Collaborative Research Networks @ CWN

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NETWORK MAPPING STUDY

Final Report

Prepared for the Canadian Water Network

Dimitrina Dimitrova, University of Toronto

Emmanuel Koku, Drexel University

Barry Wellman, University of Toronto

Howard White, Drexel University

Date: June 2007


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Acknowledgements

We are indebted to numerous people for their support and assistance in conducting thestudy and preparing this report.

Lee Weisser has been an invaluable member of the team. She has seen the projectthrough from start to finish, assisting it in numerous ways. She worked as projectadministrator, interviewer, and editor, and in all of these capacities she excelled. JeremyBirnholtz contributed incisive comments and ideas to the research design and thepreliminary report of the study. He also conducted a number of the interviews, bringinghis competence and experience to the process. June Pollard transcribed even the mostdifficult interviews with accuracy and speed. Kristen Mandziuk and Dolores Figueroacoded them expertly in NVivo. Kristen, in addition, spent many hours helping in theorderly wrap up of the project, sorting, verifying and cleaning records. A group of smartstudents assisted with numerous tasks: they transcribed interviews, entered data, searchedthe Internet, and hunted down articles and books. Glasha Romanovska , Lindsay Cai,

Jackie DSa, NatalieZinko

, and Nazila Rostami were all a pleasure to work with.Few research projects receive as much support and assistance from their fundingorganization as this one has. We have benefited tremendously from the visionary ideasand sage advice of Don Brookes, the professionalism and engaging personality of MonicaEscamilla, and the technical skills and hard work of Corban Riley. Other CWN staff including David Cotter, Bernadette Conant, and Karen Van Sickle, have also lent a handwhen needed.

Finally, this project was only possible because busy people working in the area of watergenerously shared their time and their insights with us. Working with them has been aprivilege and a delight.

Our sincere thanks to all!


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TABLE OF CONTENTS

AcknowledgementsExecutive summary...................................................................................................... i

Introduction..................................................................................................................... 1

Part I. Respondents ......................................................................................................... 3

1.1. Demographics: Who are the respondents?........................................................... 3

1.2. Personal networks: To whom are the respondents connected?............................ 4

1.3. Ties: Another look at the water community ........................................................ 6

Part II: Connections in the Water Network..................................................................... 9

2.1. Centrality Analysis............................................................................................... 9

2.2. Clique Analysis.................................................................................................. 13

2.3. Citation analysis................................................................................................. 21

Part III. The context of collaborative work................................................................... 27

3.1. Barriers and incentives for collaborative work.................................................. 27

3.2. Challenges on a project and strategies for overcoming them ............................ 29

3.3. Strategies for coping: team selection and independent work............................. 32

3.4. Impact of CWN on the work of academics and practitioners............................ 36

Part IV. Conclusions ..................................................................................................... 41

Appendix 1: Tables...............................................................................................................

Appendix 2: Figures..............................................................................................................

Appendix 3: Survey Data Collection and Available Data ....................................................

Appendix 4: Document and Interview Data .........................................................................


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APPENDICES

Appendix 1: Tables

Appendix 2: Figures

Appendix 3: Survey Data collection and Available Data

Appendix 4: Document and Interview Data


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Executive summary

The Network Mapping project is a social network study of the academics andpractitioners working in the area of water commissioned by the Canadian Water Network

of Centres of Excellence (CWN). The objectives of the study were to map the relationsamong the stakeholders in the area of water, describe the collaboration and knowledgeexchanges among them, and examine the context in which they worked.

The study included four components: a web based network survey (N=173), semi-structured interviews (N=65), citation analysis of a small subgroup of academics centralin the CWN (N=31), and review of documents. Several key findings emerged in theanalysis of these complementary bodies of data.

Socio-demographic characteristics and personal networks

The survey respondents have two salient characteristics: diversity and maturity.

Water issues are very broad, not easily captured within a discipline, and jurisdictionover water is fragmented among numerous government agencies. Hence, participantsin the water network come from a range of sectors and disciplines and have differentinvolvement in water issues. Engineers and natural scientists such as biology andearth/environmental sciences are most numerous while health, social and policyscientists are fewer. Such disciplinary and sectoral diversity provides the prerequisitesfor the cross-sectoral and multi-disciplinary research needed in the area.

At the same time, developing cross-sectoral and multidisciplinary ties strong enough

to sustain collaboration is difficult. This precludes dense connections in the waternetwork and makes water issues the playing field of experienced academics andpractitioners, who have developed diverse networks. The majority of the peopleworking in the area are mature professionals with well established networks, many of them in senior positions. In addition, despite some changes, universities tend toreward traditional work within a single discipline. This discourages junior academicsbuilding careers from doing complex collaborative research and further reinforces thematurity and seniority of the participants in the area.

Water community (whole network)

Briefly put, the water network is sparsely connected yet well structured and capable of supporting multidisciplinary and cross-sectoral collaboration.

The network has a small core of well connected central participants and a largeperiphery of sparsely connected participants less involved in water issues. Aboutthree quarters of these central participants are CWN members. This suggests that theagency either attracts central participants to the water network or helps its members todevelop their networks and become central. Among these central participants, those

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who actively network and reach out to others are junior academics, a few senioracademics, and practitioners from various sectors. By comparison, other centralparticipants play the role of experts who attract others. These are mostly senioracademics all of whom are involved in the work of CWN.

About two dozen participants actively work and exchange ideas with others, typicallyin small cliques of two to three colleagues. Some of them collaborate with colleaguesfrom several cliques and act as bridges that connect the cliques and preclude thefragmentation of the network. Notably, people in bridge positions are academics inmid career who have already developed their networks to some extent but are stillactively networking. Three quarters of the active collaborators are CWN members,confirming the key role of the agency in fostering collaboration in the area of water.

The composition of the cliques suggests that collaboration in the network ismultidisciplinary and often cross-sectoral. Most of the work cliques include membersfrom biology and earth/environmental sciences while the health, policy and social

sciences are less represented. The small size of the cliques arises from the independent work practices on the

research projects. Since collaboration across disciplines, sectors, and organizations isdifficult, one of the strategies to avoid problems and decrease efforts for coordinationis for researchers to work independently or in small groups. Only in a very few casesdo project participants work as integrated teams.

A second strategy to facilitate coordination and communication is for project leads toput together teams of people they know. While project teams include somenewcomers recommended by other team members, researchers tend to work with a

few long-term collaborators. Such teams of long-term collaborators increasecommitment and decrease the efforts for developing common practices and trust trust, commitment, and common practices have already been developed. Pre-existingties thus facilitated the formation of teams and the work on a project.

Citation practices Despite many multidisciplinary connections, the citation practices more closely

follow disciplinary boundaries. Scientists in the water network are perceived asworking in the same area and cited together. Often they are cited together withcolleagues from different disciplines. This suggests that their work hasmultidisciplinary relevance. However, scientists in the water network do not readily

see the relevance of their colleagues publications for their own work, rarely cite eachother directly, and such direct citations more closely follow disciplinary boundaries.Such citation practices are consistent with the publication criteria of most scholarly

journals which encourage working within a single discipline.

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CWN impact on the work of academics and practitioners The main impact of CWN on the work of academics is networking with the right

people. Academics interested in multidisciplinary and cross-sectoral research mightbe hard to find in a more traditional university environment and CWN helps suchacademics connect to each other and find partners.

In turn, practitioners emphasized in addition to networking the role of the CWNas a focus of expertise in the area and as a link to academics. Even outsiders withoutformal partnerships with CWN turn to it when they need information.

