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Jointly published by Akadémiai Kiadó, Budapest Scientometrics,
and Kluwer Academic Publishers, Dordrecht Vol. 52, No. 3 (2001) 365–377
Feature report
Reflections on scientific collaboration
(and its study): past, present, and future
*
D
ONALD DE
B. B
EAVER
Bronfman Science Center, Williamstown, MA (USA)
Personal observations and reflections on scientific collaboration and its study, past, present,
and future, containing new material on motives for collaboration, and on some of its salient
features. Continuing methodological problems are singled out, together with suggestions for future
research.
Introduction
Derek J. deSolla Price, Eugene Garfield, Henry Small, and Belver Griffith, among
others, the real pioneers of the systematic study of collaboration in scientific research, as
well as early and fundamental contributors to the creation of scientometrics, have left a
lasting legacy. Forty years after their groundbreaking work, a large and growing number
of scholars spanning the globe and four continents follow in their footsteps, extending
and expanding what we know about the structure and dynamics of collaboration.
In particular, it is significant to have so many researchers at work in China and India,
representing a third of humanity, and, presumably eventually a third of all scientific and
technological research. It is a truism in the history of science and technology that no one
region, nation, or civilization remains the center of creativity and activity for long. One
need only think of the historical path of science through Mesopotamia, Greece, Islam,
the Medieval Latin West, Northern Europe, the United States and Soviet Union, to grasp
the point.
*
Keynote speech presented at the Second Berlin Workshop on Scientometrics and Informetrics /
Collaboration in Science and Technology and First COLLNET Meeting, Sept. 1, 2000, Neuen Hohendorf,
Germany
0138–9130/2001/US $ 15.00
Copyright © 2001 Akadémiai Kiadó, Budapest
All rights reserved
D.
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: Reflections on scientific collaboration
In that regard, we stand at the beginning of what appears to be another important
transition in the leadership of science and technology, in the history of civilization. An
international view is even more important than before, because the world as a whole,
and the research world of science and technology with it, is undergoing a major
transformation, the exact dimensions of whose nature and future are not yet clear, and
may not be for decades. As globalization and internationalization continue, on the way
to the formation of a global community, emphasis on cooperation and group life become
an increasingly common counterpoint to an existing emphasis on competition and
individuality. What the eventual balance will be, or should be, is not ours to tell, even
though the change involves the familiar age-old problem of finding a balance between
the individual and society.
Situated as we are then, in the midst of an important transitional period, it is
appropriate to take stock of the past and the changing present, to reflect upon the study
of scientific collaboration.
Structure
The following remarks offer a series of personal observations and reflections on
scientific collaboration and its study, past and present, and make a few tentative
observations about the future (not many, because the future is so uncertain).
Occasionally, I hope to single out areas where there are continuing methodological
problems, as well as even suggest future areas for research. What follows falls into three
parts:
1. The Past
a. A review of Beaver and Rosen, 1978-79;
b. Teamwork (Big Science) differs from collaboration (little science);
c. Changes in collaboration resulting from changes in research organization.
2. The Present
d. Collaboration from the researchers’ viewpoint(s).
3. The Future
e. Remarks on email, and the world wide web.
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Studies in Scientific Collaboration, [1978]
Using bullet points, let me briefly summarize the chief unusual or novel findings of
the 1978 papers, published by Richard Rosen
*
and me (
Beaver
and
Rosen
, 1978; 1979)
• Collaboration was almost exclusively by French chemists in the period
1800–1830.
• Collaboration grew slowly until World War I, after which it grew at a much more
rapid rate.
• The statistics of collaborative authorships follow a Poisson distribution,
signifying a relatively rare event, gradually tending to a negative binomial
distribution as collaboration became more frequent.
• The MODE of coauthorship was 2. (It still is today, especially if one counts
laboratories instead of individual coauthors.)
• A collaborative first paper meant later above average productivity.
• Core journals have higher frequencies of collaborative papers than the average
journal.
This last point is the basis for an important caution about research methodology in
studies of scientific collaboration. Although the simplest procedure for obtaining a data
sample is to use the ISI database, or to do a select sample of a few core journals, such
journals are unrepresentative of the whole. Scientists themselves are generally unaware
of the differences among journals, taking as their models the key journals in their fields.
