core, rather than the machines' (BG-39) . In fact, it is the combination o f people and machines that counts. 'The core resource is one thing and the experience o f the director. . .and the people who work there, is another (LCT-10) . The combin ing o f machines and their directors in this way constituted what Latour (1987) calls a human/non-human hybrid and Picker ing (1993:373) describes as a human-machine interface. Such 'cyborgs' can find answers far more expeditiously than any 'regular' scientist or technician would . The issue is familiarity and the way constant practice refines skills. 'I don't want my technician to have to learn a whole technique 172 to do 10 samples. That is a waste o f everyone's time and money, quite apart f rom the machine' ( B G - 39). A s technical and scientific experts, core facility directors operated the 'mangle o f practice' (Pickering 1993) at the intersection o f the network's material culture and mora l economy. The material culture o f a science is its 'tools o f the trade': the machinery and methods o f knowledge product ion, its instruments and experimental practices. The mora l economy is the social rules and customs that regulate access to the material culture, establish authority over research agendas, and allocate credit. A s Robert K o h l e r points out 'tools and methods only become productive when they are part o f a social system for socializing recruits, identifying doable and productive problems, mobi l i z ing resources, and spreading the word o f achievements' (1998:243). The interesting question, according to K o h l e r , is h o w material culture and mora l economy operate together to make research productive. Picker ing (1993:374-5) argues that the mechanism is the 'mangling together' o f human agency and performative material devices i n 'a dialectic o f 'resistance and accommodation' . W i t h this i n mind , the fol lowing combinat ion o f factors i n relation to core facilities might be considered salient. (1) The researcher's requirement to have results processed, say genes to be sequenced. (2) The budgetary resources required to mobi l ize machines a n d / o r technical staff to do the processing. (3) The power o f these machines and technicians to produce inscriptions and standardizations from the data supplied. A n d (4) the technical and scientific expertise o f the core facility director, who manipulates the technologies, even when they resist, to process the experiments. W h e n we relate machines, money, molecules, and magi i n this way we are able to perceive modest, ' local ' actor-networks o f human and non-human elements, that become nodes in the larger actor-network that is C G D N . F r o m their location at the nexus o f science and technology, 173 knowledge and expertise, core facilities represent as m u c h a form o f artisanal or craft 'know-how' , as fundamental 'know-that ' ." 5 Earlier, I referred to core facility directors as 'master collaborators'. Th is was because, by virtue o f their posi t ion at a hub, they were aware o f and participated i n the majority o f research projects, and could suggest potentially fruitful interactions between researchers w h o may have been unaware o f each other's work. A s one director describes, ' in the early days.. .1 was among a small number o f people who were actually connected to most other people i n the network. . .Virtually everybody had been storing up a bunch o f stuff that they wanted mapped. . .1 interacted wi th a lot o f people' ( A D - 8). But , more than that, directors could actually steer the direction o f a project and the research agenda. By virtue of ninning a core facility, I know a lot of things that are going on, like new projects and stuff. A n d I have had input ability to actually participate and to help steer some of the research. A researcher will come to me and say that they want to do something and I say, well, maybe it wouldn't be good to do it that way, it's better i f you do it this way. Y o u see what I mean? I can actually play a role in determining the projects. If you're in a core facility well then, everybody is coming to you and saying 'I want to do this, what do you tfiink?' A n d so you have a chance for having input there. FJ-39-40 In terms o f the communa l life o f science, K o h l e r (1998:249) argues that three elements 'seem especially central to its moral economy'. These are access to the material culture; equity i n assigning credit for achievements; and authority i n setting research agendas and deciding what is actually wor th doing. Under this definition, wh ich encompasses rules o f mutual obligation, I w o u l d argue that the central role o f core facilities directors makes them responsible for a substantial por t ion o f the network's mora l economy. 