In short, the results of the study show that CWN is successfully achieving its mission: toprovide expert knowledge on critical water issues in Canada, to build scientific andhuman resources to address them, and to create a network of stakeholders in the area of water that serves as a catalyst for research and technology development. CWN plays akey role in holding the water network together and fostering cross-sectoralmultidisciplinary collaboration: the majority of central participants and active

collaborators in the area of water are CWN members. In turn, the presence of outsiders,who reach out to CWN members or already collaborate with them, suggests possibilitiesfor creating new partnerships. Although the overall water network is sparsely knit and thecore of well connected active participants is small, the ties are structured and the network is capable of supporting multidisciplinary cross-sectoral collaboration. The water network can be further improved by expanding the core, maintaining healthy balance between

junior and senior academics, increasing the number of bridges, and improving therepresentation of health, social and policy sciences. Nonetheless, in the diverse andinherently fragmented area of water, CWN has created a viable network, established itsreputation, and became a brand name in the area.


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Introduction The Canadian Water Network (CWN) was created with the mandate to supportmultidisciplinary research, cross-sectoral partnerships that link academics, governmentand industry staff, and cross-country collaboration in the area of water. CWN supports

knowledge transfer and innovation by connecting researchers and practitioners across thecountry. Crucial to its work is a comprehensive understanding of the existingrelationships among people working in the area of water that can facilitate themanagement and planning of CWN activities in support of the water community.

In the fall of 2005, CWN hired a team of researchers to conduct a social network study of the scholars, industry partners, public sector users and regulators whose work is directlyrelated to water. The goal of the study was to map the existing relationships among them,describe the processes of collaboration and the exchange of advice and innovative ideas,and delineate key individuals and research clusters within the network. The studyaddresses the following questions:

Who are the academics and practitioners in the area of water and what are theirsocio-demographic characteristics?

With whom are they connected? With whom do they exchange ideas? What is the internal structure of the network arising out of the ties among the

academics and practitioners in the area of water? Who is connected to whom? What activities do they do together in their networks? What is the context in which the academics and practitioners in the area of

water collaborate? In other words, what are the barriers to and the challengesin collaborative research?

What are the strategies used to overcome these challenges? What is the impact of CWN on the work of the academics and practitioners in

the area of water? How do they see the role of CWN in the area?

Data collection, described below and in further detail in the Appendices, consisted of aweb based national survey, semi-structured interviews, citation analysis, and a review of documents. In brief, the data collected in the study include:

173 surveys. Among the participants are 94 academics and partners involved inCWN funded projects. They are referred to as CWN members. Theremaining 79 respondents are academics and practitioners who are part of thewater community but who have never been involved in CWN funded research.They are referred to as outsiders.

65 interviews, including 56 interviews with CWN members and nine interviewswith outsiders. Among all respondents, 39 were both interviewed andcompleted the survey.

Citation analysis results for a small group of 31 CWN members.

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Several dozen organizational and personal documents, including 39 researchproposals, internal analyses and presentations, and several dozen resumes.

Although the survey is not a representative sample of all practitioners and researchersworking in the area of water, a profile of the respondents provides some understanding of

the characteristics of this part of the water community. Furthermore, both the survey andthe interviews include academics and practitioners working on CWN funded projects aswell as individuals who are not currently involved in the work of CWN. Thiscomposition of the survey respondents reflects the overall community of people workingin the area of water and enables a comparison of CWN members with other researchersand practitioners working in the area of water. The interview data, where CWN membersare proportionately much more numerous, also provide opportunities for a comparison.

Part I creates a profile of the participants in the area of water based on individual leveldata from the survey. Part II maps the internal structure of the whole network using theaggregated survey data. Part III draws on the interviews to describe how participants

collaborate, thus placing the network in context and suggesting explanations for itscharacteristics. Throughout the report, the interpretation of the results is informed by datafrom several available sources.

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Part I. Respondents The analysis below draws on both survey and interview data to describe the respondents,their networks in the area of water, and the way they use their networks for knowledge

and information exchange. The discussion introduces patterns visible in the overallsurvey sample and then follows with comparisons between CWN members and outsiders.

1.1. Demographics: Who are the respondents?The typical respondent is a mature professional in mid-career who holds a Ph.D., worksat a university, and is male.

The demographic data presen ted show that over two thirds (69.9%) of all our respondentsare men (Table 2, Section A) 1 . The mean age is 47.7 years, and the majority of therespondents are between 40 and 60 years (Table 1; Table 2, Section B). Most of therespondents have considerable work experience. On average, they have worked nearly 15

years (Table 1). More than a quarter have worked for more than 20 years (Table 2,Section C).

This is a well-educated sample. All respondents who provided information on theireducation have a university degree, and the most common highest degree is Ph.D. Amongthe respondents, 40.0% hold doctoral degrees, 20.8% Masters degrees, and 18.5%Bachelors degrees (Table 2, Section D). The largest group of respondents (40.5%)comes from academia, followed by government employees at various levels (37.6%),industry (11.6%), and NGOs (7.5%, see Table 2, Section F).

By discipline, the largest group are engineers (Table 3). They are followed by

respondents from a cluster of natural sciences: earth/environmentalscience/geology/ecology (Table 3). The next most sizable groups are social scientists(12.1%) and biology/microbiology (9.8%).

A comparison between the CWN members and the outsiders among our respondents ispresented in Table 4. As the table shows, CWN members tend to work in academia, holddoctoral degrees, be older and have longer work experience. Such differences areconsistent with the focus of CWN activities and are an indication of the calibre of thepeople the Network works with. For instance, the majority of CWN members holddoctoral degrees and have worked over 10 years (Table 2, Sections C and D). Bycomparison, the majority of outsiders hold either Masters or Bachelors degrees and are

concentrated in the lower categories of work experience (Table 2, Sections C and D).

In short, the typical CWN member among the survey respondents is an experiencedacademic, while the typical outsider is a slightly younger government employee. Thereare no significant differences between men and women although there are slightly morewomen among CWN members.

1 All tables are in Appendix 1.

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1.2. Personal networks: To whom are the respondents connected?The survey data enable us to describe the water networks of the 173 respondents. Thenetwork level data characterize the network of individual respondents: they show whoeach respondent knows in the area of waterthis group of people is referred to as theirwater networkand how they communicate and exchange information with them.

Alternatively, it is possible to combine all the 1,904 ties for which respondents provideinformation, and discuss their overall characteristics regardless of who has provided theinformation. This tie-level data describes the entire community rather than individualrespondents.

When focusing on the individual respondents and their water networks, the data showthat all our respondents have well-established networks in the water community and theytend to work directly with many of their ties. These network patterns are similar for CWNmembers and outsiders, although they are slightly more pronounced for CWN members.

All respondents

The typical respondent has known his network members in the area of water between fiveand ten years, contacts them a few times a year, works and exchanges ideas with themajority of them, and considers them acquaintances.

Further, the data on work ties shows that for a large group of the respondents, the peoplethey know in the area of water tend to be colleagues, partners, and collaborators. Therespondents work directly with them, as opposed to simply knowing them or being awareof them. Almost half of the respondents (46.2%) work directly with the majority of thepeople in their water networks (Table 5, Section E). This group of respondents is activelyworking with members of their network in the area of water. Another sizable group of the

respondents, 37.0%, works with fewer network members (Table 5, Section E). Arelatively small group among all respondents,16.8%, works with just a fractionlessthan one thirdof their network members on their water issues (Table 5, Section E).These respondents know people in the area of water but work with only a fraction of them.

This importance of work ties in the networks of the respondents reflects the selection of the respondents and the effort the survey requires for completion. We contacted peoplewho are actively working and have connections in the area of water. Further, therespondents chose to describe their ties with colleagues and collaborators rather than theirties with people they simply know but do not work with directly. In other words, the

survey captures the strong professional ties of the respondents. In that sense, theinteresting result is not the importance of work ties but the differences among therespondents: some are actively working with their network members while others areonly marginally involved with them. This suggests a diversity of the respondents which isconsistent with the diversity of the stakeholders in the area of water: water issues cover avery broad content area, they are regulated under multiple jurisdictions, and concern arange of government, community, industry and academic organizations. Priorities, needs,and level of involvement in water issues of these diverse stakeholders vary.