Core journals form a small yet visible elite, and, as such, display characteristics of the
scientific elite, which may be several generations in advance of the whole of science,
speaking socioculturally about research practice. Looking primarily at core and
prestigious data sources will bias one’s picture; studies concentrating on such data need
to qualify their results accordingly.
From collaboration to TEAMWORK [1984] (Beaver, 1984)
• Discontinuity in the organization of scientific research: from little science to Big
Science, ca. WWII.
• Teamwork, or giant collaborations multiply after WWII: high energy physics
(HEP) is the exemplar.
*
Richard Rosen was a student of mine in the late 60s who went on to study with Robert K. Merton at
Columbia University, receiving a master’s degree in sociology. Today he lives in New York City with his
family, and is self-employed, no longer in academia.
Scientometrics 52 (2001)
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• Coauthorships in giant collaborations (teamwork) follow a power law
distribution, different from the Poisson characteristic of “traditional” small
collaborations.
• There is no simple distribution making the coauthorship distributions of
teamwork
continuous with those of small (N
≤
5)
collaborations
. Whether a
general distribution exists remains a puzzle.
Speaking of statistical puzzles, one of the puzzling statistical features of
communication in the sciences is one noted in the 1960s that to a first approximation, as
measured scientometrically, formal communications amongst scientists are random.
That research indicated that the Signal to Noise (S/N) ratio in scientific communication
was very small (the almost universal complaint of scientists that most of the literature is
garbage may seem to confirm that finding). But we might extend that research to
collaboration insofar as it reflects communication in science. Then, presumably there,
too, the majority of collaborative relationships are also random. Yet it is clear that at the
individual level, collaborations and communications are made with purpose and
intention. How is it possible to produce such randomness out of so many purposeful,
(one might even say causally related) decisions to communicate or collaborate? A
satisfactory resolution of the puzzle might have important implications for the analysis
and description of science, and of other social structures in which an apparently high
degree of stability and order is maintained by a relatively small set of practices.
• Teamwork, or giant collaborations, represents a
new paradigm
for the
organizational structure of research.
• Teamwork has spread from HEP, most notably to molecular biology and
biomedical research. See, for example, the human genome project (HUGO).
The changing organizational structure of research
Over the past few years, Henry Etzkowitz, among others, has been gradually
constructing a new view of the organization of scientific research more consistent with
Big Science, in which the research scientist plays the role of entrepreneur. Because the
research carried out in such a style of scientific organization is almost wholly
collaborative, the implications of how that organization is implemented in the laboratory
are directly relevant to undestanding collaboration in research. What follows briefly
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Scientometrics 52 (2001)
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outlines the advantages and disadvantages of that organization, both as reflected in
Etkowitz’ work, and as supplemented through interviews with some of my scientist
colleagues.
The typical group
structure
at a major research university consists of:
A Principal Investigator (PI), together with postdocs, graduate students, (and perhaps
undergraduates) -or- A senior professor, perhaps an assistant or junior professor,
postdocs, graduate students, (and perhaps undergraduates).
Salient Advantages:
Efficiency, Power
“Many hands make light work.”
• Multiplicity of projects optimizes chances for funding, for obtaining
support for the lab and continuing research.
•“A stable of graduate students is a power booster.”
*
Speed
• Like the advantages, in some cases, of parallel processing. Can
parcel out parts of a problem, and finish more rapidly than one’s
competition.
• Students are already trained, OR, the seniors train the juniors. Lab
leader freed from the time it takes to train new researchers.
Breadth:
• Can tackle broader, more encompassing problems, “more exciting
things.” Consequently enhances visibility and feedback at meetings.
For example, paraphrasing a geologist at Williams College, “I can put one student
into the field for the summer, 3 months. After 5 years, I’ll have enough data to produce
a research publication. A large research group can put 5 students in the field for the
summer, 3 months. But in 3 months, the research group already has the data for a
publication.”
**
Synergy
• Multiplicity of viewpoints energizes and excites participants. Makes
actual work more intense.
Reduced Risk
[“Don’t place all your eggs in one basket.”]
• Can have several projects going simultaneously; increases chances
of success, and successful re-funding.
