Environmental Science & Policy 7 (2004) 385–403
How science makes environmental controversies worse
Daniel Sarewitz
Consortium for Science, Policy, and Outcomes, Arizona State University, P.O. Box 874401, Arizona, AZ 85287-4401, USA
Abstract
I use the example of the 2000 US Presidential election to show that political controversies with technical underpinnings are not resolved
by technical means. Then, drawing from examples such as climate change, genetically modified foods, and nuclear waste disposal, I explore
the idea that scientific inquiry is inherently and unavoidably subject to becoming politicized in environmental controversies. I discuss three
reasons for this. First, science supplies contesting parties with their own bodies of relevant, legitimated facts about nature, chosen in part
because they help make sense of, and are made sensible by, particular interests and normative frameworks. Second, competing disciplinary
approaches to understanding the scientific bases of an environmental controversy may be causally tied to competing value-based political
or ethical positions. The necessity of looking at nature through a variety of disciplinary lenses brings with it a variety of normative lenses, as
well. Third, it follows from the foregoing that scientific uncertainty, which so often occupies a central place in environmental controversies,
can be understood not as a lack of scientific understanding but as the lack of coherence among competing scientific understandings,
amplified by the various political, cultural, and institutional contexts within which science is carried out.
In light of these observations, I briefly explore the problem of why some types of political controversies become “scientized” and others
do not, and conclude that the value bases of disputes underlying environmental controversies must be fully articulated and adjudicated
through political means before science can play an effective role in resolving environmental problems.
© 2004 Elsevier Ltd. All rights reserved.
Keywords: Values; Politics; Science policy; Environmental policy; Lomborg
1. Introduction
One may or may not find believable the claim by Bjorn
Lomborg, author of The Skeptical Environmentalist, that,
starting out as “an old left-wing Greenpeace member”
gloom-and-doom environmentalist (Lomborg, 2001, p. xix)
he gradually convinced himself, through the power of statistical
analysis, that the environmental conditions upon
which humanity depends for its well-being were not getting
worse, but were actually getting better. Whether or not
Lomborg did undergo a data-induced perceptual transformation,
his underlying claim is a familiar and comfortable
one. Our commitments to acting in the world must be based
on a foundation of fact, and when a conflict arises between
the two, then our commitments must accordingly change.
Thomas Lovejoy, in a sharply critical review of Lomborg’s
book, nevertheless supports a similar view, where appropriate
action is determined by scientific inquiry: “researchers
identify a potential problem, scientific examination tests
the various hypotheses, understanding of the problem often
becomes more complex, researchers suggest remedial
policies—and then the situation improves” (Lovejoy, 2002,
E-mail address: daniel.sarewitz@asu.edu (D. Sarewitz).
p. 12; emphasis in original). David Pimentel, another Lomborg
critic, argues in the same vein: “As an agricultural
scientist and ecologist, I wish I could share Lomborg’s optimism,
but my investigations and those of countless other
scientists lead me to a more wary outlook” (Pimentel, 2002,
p. 297).
So Lomborg and his critics share the old-fashioned
idea that scientific facts build the appropriate foundation
for knowing how to act in the world. How, then, are we
to understand the radical divergence of the supposedly
science-based views held by opposing sides in the controversy?
If we accept the arguments of the critics, the divergence
is simply a reflection of Lomborg’s (perhaps willful)
misunderstanding of the data. Yet, as Harrison (this issue)
amply documents, Lomborg also has his supporters within
the community of scientists. Are we instead witnessing a
debate that exists because the science is incomplete, and
thus allows for different interpretations? Stephen Schneider
(2002, p. 1), another of Lomborg’s critics, notes: “I readily
confess a lingering frustration: uncertainties so infuse the
issue of climate change that it is still impossible to rule
out either mild or catastrophic outcomes, let alone provide
confident probabilities for all the claims and counterclaims
made about environmental problems.”
1462-9011/$ – see front matter © 2004 Elsevier Ltd. All rights reserved.
doi:10.1016/j.envsci.2004.06.001
386 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
There is an obvious problem of causation here. If the
science is insufficiently certain to dictate a shared commitment
to a particular line of action, from where do these
commitments spring? For Lovejoy, the process starts when
“researchers identify a potential problem,” but the recognition
that something is a “problem” demands a pre-existing
framework of values and interests within which problems
can be recognized. And Pimentel’s “wary outlook” (not
to mention Lomborg’s rosy one) presupposes some expectations
of what the world ought to look like in the first
place.
This paper thus confronts a well-known empirical problem.
In areas as diverse as climate change, nuclear waste
disposal, endangered species and biodiversity, forest management,
air and water pollution, and agricultural biotechnology,
the growth of considerable bodies of scientific
knowledge, created especially to resolve political dispute
and enable effective decision making, has often been accompanied
instead by growing political controversy and
gridlock. Science typically lies at the center of the debate,
where those who advocate some line of action are likely to
claim a scientific justification for their position, while those
opposing the action will either invoke scientific uncertainty
or competing scientific results to support their opposition.1
A significant body of literature both documents and seeks
to understand this dynamic (see, e.g., the admirable synthesis
by Jasanoff and Wynne, 1998). This literature is characterized,
for example, by the understanding that scientific
facts cannot overcome, and may reinforce, value disputes
and competing interests (e.g., Nelkin, 1975; Nelkin, 1979;
Collingridge and Reeve, 1986), that scientific knowledge is
not independent of political context but is co-produced by
scientists and the society within which they are embedded
(e.g., Jasanoff, 1996a), that different stakeholders in environmental
problems possess different bodies of contextually
validated knowledge(e.g., Wynne, 1989), and that the
boundaries between science and policy or politics are constantly
being renegotiated as part of the political process
(e.g., Jasanoff, 1987; Jasanoff, 1990).