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A cross tabulation with sectoral data shows that the pattern of direct work with themajority of network members is common for some federal government employees andacademics. By comparison, the provincial and local government staff work with fewer(between 30% and 70%) of their network members (Table 6). These are people whose

main work responsibilities are in the area of water.

In contrast, working with a small fraction of their network members is common for otherfederal employees and some industry staff (Table 6). Since federal agencies andbusinesses are very diverse, their involvement in the area is very different. Some federalagencies and businesses are actively working in the area, others are connected tobut donot work inthe area. The main work activities of such respondents likely requireawareness and information gathering rather than direct contact with others in the watercommunity. These three groups with different network characteristics will need andbenefit from different CWN activities.

CWN membersComparing CWN members and outsiders reveals only slight differences in theirnetworks. When asked how close they are to each of their network members, both CWNmembers and outsiders show similar patterns. There are no differences between them inhow many friends they have in their networks. Consistent with their older average age,CWN members tend to have known their water network members longer than outsiders,work with more of them, and contact each of them less frequently. For instance, manymore CWN members work directly with most of their water network members comparedto outsiders (Table 7, Section E). The majority of CWN members (55.0%) contact theirnetwork members a few times a year (Table 7, Section A). Outsiders, in contrast, are notconcentrated in one modality of communication frequency: one third of them contacttheir network members a few times a year but almost as many contact their network members monthly. For a sizable group of outsiders, the average frequency of contact isweekly (Table 7, Section A).

Overall, outsiders tend to contact their water network members more often. This issurprising. Because CWN members work with more of their network members comparedto outsiders, they might be expected to contact them more often. Yet the opposite is true.A possible explanation is the long-term work schedules of CWN members. It is likelythat their work ties are with colleagues and partners participating in CWN-fundedprojects, which have a relatively long duration. Further, the majority of CWN membersare academics whose work also has long-term schedules. Indeed, the interview data withCWN members suggest that working with others on a project, whether CWN funded ornot, does not require constant communication. Instead, project communication isconcentrated in specific stages: writing the application and the reports, discussing theresearch design, or solving problems. Despite this burst of communication at certainstages, the average frequency of communication is not high.

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In contrast, outsiders tend to be government employees, most often from municipalities(Table 4, Section E). The comments of interviewees, which touch upon the different timeconstraints for government and academia, suggest shorter duration and quick turnaroundtime for government employees compared to academics.

In short, the work network characteristics of the overall samplethe large number of respondents working with the majority of their network members, five to 10-yearduration of ties, majority acquaintances rather than friendsare more pronounced in theCWN sub-group than in the overall sample of respondents. On the average, academicscontact their colleagues less frequently. But the average is misleading. Ties betweenacademics vary greatly in their frequency of contact. The typical academic has few ties of frequent, intense collaboration and many less intensive ties with other academicsoccasional interactions at conferences, etc.

The survey data also show whether, in addition to working, respondents also exchangeideas with other participants in the water community. People often work and exchange

ideas with the same colleagues, but it is not always the case. Compared to work ties,exchanging ideas is a more informal tie and at the same time requires trust. Hence, work and innovation ties may be quite different.

Social psychologists often find disjunctions between what people say and what they do.That is the case with CWN. The data show an interesting dynamic: the actual andpotential exchanges of ideas have different, almost opposite patterns. Table 8, Section Ashows that over half of the respondents have discussed innovative ideas with a majorityof their network members, suggesting a pattern of active exchanges of ideas. This isparticularly common for CWN members who are mostly academics; tossing around ideasis common for them. At the same time, when asked whether they would exchangeinnovative ideas with others, respondents reveal a completely different pattern (Table 8,Section B): the majority of the respondents say they would share ideas with a very smallproportion of their network members. They focus on obtaining ideas from a small set of other academics whom they trust as well as from grant-giving industry and governmentpartners. Thus, when it comes to sharing ideas in the future, selectivity is the majorpattern.

By contrast, the respondents do not expect such selectivity on the part of their network members. They expect a sizable proportion of their network members to exchange ideaswith them (Table 8, Section C). In other words, they believe they have the trust andrespect of their colleagues, and they want to gather ideasbut not share themwith awide range of network members.

1.3. Ties: Another look at the water communityWhat do these relational characteristics mean for the community of people working in thearea of water? Investigating all the ties of the survey respondents together provides apicture of the community.

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The analysis now turns to the ties, or those 1,904 people for whom our respondentsprovide information in their surveys. These tie level data capture additionalcharacteristics of the entire water community. The analysis suggests that the ties in thewater community are dominated by academics and local government: these two groupsare the backbone of the community.

As previously discussed, the largest group of respondents is in academia. The proportionof all government employees combined (37.6%) is close but does not reach theproportion of academics (40.5%, see Table 2, Section F). Among all governmentrespondents, those from municipalities are the most numerous (21.4%, see Table 2,Section F).

The ties of the respondents are principally directed to other government staff andacademics. The distribution of ties is not as strongly dominated by academics and bylocal government staff as the sectoral characteristics of the respondents suggest. Forinstance, the ties directed to academics comprise only 31.1% of the entire set of ties, even

though academics are 40.5% of the respondents (Table 2, Section F; Table 9, Section A).Similarly, the ties directed to local government employees are only 16.1%, compared to amuch stronger presence of such officials in the sample: 21.4% (Table 2, Section F; Table 7, Section A). Conversely, while industry employees as well as federal and provincialgovernment staff are a smaller proportion of the sample, they comprise a largerproportion of the ties (Table 9, Section A; Table 2, Section F). These findings suggestthat academics and local government staff have diverse networks that connect also toother government officials, industry practitioners, and members of non-governmentalorganizations (NGOs). The importance of academic and local government ties comesfrom their diversity as well as their sheer numbers.

This is consistent with the data about who works with whom. A cross tabulation of sectoral data and the direction of ties (Table 10) more clearly shows who works withwhom. Most of the ties of all respondents are within their own sector. This could only beexpected: government employees work mostly with government employees, academicswork mostly with academics and so on. Yet there are distinct patterns by sector.

Academics are the most inward-looking group; they have ties above all with otheracademics, in fact half of their ties are directed to other academics (Table 10). Far behindtheir ties in academia are their ties to the federal government (14.0%) and industry(10.0%, see Table 10).

Federal government staff is at the other end of the continuum. In fact, they are anexception: their ties with academics are more numerous than their ties with colleagues inother federal agencies, provincial or local government (Table 8). Local and provincialgovernment, industry and NGO employees are in between academics and federalgovernment: they work mostly with people in their own sector but are not as lockedwithin it as academics.

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Further, the distribution of respondents ties suggests that the ties of academics to othersectors are strongest in the federal government; academics are relatively weaklyconnected to provincial and local governments as well as NGOs. This is consistent withthe ties of the federal government and municipalities. Federal government staff isconnected strongly to academics. Local government, in turn, is connected to industry but

to a much less extent than to academics. NGOs have the most evenly distributed ties withvarious sectors. However, they are well-connected to industry but weakly connected tothe federal government (Table 10).

Summary

To summarize, academics and local government have strong presence in the area of waterand ties directed to them dominate the community. Since respondents from each sectorexcept federal government work mostly with their own sector, we can expect afragmentation of the community along sectoral lines. When academics do work on waterissues with partners outside academia, they work mostly with federal government.