*
Science Professor, Williams College, private communication, August, 2000.
**
Science Professor, Williams College, private communication, August, 2000.
Scientometrics 52 (2001)
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Flexibility maintained
• Can have one project of a “far-out,” speculative, and prospective nature.
• Failure does not destroy the laboratory. Success may open up new
directions, funding sources that accrue to pioneer leaders of new
successful research program.
Accuracy
• Errors are more readily detected when several different individuals
with different perspectives discuss or argue about data and/or theory.
Another way to view this is that in collaboration, the “context of
justification” becomes to some extent part of the “context of
discovery”, or that a large collaborative group partly embodies the
valuable and ongoing process of intersubjective verifiability.
Feedback, Dissemination, Recognition and Visibility
• Participants can present preliminary findings at many different
colloquia or conferences and get response from their colleagues.
They can more widely disseminate their findings, and lay claim to
their piece of the research turf.
Disadvantages
Individuals’ invisibility
• Most participants are invisible, in a formal sense, to the larger
research community. They are just “names” on a paper, “fractional”
scientists, essentially anonymous.
PI loses touch with direct research
• Reduces creativity inspired by directly acquired tacit knowledge of
how things work in practice.
• Loses ability to be a bench scientist.
• Diverts creative talents to administration, competition for limited
resources, rather than actual research.
Privatization of Research harmful to research ethos
• Creation of entrepreneurial fiefdoms may promote tempting negative
strategies, especially secrecy or additional limits on the free sharing
of ideas and materials in research.
• Cooperation with other laboratories (competitors) may be for
purposes of cooptation or espionage, practices potentially harmful to
science. Even if for the more positive purpose of alliance,
competitive advantage may deter “smaller” laboratories or
individuals.
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It is an open question whether and how such an organizational style can long
continue, given individual’s self-interest in obtaining recognition of their own creativity.
Note that viewing collaboration primarily from a laboratory perspective creates
another interpretive possibility for understanding collaborative work: Collaborations of
10–12 people could be viewed as another level of the original historical Poisson-type
collaborations: Two different research groups, each of size 5 to 6, led by a PI,
collaborate. Each research group could be seen as a kind of “person”, or “individual”,
just as in (American) law, a corporation as a legal entity is a person or being. Then, such
collaborations are really 2-“author” collaborations, in which the individual human
researchers are but component parts of larger wholes. Being a “component” may be
satisfactory through the postdoctoral years, for security and acquisition of new skills,
but thereafter, the ambitious individual will want to become a PI.
By this interpretation we have a kind of hybrid collaboration lying between
“collaboration” and “teamwork.” Having 10–12 individuals working on the same
project should qualify their product as teamwork, but if they are viewed as 2 collective
individuals (laboratory collectives), their product is like old style collaboration. The fact
that the modal number of collaborating laboratories is 2 additionally supports this idea
of laboratories/working groups as “individuals.” Furthermore, this relatively new way of
organizing research fits and extends nicely Derek Price’s suggestion that collaboration
is in part a response to a shortage of scientists, allowing there to be “fractional”
scientists. (
Price
and
Beaver
, 1966)
Research scientists’ views on collaboration today. Background
The following comments reflect the views of currently active researchers about what
collaboration means to them, based on a series of one-hour long interviews.
*
Their
perspectives on collaboration derive from the standpoint of an elite United States’
liberal arts college, located in Williamstown, in Northwestern Massachusetts.
Williams College is a coeducational undergraduate college of about 2,000 eighteen
to twenty-one year olds, about evenly split between male and female students. It is very
highly rated academically and it students are on a par with those of major research
universities like Harvard, Yale, Princeton, Berkeley, and Stanford for admission. About
40% of the students major in the natural sciences, mathematics, computer science, and
psychology. Williams leads small college in terms of National Science Foundation
Grants per science faculty member.
*
In all there were 7 scientists: 2 computer scientists, 2 physicists, 1 geologist, 1 biologist, and 1 chemist.
Scientometrics 52 (2001)
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: Reflections on scientific collaboration
For shedding light on collaboration, Williams has the following 3 advantages:
[1] (
reproduces researchers
) Small liberal arts colleges are “feeders,” to science: per
capita undergraduate student, they lead to more Ph. Ds in science than major
research universities, and that has been true for most of the 20th century. (See
Knapp
and
Goodrich
, 1952.)