1 5 For interesting historical treatments of artisanal knowledge see Eamon (1985) and Jackson (2000) 174 Conclusion This chapter has presented two contradictory impressions o f C G D N . O n one hand is a sense o f the chimerical: an ' imagined' communi ty wi th an 'imaginary' research program; n o w you see it, n o w you don't. O n the other hand is a sense o f real durability: established relationships founded o n mutual trust and anchored i n significant technologies. Is the black box empty or full? W e can approach an answer to that question by looking at the shift between Phases. The addition o f new actors into an existing network is always destabilizing. N e w actors come wi th their o w n networks, all wi th goals o f their own. Stability requires the disconnection o f alternative associations such that the network becomes the only point o f passage. A process o f mutual shaping must take place to incorporate the new into the existing actor-network. That integration was successful i n the shift f rom Phase I to Phase II. Bu t i n Phase III, the enrolment o f new allies (researchers and institutions) seems to have taken place without enough attention to interessement. The latter is where network-builders lock- in potential allies by gaining their commitment to a set o f goals and a course o f action. Enrolment without interessement creates a fragile network that readily fragments. The Phase III expansion was overwhelmingly strategic, thus translations were incomplete and the voice o f the spokesperson no longer spoke for all. W h e n there is 'interpretive flexibility' (Bijker 1994), the system's stability becomes precarious: black boxes open; points o f passage are ignored; and ambivalence becomes pervasive. . What then to make o f strong associations that only seem to strengthen wi th time? Perhaps we can think o f networks wi th in networks; layers o f associations like tree rings, showing different stages o f expansion. The older layers are the most dense; compacted; difficult to ^associa te . The newer layers are more porous; they can be peeled apart, and peeled away. A s wel l , it is clear that materiality makes networks durable and that more-durable materials tend to produce relatively more-stable networks. 175 Ideas and talk are ephemeral; to persist they need to be embodied i n inanimate materials like machines, books and birildings (Law 1992). The core facilities thus 'anchor' the network i n complex and costly technological tools and i n the embodied knowledge o f the scientists and technicians that operate them. A s L a w points out, however, durability itself is a relational effect. 176 C H A P T E R 6: F R O M S C I E N C E T O C O M M E R C E Truth and understanding are not such wares as to be monopolized and traded in by tickets and statutes and standards. We must not think to make a staple commodity of all the knowledge in the land, to mark and license it like our broadcloth and our woolpacks. John Milton. Areopagitica. (1644) N C E s were funded wi th the idea that they would , among other benefits, generate products and technologies for profit. A l though 'excellence o f the research' was the dominant criterion i n Phase I selection, and remained a background condi t ion, commercialization and partnerships wi th the private sector were key to the core mandate. W i t h the sunset o f N C E funding looming , C G D N focused o n constructing a portfolio o f licensing deals and spin-off companies that w o u l d provide a stream o f future revenues. All alternative sources o f income were investigated. In this chapter, I draw o n the metaphor o f the 'pipeline' that links the lab and the market. A c c o r d i n g to a recent description the process o f traversing 'the pipe' is 'arduous, passionate, r ich i n ritual, and steeped i n conflict and controversy ' ." 6 1 begin by discussing the nature o f the pipe and C G D N ' s posi t ion i n relation to it. I then review changes i n C G D N ' s connections wi th its industry partners. " 6 A network of Canadian social scientists has recendy begun a SSHRC-funded study (Financing the Pipe) that explores the moral basis of profit when disease is defined as a market opportunity (what I earlier called 'profitable diseases'). Although there are as yet no results or publications from the study, the funding application (supplied to me by the principals and available on the web page contains powerful and evocative descriptive language 177 Next, I map the two major strategic shifts in the network's evolution 'from science to commerce': first, in the mid-1990s, bringing some coherence to the commercial portfolio; second, in the late- 1990s, with a focus on network sustainability. In relation to the latter, two new initiatives are discussed that ratchet networking to a higher level, by bringing the life-science NCEs together, to joindy finance, 'bundle', and market the technologies in a combined pipeline. I. Understanding the Pipe The pipeline metaphor originates in the linear understanding of innovation that underpinned the postwar social contract for science. Even proponents of the 'open science' model on whichMost now view the linear model as an unrealistic depiction of the public/private, basic/applied relationship, especially in 'forefront' sciences like information technology and molecular biology which 'overflow' attempts to contain them. Yet the pipeline metaphor survived the collapse of the linear model; it remains ubiquitous in the 'pharmaceutical talk' of molecular biologists, as well as in the policy discourse. As Godin (2000-3:7, fn.31) argues it is, in fact, 'the spontaneous philosophy of scientists' and has been used in public discourse since the end of the 19 th century. Certainly, 'the pipe' accurately represents the realities of commercial d