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Part II: Connections in the Water Network

This section examines the connections in the water network as a whole. The discussionfirst examines the overall connectivity of the network and identifies the well connected

members in the network, those who are most central. The analysis then turns to theinternal divisions in the network drawing on clique analysis. The clique analysisdescribes the internal structure of the network, revealing sub-groups and connectionsbetween them. Finally, the discussion examines the ways researchers in the network citethe scholarly articles of colleagues. Citing other scholars can be treated as a specific typeof tie. The citation analysis, therefore, provides an additional avenue to examine theconnections among academics in the water network.

2.1. Centrality Analysis

Network centrality , the number of connections a person has in a network, is the most

common way to capture the connectivity of the overall network and the role of specificpersons in it. The more connections each member of the network has, the higher theconnectivity in the network. In highly connected networks, ideas travel quickly, membersinfluence each other strongly, and resources can be mobilized easily. In turn, individualswith many connections, or with high centrality, are well-positioned to collaborate orexchange information with others. For instance, network members who are central are oncommunication paths that keep them in contact with others in the network; they receiveinformation sooner than those who are less connected and benefit more fromcollaboration opportunities.

Further, respondents may be connected to others either because they work with them or

they may be connected because they exchange ideas with them. Respondents workingwith many collaborators may not be exchanging ideas with the same number of people,or they may be exchanging ideas with a very different set of people. The centrality of respondents is therefore calculated separately for working ties and for the ties that discussinnovative ideas.

In a network, people connect to others either when they initiate a contact or when othersseek them out and contact them. Thus, we can distinguish between two types of centrality. Outdegree centrality shows the extent to which a person is actively reachingout to others and initiating contacts with them. People with high outdegree centrality arethe active networkers . By comparison, indegree centrality shows the extent to which

other members of the network contact a particular person. People with high indegreecentrality have prestige and status; they can be considered the established experts in thenetwork. Both types of centrality reflect connectivity and are crucial for maintaining thenetwork. Whether reaching out or responding to others, centrally located individuals holdthe network together.

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Overall connectivity

The analysis suggests that the connectivity in the network is low 2. Centrality variesdepending on the particular measure (indegree or outdegree) and the types of tiesexamined (work ties or exchanging innovative ideas). The highest number of connections

a respondent has, for instance, varies from a mean of 6 (work outdegree) to 10 (work indegree). Yet in each type of measurement, only about a dozen respondents are linked tothe network by three or more ties. The network is sparse.

Why is the connectivity so low? These results should be viewed in the context of the wayresearchers work and the diversity of the water community. All the respondents report themost important professional ties they have with people working in the area of water.Thus, the survey captures relatively strong professional ties and people have few suchties. Previous research shows, and our interview data confirm, that academicswho arealmost half of the survey respondentswork closely with only a few colleagues. This isparticularly visible on large research projects; even when the project team includes a

dozen or more people, each project team member works closely with just a few people(see also clique analysis). These fewer but stronger ties are the type of ties captured in thesurvey. In contrast, the survey disregards weak professional ties. For instance, severalmembers of a large research project have filled in the survey and listed their strongprofessional ties. However, they do not work closely with each other, and the analysisfound no ties among them.

For non-academics (over half of the sample), such strong professional ties in the area of water are likely to be even fewer. The area of water is known for the breadth of issuesand the diversity of stakeholders in it. As some respondents indicate, water issues areeverybodys concern. The responsibility for policy and management in this area isshared by all levels of government and several agencies. A number of NGOs andindustries are also involved in water issues. The points of common interest among suchdiverse stakeholders are likely to be few; the practitioners are therefore likely to work separately from each other. In turn, their connections to academics depend on their joband the specific needs of their organization at the moment. For many of them, their mainwork responsibilities are unrelated to research activities and outside of the area of water.In short, the diversity of the stakeholders fragments the community and decreases theoverall connectivity. The results show that many of these non-academic respondents,especially those not involved in CWN, neither work closely together nor share ideas withothers in the water network.

Finally, the low connectivity in the water network is also affected by the fact that the 173respondents who filled in the survey are just a sample of all the people working in thearea of water. The analysis looks for connections among the 173 respondents who filledin the survey. Some respondents work and exchange ideas with collaborators in the area

1 Construction of the network data was derived from the survey results of personal networks in whichrelations with others in the water community were described. The connections of each respondent reportedhere are connections to the 173 people who filled in the survey. See Appendix 3 for details.

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of water, but their collaborators have not filled in the survey. Therefore, theseconnections are not reflected in the analysis.

In short, strong professional ties in the water network are likely to be few. The analysiscaptures this low connectivity. The sampling further emphasizes it.

Work centrality

Who are the most connected respondents in the survey and what are their connections?The discussion next examines those respondents who are better connected to others andare thus the most active in the water community. These are the respondents central to thenetwork.

The results of the survey show that the respondents most actively working with others arenot always those who most actively exchange innovative ideas (Table 11). The twogroups only partially overlap. Similarly, those who most actively contact others (high

outdegree) are not necessarily those who are most often sought out by others (highindegree); the two groups only partially overlap. This pattern of asymmetric ties, quitecommon for network studies, holds true for both working ties and sharing innovativeideas. That is why it is important to examine them separately.

About a dozen respondents are actively working with others in the water network, or theyhave high outdegree centrality (Table 11). These are the respondents who have stronginterest in collaboration and are focusing their networking in the area. The interview datashow that among those seeking out collaborators are several senior academics stronglyinvolved in CWN work; two of them are project leads. At the same time, some of theseactive networkers are junior researchers and outsiders not who are not currently involvedin CWN. In other words, the interest and focus on collaborators in the area is strongeramong junior academicsthose still building careers and expanding their personalnetworks.

The presence of outsiders is particularly interesting. The person who is most central of allthe active networkers is an outsider, a senior government official from the federalgovernment; he works with six other respondents in the water network. The presence of outsiders among the active networkers is a good indication of their interest incollaborative research and the potential for developing new connections.

Roughly the same number of respondentsabout a dozenare named as collaboratorsby at least three others members in the network (indegree). But this is a different group of people: only four of the people actively reaching to work with others are also amongthose most often sought by others; these four people do not have the highest indegreecentrality scores. In other words, there is a low overlap between the respondents withhigh outdegree and those with high indegree. If the first group of respondents with highoutdegree includes respondents interested in collaborative work, this second group of respondents with high indegree consists of experts with established reputations in the areawho are attractive collaborators for others. There are no outsiders among them. All but

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one are academics. About half of them lead CWN projects. The most central person(indegree ), named by 10 other members in the network, is the project lead of a largeCWN project.

Innovation centrality

The connections among respondents who exchange innovative ideas show similarpatterns to the connections among those working together (See Table 11). A small groupof slightly more than a dozen respondents is connected to the networks by three or moreties. Those who seek out others to share their ideas are not necessarily the recipients of such ideas; only five respondents with high outdegree also have high indegree. Notably,over half (7) of those who initiate contact to discuss innovative ideas are not academics:they are government, NGO and industry staff. Almost as many (6) are outsiders to CWN.These are people with ideas who seek out the experts in the water network. In contrast,the majority of the established experts who attract the interest and trust of others aresenior academics who lead CWN projects. All are involved in CWN.

Comparisons across type of ties and types of centrality

Comparing work ties with ties for exchanging innovative ideas shows that therespondents who actively contact others for work are often the same people who contactothers to share their innovative ideas with them. Alternatively, those who are named byothers as collaborators are often the same people with whom others want to share ideas.The overlap suggests that people behave consistently across their ties. Active networkerstend to be well connected in the water network because they both work and exchangeideas with others in the water network. Similarly, high status experts attract others as bothwork collaborators and consultants on innovative ideas. Where differences between work and sharing innovative ideas do emerge, it points to higher proportion of non-academicsand outsiders. Sharing innovative ideas, in other words, evokes diverse participants.