[2] (
“hands-on” learning by doing collaborative research
) A great educational
advantage of the small liberal arts college is that undergraduates actively participate
in on-going research front investigations. They do so both because pedagogically
such experience affords superior education, and because their mentors reciprocally
derive benefit from their activity in the laboratory. Many undergraduate students
publish their first research paper with their advisers; a significant fraction of
professors’ publications consists of paper written with student co-authors.
[3]
(clearer standpoint
) Over the past few decades, pressures for greater research
productivity at liberal arts colleges has increased, to the point where researchers at
such institutions compare with those at minor research universities. Thus being
active in research, but not in a major research university, research institute, or
industrial research lab, affords a unique vantage point for providing a clearer
perspective on the nature and function of collaboration. It is to be hoped that such a
standpoint may help correct or make more objective findings based only upon data
from the most elite major research institutions.
Perspectives on collaboration
Let us proceed then, to see what my colleagues said about motives for collaboration
in research – why do they do it? First let us consider the summary outline presented in
Table 1.
*
In large measure, the summary items presented in Table 1 speak for themselves, so I
won’t dwell on them here, except to emphasize the very welcome item number 18 – if
we ever lose sight of those motives, we’re in trouble. There are, however, some
additional significant themes that emerged in response to five other questions about
collaboration.
*
For a related table, dealing with 10 general factors helping to increase collaboration, see
Katz
and
Martin
,
1997, Section 2.2.
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Table 1
The purposes for which people collaborate
1 Access to expertise.
2 Access to equipment, resources, or “stuff” one doesn’t have.
3 Improve access to funds.
4 To obtain prestige or visibility; for professional advancement.
5 Efficiency: multiplies hands and minds; easier to learn the tacit knowledge that goes
with a technique.
6 To make progress more rapidly.
7 To tackle “bigger” problems (more important, more comprehensive, more difficult,
global).
8 To enhance productivity.
9 To get to know people, to create a network, like an “invisible college”.
10 To retool, learn new skills or techniques, usually to break into a new field, subfield,
or problem.
11 To satisfy curiosity, intellectual interest.
12 To share the excitement of an area with other people.
13 To find flaws more efficiently, reduce errors and mistakes.
14 To keep one more focussed on research, because others are counting on one to do so.
15 To reduce isolation, and to recharge one’s energy and excitement.
16 To educate (a student, graduate student, or, oneself).
17 To advance knowledge and learning.
18 For fun, amusement, and pleasure.
How do collaborations start?
• By chance, at a colloquium or lecture, or at a conference, because of
a presentation, or because of working sessions or, on leave at
another institution, to learn new skills, or catch up with the field.
• By intention, by letter or phone call of solicitation.
• By recommendation or referral by trusted colleagues.
• Because it’s a part of one’s job – to mentor, to educate.
What’s the typical size of a collaboration?
• 2 or 3 persons or laboratories, OR “giant”.
• Dominant model: 2 individuals, usually “peers”.
• Unusual persistence of “Poisson” model, of
pairing
off.
• Perhaps also responds to the pressure of unwanted intermediate
authorships – with 2 authors, can take turns at being first author.
Scientometrics 52 (2001)
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• Persistence of prestige of single-author publications (perhaps also
dependent on the journal where published).
• Some even “frown on” collaborations of more than 6 people.
• It shows “you still have the juice to do it on your own”.
• This suggests that in our studies of collaboration, we should also pay
more attention to single authors, as counterpoint, balance, and for
comparative purposes to help calibrate and place our results in
context.
How is credit allocated in collaborations?
• Name Ordering: a signal to the research community, and to hiring
committees’ evaluations, which at Wiliams often first look at the
total publication list, then look for the percentage of first author, or,
single authored papers, as a sign of creative independence and
ability to do most of the work of a published piece of research –
qualities needed to establish a research laboratory, get funding, and
educate students in the laboratory.
• Conventions are highly variable, and dependent on field or subfield.