Summary of centrality analysis

In sum, the water network is only sparsely connected. Only a small group of therespondents (29) are better connected to the network, either because they initiate orattract connections by others. CWN members comprise the majority of these centralnetwork members (22) and therefore contribute most to the connectivity in the network.The respondents who hold the network together through their connections are dividedinto two relatively different groups. The active networkers, who are interested incollaborative work, include a sizable number of non-academics and people outside CWN.Young academics building their careers as well as some established academics are alsolooking for collaborators in the network. The presence of outsiders in the grouppeoplewho reach out to CWN researchersis evidence of their interest in the work of CWN. Bycomparison, the second group of central people who contribute to the connectivity in thenetwork by attracting others, or the established experts, are overwhelmingly CWNmembers and academics. Their centrality to others suggests the role of CWN in the watercommunity as a focus of expertise.

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2.2. Clique AnalysisUnderstanding how a network functions is impossible without examining the internalstructure. All networks have their own internal divisions and typically include severalsub-groups of people who are closely connected. In turn, sub-groups may be connected toeach other to a different degree. The number and size of the internal sub-groups as well

as their connections affect the processes unfolding in the network. They determine howinformation travels within the network or how resources are mobilized. For example, if anetwork consists of many small groups that are not connected to each other, informationand resources are not easily shared across the network. In such networks, informationspreads slowly and resources available in the sub-groups are not pooled together. Incontrast, if a network includes people who are members of more than one sub-group andthus can connect the subgroups, information and resources travel more easily across thenetwork. Information spreads rapidly throughout such a network, jumping from one sub-group to another with the help of overlapping members.

This section examines the results of analyses that identify a specific type of sub-group

within the networkcliques, or groups of individuals who are closely connected. Theymight be working together, exchanging information and ideas, or pooling resources. In allcases, they interact directly and are more strongly connected to each other than they areto the rest of the network. Clique analysis, in other words, identifies the groups of peoplewho are strongly connected to each other.

The analysis examined two types of cliques: cliques based on working ties, in whichmembers work closely with each other, and cliques based on exchanging innovativeideas, in which members extensively discuss their ideas. The results of the clique analysisaddress several questions: How many cliques of close collaborators and discussants arethere in the water network? How big are they? Who works with whom in a clique? Are

the existing cliques connected, i.e., are there individuals who are members of more thanone clique? Finally, do the people who work closely together also exchange ideas or dopeople work with some colleagues but exchange ideas with others? In other words, arework cliques similar to cliques discussing innovative ideas?

Work cliques

The analysis found 12 smal l cliques, or groups of close collaborators, in the waternetwork. Figure 1A and 1B 3 are sociograms of the work relations, i.e., they are visualrepresentation of the ties among network members who work together (Appendix 2). Thegraph includes 86 respondents who work with at least one other person in the network.

The analysis showed that these respondents tend to work closely with only one or twoother collaborators. There are many dyads but no groups of close collaborators that arelarger than three members. The small size of work cliques is consistent with thequalitative data on project practices. While projects may include numerous researchersand partners, most of them work independently from each other. Daily work is done in

3 All figures are in Appendix 2. Figure 1A and 1B both represent the same work relations; the symbols usedin Figure 1A indicate the sector of the respondents while the symbols used in Figure 1B indicate whetherthe respondents are members of CWN or outsiders.

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small groups of close collaborators. Researchers switch from one small group to anotherdepending on the stage of the project.

A dozen such three-member work cliques exist in the networks (Table 12). Half of therespondents involved in cliques (8) are members of more than one clique; three of them

are members of five or six cliques of closely related members. Because of theseoverlapping members, all 12 work cliques taken together include 16 people (Table 12).

In short, a small number of the active collaborators in the water network (16) areinvolved in closely collaborating groups. Such respondents always work with two closecollaborators in a group but are often involved in more than one group. These are theactive collaborators in the network. The rest of the respondents might have closecollaborators, but their close collaborators are either outside the water network or simplydid not complete the survey.

Who are the active collaborators in the network?

The majority of the 16 members of the existing work cliques are CWN members (13 outof 16) and academics (11 out of 16). More than half of them are over 50 years old andhave long work experience. In other words, the typical active collaborator in the waternetwork, as captured in the survey, is a senior academic with a lot of experience who isworking on a CWN project(s). However, five of the respondents who are closely workingwith others in the area of water, are employees from various levels of government. Whileacademics dominate, one third of the active collaborators are government employees.What is even more interesting, three of the government employees are outsiders to CWN.One of these outsiders, a federal government employee, is involved in three work cliques.This suggests that some of the key collaborators in the water network are outside CWNand that there are still important partnerships to be built between CWN and the federalagencies.

Who works closely with whom in a clique?

Who works closely with whom is the next key question in understanding the network. If academics work with each other, or government employees keep to themselves, or work cliques are drawn by a single discipline, this tell us that their research is hardly cross-sectoral or multidisciplinary. A closer look inside the work cliques reveals, however, thatthe opposite is the case.

The analysis showed that work cliques in the water network cut across sectors anddisciplines. In other words, collaborative research in the area of water tends to be cross-sectoral and multidisciplinary. This finding is all the more significant since the work cliques include only three members. Despite this, cliques bring together collaboratorswith diverse backgrounds.

Table 13 shows that more than half (7) of the work cliques are cross-sectoral; theyinclude two academics and a non-academic (#1, #3, #5, #9, #10, #11, #12). The non-academic collaborators are government employees at the three levels of government.

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Most of the collaboration, in other words, takes place among academic and governmentemployees. The most sought after collaborator is a federal employee: he is a member of three different cliques, each in a different part of the country. Since he is also the outsidermentioned above this result reinforces the idea that there are untapped connectionsbetween CWN and the federal government.

Equally important, the composition of the work cliques is multidisciplinary, with a heavyrepresentation of biology, followed by earth/environmental science/geology, andengineering. By contrast, there is a poor representation of social sciences (Table 13). Theanalysis found that none of the work cliques draws its members from a single discipline.Instead, virtually all work cliques are multidisciplinary; in half of them each membercomes from a different disciplinary background.

Biology is the most prominent discipline in the network. Two thirds of the cliquesinclude at least one biologist (#3, #4; #5, #6, #7, #8, #9, #11); all of them include either abiologist or an epidemiologist. In several cliques, two of the members are biologists. As a

result, in most of the work cliques, members are involved in research projects related tobiological issues.

There are four to five biologists who participate in the work cliques (four biologists andone microbiologist). Two of them are much more active collaborators: they are involvedin five and six cliques respectively. Both of them are CWN members who have beeninvited to participate in a number of research projects. It is through their collaborativework that biology takes such a central place in the work cliques.

The next two areas that figure prominently in the work cliques are earth/environmentalscience/geology (multidisciplinary by nature) and engineering. Two thirds of the cliquesinclude earth/environmental scientists (#1, #2, #4, #5, #6, #8, #9, #12). There are fivepeople with earth/environmental sciences backgrounds who participate in the work cliques. None of them, however, is a member of more than two work cliques; they do notcontribute to the same extent as biologists to the water network. Engineering isrepresented in half of the work cliques (#1, #2, #3, #10, #11, #12) even though there areonly two engineers. Both of them participate in several cliques, ensuring the highrepresentation of their discipline.

The social sciences are not well represented in the work cliques. Out of the 12 existingcliques, only three contain a single collaborator with a background in social sciences (#3,#10, #7). They collaborate with biologists and engineers. Each of the collaboratorsageographer and two economistsparticipates in a single clique.

The cliques in the network are various configurations drawing on these three populardisciplines. The most common combinations include epidemiology, biology andenvironmental sciences, or biology with environmental sciences and engineering. Forinstance, one of the well-connected researchers is an engineer who appears in threecliques along with a biologist, epidemiologist, and environmental scientist.

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In short, there is no doubt that the active collaborators in the water network, most of whom are CWN researchers, are doing cross-sectoral and multidisciplinary research.They work closely with government employees (although some of their partnerships areoutside CWN) and collaborate with other academics outside their own discipline.However, the disciplines from which they draw their collaborators are limited and social

sciences are underrepresented in the collaborations.

Are the work cliques connected?

It is important to examine the connections among cliques. Without such connections, thelarger water network would be only a collection of independent groups, in whichmembers work only among themselves and do not have common work interests. Giventhat the work cliques are quite smallonly three memberssuch a situation would meanthere was a very limited circulation of information and resources within the largernetwork. In turn, with only a few connections among the cliques, the network would bevulnerable to slipping back to a disconnected state. If only a few members collaborate in

several groups, all these connections would be removed if they were to leave the network.The analysis showed that eight of the active collaborators in the network are members of more than one work clique. In other words, there is a significant overlap in themembership of the work cliques and this ensures that many of the work cliques areinterconnected. This suggests that active collaborators in the network have common work interests that link them together in various configurations. Further, the activecollaborators contribute to different degrees to these interconnections. Three of them areinvolved in as many as five or six work cliques while five other collaborators are in twoor three work cliques. The remaining eight participants in work cliques are working withmembers of only one clique.

In short, there are connections that cut across the work cliques and hold the overall waternetwork together. People working in the area of water are thus a network and not acollection of independent groups. Yet the people contributing to these integrativeconnections are relatively few. Among them, an even smaller number contributesdisproportionately to these connections. While for the active collaborators themselvessuch connections mean access to resources and information, for the network as a wholethis dependence on a few key participants reveals a weakness.

What brings work cliques together?

How active collaborators come together to create work cliques is important not only forthe understanding of the network but also for possible interventions in the network. Thisis not a matter that the survey can answer. However, documents and interview dataprovide some clues.

About one third of the work cliques identified in the analysis are most likely based onCWN projects. Such work cliques consist of people who work together on the sameCWN project (Cliques #2, #4, #8, #5). Most of them include the project lead, senior

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researcher, or partners. These groups of collaborators have come together because of theirCWN project. To put it differently, in these groups the membership in the work cliques isa function of the membership in CWN.

A surprisingly sizable number (6) of work cliques, however, includes two academics

working on the same CWN project and a government employee who is not formallylisted as a partner on their project (#1, #3, #9, #10, #11, #12). It is unclear in these caseswhether members work together on a CWN project or on a project funded by a differentagency. In the first scenario, it is possible that the third member of the clique, thegovernment employee, may not be listed as a partner on the CWN project for reasons of authority. The formal proposals often include high ranking contact persons from thegovernment who do not necessarily do the everyday work. In contrast, the clique analysiscaptures the government employee who works on a day-to-day basis with the academics.Personnel changes in the government can also change the members of a work cliquewithout changing the nature of the partnership and the collaborative work.

Alternatively, in the second scenario, the members of the clique are working on a projectunrelated to CWN. Their relationship goes beyond CWN. It is not clear which of the twoscenarios corresponds to reality in each of the cliques with such composition. In bothcases, however, the active collaborators demonstrate a commitment to cross-sectoralresearch and solid connections to the government.

Finally, a third set of work cliques cuts across projects; it includes members from twoCWN project teams (#6, #7, # 9). Such groups most likely work together on projects notfunded by CWN. They extend their collaborative relationship across several projects.

This is consistent with what the interview data reveal about the way researchers work together. Researchers are typically involved in several projects and thus work withcollaborators from several formal work groups. At the same time, most researchersconsciously build a group of close collaborators, and they invite them to participate inmultiple projects. This is particularly true for senior researchers. Their close collaboratorsget involved in different configurations, and in several projects. Collaborative ties withthem transfer across several formal projects.

Summary

To summarize, the membership in a work clique does not closely follow CWN projectteams. While the majority of active collaborators in the water network are CWNmembers, they are not necessarily working on a CWN funded project. These resultsreflect the fact that research in the area of water is funded by many agencies includingCWN. The collaborative ties in the water network do not all arise in CWN projects andare not entirely dependent on the work of CWN. These results are consistent with theexistence of active collaborators outside of CWN.

On the other hand, CWN plays a crucial role in the water network; the majority of theactive collaborators in the network, and certainly all of the academics among them, are

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CWN members. Whether CWN attracted active collaborators or, alternatively, helped itsmembers expand their collaborative ties (interview data suggests that both processes aretaking place), it has been able to link those academics who are interested in collaborativework in the area of water.

Innovation Cliques

Innovative ideas can be interpreted as a distinct resource in networks. The way thatinnovative ideas travel in a network does not necessarily follow work ties. In some cases,collaborators are experts with complementary expertise who can bring a fresh look to anissue; in others, they are close collaborators who act as sounding boards. In such cases,collaborators from a work clique not only work together but also exchange innovativeideas. Work cliques coincide with the innovation cliques.

Yet there are also good reasons to expect differences between the two types of cliques.Innovative ideas are often cross-sectoral in nature. Further, people outside ones own

work group and outside ones own discipline can bring unexpected ideas. We wouldexpect, therefore, exchanges of innovative ideas to occur more across sectors anddisciplines.

How do work cliques and innovation cliques in the water network compare?

Figures 2A and 2B present the innovation exchanges in the network 4. The clique analysisfound 12 small innovation cliques with three members each (Table 14). Despite theopportunities for different networks, in practice, most of the cliques coincide with work cliques (#1, #2, #3, #5, #7, #10, #11, #12). Just a third of the cliques contain one or twonew members (#4, #6, #8, #9). In other words, respondents not only work with their closecollaborators but also discuss their innovative ideas with them. Nonetheless, there aresome interesting differences between innovation and work cliques.

Who exchanges ideas with whom?

Compared to work cliques, the data in Table 14 reveal that the participants in innovationcliques have fewer outsiders (2 out of 19) and more non-academics; almost half of theparticipants are outside academia (9 out of 19). Such changes in the background of theparticipants in innovation cliques can be expected; the sharing and implementation of innovative work and ideas involves collaboration between academics and non-academics,whereas collaborative research work is more limited to ties among academics.

What is perhaps unexpected is that the non-academic participants in the innovativecliques are somewhat different than those in work cliques. Innovative cliques, non-academic participants are more evenly distributed across various sectors: there areemployees from the federal government (2), provincial government (1), local government

4 Figure 2A and 2B both represent the same innovative relations; the symbols used in Figure 2A indicatethe sector of the respondents while the symbols used in Figure 2B indicate whether the respondents aremembers of CWN or outsiders.

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(1), as well as representatives from industry (2) and NGOs (2). Notably, some of the localgovernment participants from work cliques are not present. Thus, industry and NGOrepresentatives not present in work cliques become members of innovation cliques.

Disciplinary characteristics of the innovation cliques also slightly change compared to

work cliques. Biology retains its prominence: just as in work groups, two-thirds of thecliques include a biologist and some are entirely based on biologists. However, the role of environmental sciences and engineering decreases. The number of social scientists in thegroup slightly increases due to the participation of more non-academics from governmentand NGOs.

Are innovation cliques connected?

Connections between such innovative cliques are especially important since suchconnections facilitate the spread of ideas in the larger network. Yet it is much easier toshare ideas with only close collaborators.

The analysis shows that the innovation cliques are connected albeit to a lesser degreecompared to work groups. Out of 19 participants in innovation cliques who exchangeideas, five are involved in two cliques. An additional two are involved in five and sixcliques respectively. With a few exceptions, the clique members who connect theinnovation cliques are the same clique members who connect the work cliques in thenetwork. In other words, respondents who are most actively working with collaboratorsfrom different work groups are also most actively exchanging innovative ideas with theircollaborators from different groups. It is significant that the two members involved in thehighest number of innovation cliques are the same two members involved in the highestnumber of work cliques. Since they are both biologists, they reinforce the centrality of biological sciences in the innovation network.