Alphabetical or First Place-Last Place are the two most common
systems. Conventions vary enormously. Intermediate authors tend to
be overlooked, or, intermediate authorships tend to be less highly
valued.
• A rather unique way of determining authorships is practiced by a
theoretical quantum information group at IBM, where the group
leader lists everyone who contributed to the research, and then
invites individuals who don’t feel they did enough to deserve an
authorship to cross their names off the list.
Does collaboration affect one’s research productivity?
• At worst, collaboration doesn’t influence, at best, it enhances.
• Problems: The persistence of stylistic differences complicates
evaluation. For example, consider the different practices represented
by the following types of research practice: field-closet; field-lab;
theoretical-experimental. Furthermore, subtle but significant
differences in co-authorships and also the frequency of collaboration
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may be lost or simply undetectable in aggregate data. It is important
to know something qualitatively about the nature of the research
being studied, and who is performing it.
Has Email affected collaborations?
• Generally, research is nearly impossible without it.
• Cf. one scientist’s collaboration with colleagues from China, Russia,
and Mexico.
• Cf. one scientist’s collaboration with colleagues at 3 different
universities (e.g. California, Munster, Bremen).
• Enhances efficiency, intensiveness, if not necessarily volume – for
some. But others clearly wouldn’t be as productive w/o email-
assisted collaboration.
The future: Internet and E-journals
There is space and time for only a few limited and necessarily speculative ideas
about possible future changes that may affect the form, quality, and nature of
collaborative research in the future. In particular, the expansion of the World Wide
Web, and the growing number of electronic journals are likely to bring changes in
research practice, which will be in turn reflected in the conventions of formal
“publication”, whether singly or multiply-authored.
Because science is “many-brained”, as Derek Price used to like to say, the open and
accessible nature of sites and links on the Web is tailor made to suit that character. But,
just as important as surfing or searching for data may be, it is equally important to know
when to stop doing so.
Because data is becoming so ubiquitous, and web sites proliferating, the practice of
taking people’s materials off the web and manipulating them for research, for lectures,
or other professional purposes, is bound to increase. There will be enormous temptation
to do “instant research.” With increasing “borrowing” of others’ materials will come
problems of determining, assuring, or evaluating quality. (At least a few of our
undergraduates are already adept at relying on the Web for research papers, while still
neophytes at evaluating the validity or adequacy of the data they acquire.) Because the
Web simultaneously becomes both investigative tool and research subject, how to deal
with that novel character will require considerable care.
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For collaborations, and collaborative study in particular, increasing globalisation is
likely to produce increases in the geographical diversity of collaborators, be they
individuals, laboratories, or institutes. Physical location is no longer a barrier to the free
and easy exchange of information. Indeed, it may be the case that the advent of email
had already begun to increase diversity in geographical locations. It would be interesting
to see if such a phenomenon could be detectable in a retrospective study.
Collaborative research published in ejournals will, for a while, create enormous
problems of comparison with that represented by print journals, and quite likely many of
the problems that arise in evaluating the latter will also apply to the former. It is not yet
clear what will constitute the “core” of ejournals, or along what lines they will be
stratified. Perhaps the simplest strategy for evaluating the impact or visibility of such
sites would be to adopt the practice of counting “hits”, and focusing only on the “most
hit” as the “biggest” sites. But we have seen that most such convenient and efficient
practices can all too easily introduce enough bias to seriously cast in doubt the research
based on them.
Conclusion
Let me leave the speculative future, and return to the present, and close by noting
that the number of conclusions, caveats, and potential research problems connected with
studying collaboration in scientific research is enormous. As pleasant and rewarding as
it is to solve problems, it is nonetheless even more exciting to realize that there are still
more problems to be solved about collaboration, and that there are more problems than
there are researchers working on them, which is a good thing for us and the future of our
field.
*
Support for this presentation and for travel to this conference was provided by the Office of the Dean
of Faculty, Williams College, Williamstown, MA, USA.
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EAVER
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EAVER
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ATZ
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EAVER
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Received July 17, 2001.
Address for correspondence:
D
ONALD DE
B. B
EAVER
Department of History of Science, Williams College
Bronfman Science Center, 18 Hoxsey St.
Williamstown, MA 01267, USA
E-mail: dbeaver@williams.edu
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