Bridges: Who are the people connecting the cliques?

The analysis of cliques showed that some respondents are members of more than onegroup. Two of them are also cutpoints in the data, meaning they are central to both thework and innovation networks, connecting and acting as bridges between cliques (thepeople identified as 146; 122, Figures 1 and 2). Such network members are known asbridges connecting otherwise disconnected groups. People in such positions act asinformation or resource brokers and boundary spanners within the group. They are a keyto the health of the network; their removal could result in fragmentation of the network.

Demographic information, as well as the clique analysis and centrality scores, canidentify who are the important bridges and how they behave in the network. The tworespondents in bridge positions are academics in mid-career. Both are biologists, the mostprevalent discipline in the network. Both work on a CWN funded project although neitherof them is a project lead. In other words, they are not junior researchers; they have hadtime to develop their professional ties in the network. Neither are they among the mostsenior members of the network who have less time for networking, get more easily

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funded by various agencies, and work on many projects whose participants may beunconnected to CWN.

The clique analysis also shows that the two bridges work and exchange ideas withacademics and partners across the country, i.e., they have developed broad networks of

distant collaborators and partners. Quite likely, in addition to their CWN project, theyhave research projects not funded by CWN. In turn, centrality analysis shows that theyare among the few people who both reach out to others and are named by others whowant to collaborate and exchange ideas with them. Their indegree and outdegreecentrality scores are quite similar.

Finally, they are involved not only in CWN but also in other organizations in the area of water. There is a significant overlap in the membership of the two organizations. Thishelps them develop and strengthen their ties to other researchers in the area.

Summary

Several findings emerge in the clique analysis. First, the research taking place in thenetwork is cross-sectoral and multidisciplinary. The composition of the work andinnovation cliques bears evidence to that. The finding is all the more important given thesmall size of the cliques.

Second, CWN plays a central role in supporting these partnerships and research althoughit is not the only player in the area of water. The clique composition shows that it is CWNmembers and especially academics who dominate research collaboration. Not all of theirwork is on CWN projectsother funding agencies also support such complexcollaborationsbut CWN members are always a strong presence in these collaborativegroups. Work and innovation cliques have similar memberships, although outsiders aremore active in exchanging innovative ideas than in work cliques.

Third, clique analysis confirms the opportunities for expansion of CWN memberships ingovernment and industry. Outsiders from industry, federal and local government arealready collaborating and exchanging ideas with CWN academics. This is consistent withthe centrality analysis which shows industry and government employees activelyreaching out to the networks. In this respect, the federal and provincial employees areparticularly active. Notably, the analysis of personal level networks (Table 10) confirmsthat the largest proportion (26%) of the ties of federal employees is directed to academicsin universities and not to people in their own sector. The interview data also show thatsome federal employees feel an affinity to academics. In short, if local governmentemployees are already involved in research and exchanging ideas, federal employeesseem to be the most important, albeit not the only, untapped resource for expandingCWN.

Finally, the analysis suggests two weaknesses in addition to the overall low connectivitydiscussed in the previous section. Multidisciplinary research draws on a limited range of disciplines; biology dominates collaboration, followed by environmental science and

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engineering, while social sciences are not well represented. Next, there are only twosignificant bridges in the network, making it vulnerable to changes.

2.3. Citation analysis

Citation analysis is a technique that examines how scholars cite each other. Citinganother scholar is interpreted as a specific type of tie. A group of authors citing eachother is thus seen as a network of scholars who have common interests, work in the samearea, and read each others publications. In a university environment, publicationsmeasure the value of academic work and citing is the most common recognition of thisvalue. Citation analysis therefore captures the most significant as well as the mosttraditional professional tie among scholars.

The discussion below presents the result of citation analysis for a small group of 31scholars 5 . Applied to CWN members, citation analysis can show whether scholars in thenetwork are connected by this traditional professional tie. The analysis can tell a lot about

what is happening in the network by answering questions such as: do scholars in thegroup cite each other? In other words, does their collaboration end with the report for theproject or do they continue to follow each others publications? Citing indicates that theirpublications are related and relevant for their colleagues. Who are the most often cited?In others words, who are the most visible and influential scholars? Alternatively, whocites others most often? Such scholars are familiar with the work of their colleagues andare able to link it to their own work.

Citation analysis is particularly important for the CWN by revealing who cites whom in agroup of scholars and thus mapping the internal structure of the group. Combined withinformation on the disciplinary background of scholars, this can show whether scholars

from different disciplines work on common issues and find each others publicationsrelevant in their own work.

The analysis includes several types of measures, each of which examines a distinctcitation behaviour and adds to our understanding of the network. The first measure is

cocitation, or how many times any two authors in the group are cited together by anyonein any field, whether in the group or not. It is a pairwise measure. Repeatedly cocitedauthors are perceived to work on related issues; their work is either similar orcomplementary in some respect. Cocitation captures opportunities for collaboration.

By comparison, intercitation shows how many times scholars from the selected group

cite each other directly. The role of a scholar who frequently cites others in the groupdiffers from that of the scholar whom others frequently cite. Scholars who cite others inthe group are familiar with their work, find it relevant to their own, and recognize its

5 Citation analysis is only feasible for small groups. This analysis includes the 31scholars who are amongthe most central people in the network. Compared to the group of people who are central in working andexchanging ideas, this 31-member group excludes respondents outside CWN. Details of methodologicalissues are available in Appendix 5.

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importance. Senior scholars citing others act as integrators of the intellectualcontributions of their colleagues.

In contrast, scholars who are widely cited have prestige and influence with theircolleagues but may not be citing them; they may not even be familiar with their

colleagues work at all. Such scholars are thought leaders in the group.

Intercitation thus includes two separate measures. The first captures the instances inwhich a scholar cites others in his or her gro up. The second captures instances in which ascholar is cited by others in his or her group 6 .

Centrality of Authors in Citation Networks: Do Scholars Cite Each Other?

The scholars included in the citation analysis are all members of CWN and represent overa dozen CWN projects. Most are either biologists (10) or earth scientists (7); the rest arealmost evenly distributed among chemistry, health, engineering, geography and business.

The multidisciplinary composition of the group makes dense citation within the groupunlikely.

Most scholarly journals publish work in a single discipline and their criteria foracceptance reinforce disciplinary boundaries (Section 2). Citing the scholars you work with cannot be taken for granted: even for people working in multidisciplinary teams,publishing and citing can fold back within ones discipline to increase the likelihood of publication. Citing, therefore, is the most rigorous test for the existence of cross-disciplinary connections. At the same time, citing across disciplines may stronglyindicate the interdisciplinary nature of the work being done in the group.

Do scholars cite their colleagues?

The analysis suggests several salient patterns. First, scholars in the group do not cite theircolleagues very often. Citations within the group are not frequent and connectivity in thecitation network is low. This is consistent with the low connectivity found in the survey.To be sure, the majority of the scholars are in some measure connected to the group: theyare cocited with others in it, and they cite or are cited by others in it (Table 15). However,most of the citation counts are small and some scholars neither cite nor are cited withinthe group. Individual scholars, though, differ considerably in terms of citation.

Second, the scholars in the group are more often cited together (cocitation) than they citeeach other (intercitation). Almost everyone is cocited with at least one other groupmember: there are relatively few zeros indicating that the scholar has not been cocited atall. This suggests that the work of the scholars in the group is perceived as having acertain measure of coherence; they are seen as working on the same issues.

6 These measures are similar to the centrality measures in any other type of tie and have already been usedin Section 4 to show the active networkers (outdegree) and established experts (indegree).

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Table 15 compares the number of other persons in the group that each member is cocitedwith (Cocite Degree), the number of persons each cites (Intercite Outdegree), and thenumber each is cited by (Intercite Indegree). Values above 4 are shaded. Intercitationamong members is responsible for some of the cocitation they receive. As indicated bythe zeros, two scholars in the group have not been cocited, and four neither cite nor are

cited by their colleagues. This is consistent with the diverse disciplines from which thescholars in the group come.

In sum, scholars in the group do not cite their colleagues very often. While they can seethe connections between their work and the publications of a few other colleagues, theyhave trouble relating most of their colleagues publications to their own research.

Cocitation Centrality: Who is most frequently cited together with other colleagues?

As noted, cocitation refers to the instances in which pairs of authors are cited together byany citer in any field. Scholars with high cocitation scores usually write on similar topics

and use methods in common. Almost all of the scholars in the group are cocited with atleast one of their colleagues, and one is cocited with 11 others (Table 15) . Suchdifferences may be linked both to individual characteristics, such as the career trajectoryof the scholar, and to contextual characteristics, such as the disciplinary composition of the group and the established practices in it.

When the articles that cocite pairs of CWN authors are counted, the analysis shows thatthe scholars who are most often cited together tend to be biologists and earth scientists.The top scholar on the list, who is cocited with other group members in a total of 60articles, is a biologist, works in large projects, and participates in more than one CWNproject. Participating in several projects underscores the fact that his work is related andfits well with the work of his colleagues. The centrality analysis in Section 2.1 shows thathe is often named by others as a collaborator and a person with whom others want toshare ideas. His project participation reinforces his visibility in the group, makes him afamiliar name to others, and increases the likelihood that that his work will be seen asrelated to the work of other colleagues.

Yet, this is not the full explanation: there are other scholars who are also senior andparticipate in several projects but are not cocited so frequently. To understand better whatis happening, the analysis needs to take into account the broader characteristics andinternal structure of the networks. The discussion turns to the question of particularauthor pairs.

Cocitation Map: Whom are they cited together with?

Figure 3 is a map of the cocitation links that shows which scholars are cited together. Alink between any two scholars indicates that they have been cocited in at least one article.The thickness of the link indicates the frequency of cocitation: scholars joined withheavier lines are cocited in many more articles than those with lighter lines. The heaviest

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link is between a pair of authors who were cocited in 23 articles. Disciplinary backgroundis indicated by colour.

The map shows that the central people are cited together with scholars from severaldisciplines. For instance, one of the two most central people is cited together with

biologists, engineers, chemists, and health scientists. This is what leads to his centrality.The second person is cited more often with people in his own discipline, but there is stilldisciplinary diversity. This pattern of diversity is common for many of the scholars, eventhough they are less frequently cocited.

Figure 3 shows an internal structure in the group that further suggests patterns of cocitation across disciplinary boundaries. The cocitation map indicates that scholars tendlink up in groups of three. The majority of these groups are composed of authors fromdifferent disciplinary backgrounds. In other words, their works are perceived as relevantto issues in several other disciplines and cited together. This pattern is an indication of themultidisciplinary relevance of the publications of these scholars.

On the other hand, several patterns suggest the impact of disciplinary boundaries. Someof the scholars, who are cited together, include only biologists (#164, #122, #152) or onlyeconomists (129, 126, 149). Some of the biologists have very strong connections amongthemselves. Scientists in economics, geography, and health tend to be at the periphery of the network. In short, while there are many cross-disciplinary connections, disciplinaryboundaries remain important.

These patterns suggest an interesting dynamic of the disciplines in the group, bestillustrated in a comparison between biology and economics. Biologists are the mostnumerous in the group of scholars included in the citation analysis. They dominate thework cliques (Section 2.2) and are highly visible in the network. Given this wideparticipation and visibility, it is easy to perceive their publications as relevant to manydisciplines; biologists are therefore often cited together with scholars from otherdisciplines. At the same time, the sheer numbers of biologists is a temptation to citebiologists only. This accounts for the strong cocitation links between several of thebiologists in the group.

In contrast, social scientists are not well represented in the group included for citationanalysis. They are less central in work cliques and less visible (Section 2.2). Otherscholars have trouble finding the links between a social sciences discipline such aseconomics and others more popular in the CWN disciplines. Economists, therefore, tendto be cited together with other economists; their participation in cross-disciplinarycocitation is very low.

In short, cocitation suggests that, with a couple of exceptions, all scientists are perceivedas having at least minimal ties with colleagues in the group. There is a perception thatscholars in the network work on common issues. Working actively in the network facilitates such perception of relevance but it is not the only factor that affects it.Individual participation in CWN projects interacts with discipline to determine who is

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most visible and most often cited with others. Further, cocitation indicates many cross-disciplinary connections, but also that disciplinary boundaries remain important. This isparticularly important for the social sciences and to some extent for the health sciences,which remain locked in their own disciplines.

Intercitation Centrality: Who cites other colleagues?

Intercitation occurs when scholars cite each other directly. Scholars who often cite theircolleagues within this set are familiar with their publications and recognize theirrelevance and importance. Typically, they may be junior to these colleagues and areciting to establish the credibility of their own work. However, there are no junior scholarsin the CWN group. All members are well-established in their careers and are oftenleading scientists in their disciplines. This, together with publication pressures to citepeople within ones own discipline, is part of the explanation why there are relatively fewinstances in which scholars in the group cite their colleagues, despite the manyopportunities to do so.

The more interesting finding is that in this group, scholars who cite their colleagues mostfrequently are not juniors. The person who cites group colleagues in the most articles isindisputably a senior scholar (127). He is also actively working and highly visible inCWN. He has cited colleagues in 48 articles. (By contrast, seven scholars in the grouphave not cited anyone at all.) The average outcitation score is 6. Notably, the next personon the list, who has cited others in 22 articles, is also a well-established scientist. Thesescholars are not only familiar with the work of their colleagues, but are also able to findthe connections between the work of others and their own. They synthesize and integratediverse contributions. Figure 4 shows that the scholar on the top of the list cites not onlycolleagues from his own discipline (biology), but also colleagues from several otherdisciplines. In short, he integrates the intellectual contributions of the other scholars inthe group.

Who is cited by colleagues?

In contrast, scholars who are cited by their colleagues are visible and influential. Thisdifferent role in the group is played by different people. Despite some overlap, thescholars who are cited by colleagues in the most articles are not the scholars who mostoften cite colleagues in articles of their own.

The person most often cited by others in this group is, not surprisingly, another biologistin a senior position who is actively involved in CWN (164, Figure 4) . He is highly visibleamong colleagues, often being named by them as a collaborator and as a person withwhom they want to share ideas (Section 2.2). They cite him much more often than othermembersin some 48 of their articles. (That his 48 incitations match the other leaders48 outcitations is a coincidence.) Although he is cited by scholars in his own discipline,scholars from different disciplines also cite him (Figure 4). In other words, they find hispublications relevant in their own worka strong recognition of his importance. (He isalso the group member most highly cocited with other members.) This scholar, hence, is

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in a position to influence his colleagueshe is a thought leader . His closest competitorin this role is cited in 17 articles. The average number of articles in which the group citesa member is 6.

Thought leaders are all the more important because being cited by colleagues does not

happen very often: while these scholars are leading scientists in their areas, publicationcriteria strengthen disciplinary boundaries and limit within-group citations. Thiseliminates one of the major channels for influence among scholars. Moreover,disciplinary boundaries are reinforced by organizational boundaries, which furtherdecrease opportunities for influence.

Who cites whom? Who is cited by whom?

The two scholars leading the intercitation lists in sending and receiving citations are bothconnected to colleagues from different disciplines. Is this pattern of citing acrossdisciplinary boundaries common for other members of the group? In other words, dointercitation patterns indicate multidisciplinary connections?

Figure 4 maps the structure of the intercitation connections in the group. Direct citation isless frequent, and more scholars become disconnected from the group. The remainingconnections are quite similar to the cocitation

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