This work adds up to a deeply textured portrayal of the
troubled relationship between science and decision making
in the realm of the environment. Yet, as the Lomborg
controversy highlights to a degree that is almost painful,
high-profile public discourse surrounding environmental disputes
remains stubbornly innocent of this past 20 or more
years of constructivist scholarship. The notion that science
is a source of facts and theories about reality that can and
should settle disputes and guide political action remains a
1 This dynamic does not discriminate on the basis of ideology: in the
case of the Yucca Mountain nuclear waste repository, the claim that the
science is sufficient to justify action (i.e., construction of the site) has
most strongly been invoked by those with a politically conservative bent;
in the case of climate change, it is political liberals who have been more
likely to claim that the science is sufficient to justify a particular line of
action (mandated reductions of greenhouse gas emissions).
core operating principle of partisans on both sides of the
Lomborg case and other environmental controversies.2
Much, perhaps most, of the recent literature grounds its
critique in the difficulties associated with the first component
of this pervasive and strongly held notion—that science
is a source of verifiable facts and theories about reality. In
this paper, I treat this realist notion not as a contestable idea
but as an initial condition of the policy context—a starting
point for further analysis. My goal is to offer an interpretation
of the current, lamentable state of affairs whose acceptance
by political actors does not require an abandonment of
fundamental cosmologies. Thus, I look for explanation not
in the social construction of science, but precisely in “the
fact that scientists do exactly what they claim to do,” (Hull,
1988, p. 31) and argue that the fulfillment of this promise
is what gets us deeper into the hot water—science does
its job all too well. The argument, in brief, is this: nature
itself—the reality out there—is sufficiently rich and complex
to support a science enterprise of enormous methodological,
disciplinary, and institutional diversity. I will argue
that science, in doing its job well, presents this richness,
through a proliferation of facts assembled via a variety of
disciplinary lenses, in ways that can legitimately support,
and are causally indistinguishable from, a range of competing,
value-based political positions. I then show that, from
this perspective, scientific uncertainty, which so often occupies
a central place in environmental controversies, can
be understood not as a lack of scientific understanding but
as the lack of coherence among competing scientific understandings.
These considerations lead me finally to consider
the question of why environmental controversies tend to become
highly “scientized,” and to speculate about what might
happen if we could “de-scientize” them.
But first, as a sort of control case, it might be helpful
to visit a major political controversy that was not resolved
through resort to scientific research: the 2000 US Presidential
election.
2. Determining an integer
The front page of the 6 May 2000 Washington Post
reported that political scientists were using mathematical
models to predict the winner of the forthcoming US Presidential
election between Democratic candidate Al Gore and
Republican George W. Bush (Kaiser, 2000). The models,
which integrated such factors as the state of the economy
and public opinion data, indicated that Gore would handily
win the election. But by the time the polls in most states
had closed, it was apparent that victory in this remarkably
close election would depend on the outcome of the vote in
the populous and tightly contested state of Florida, with its
2 Perhaps paradoxically, the notion persists despite carefully argued
claims about the delegitimation of the authority of science in society (e.g.,
Ezrahi, 1990).
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 387
25 electoral votes. At about 8:00 p.m. on election night, the
major television networks famously declared Gore the winner
on the basis of data from Florida exit polls. But as the
actual Florida returns came in, it soon became clear that the
race was too close to call, and the networks rescinded their
initial prediction of a Gore victory. Early the next morning,
the networks named Bush the victor, but they soon learned
that the closeness of the vote would trigger an automatic
recount, so again they had to reverse themselves. A day
later, with all precincts reporting, the initial vote count for
Florida indicated a difference between Gore and Bush of
about 1800 votes out of almost six million cast—a margin
of less than three hundredths of a percentage point.
With so much at stake, the vote count was of course furiously
contested, with claims of irregularities, miscounts,
misvotes, machine failure, and even voter intimidation, and
demands for recounts. Yet the basic contention focused on
the determination of a single, apparently simply fact: how
many votes did each candidate receive?
This is a remarkably straightforward-seeming problem,
with an apparently clear path to resolution: count all votes
and determine the winner. Yet, in the end, the winner of
the Florida vote was not determined by an assertion of fact,
it was determined through the resolution of a legal battle
between lawyers representing the interests of each candidate,
and decided by the Supreme Court of the United States
(2000). The decision overturned an earlier Florida Supreme
Court ruling that would have allowed additional recounts. In
so doing, it accepted a vote count that had been previously
certified by the state of Florida, which showed Bush to be
the winner (now by 537 votes) despite ongoing uncertainties
about the actual tally. In other words, the Court asserted
that the final answer to the question “Who got more votes
in Florida?” was appropriately determined by legal and political
processes.
2.1. A thought experiment
Would not it have made more sense to simply get a definitive
count of the votes to objectively determine the winner?
Imagine that the contesting parties had agreed that the problem
was a technical one, not a legal or political one, and
that they had turned the vote counting over to a team of
disinterested experts whose job would be to determine the
correct result. On its face, it is hard to imagine a problem
more suited to a strictly technical approach. The system under
consideration—an election—is in principle a closed one,
with a finite number of system components (voters; voting
machines; vote counting procedures) obeying simple decision
rules (each voter votes once for one candidate based on
personal preference; all votes for each candidate are added
up) within clearly defined spatial (the state of Florida) and
temporal (the time period during which the polls were open)
boundaries. The correct answer is known to be an integer,
and it is derived through the simplest possible arithmetic
process.
Of course the political debate over the vote count revealed
system complexities. Overvotes (ballots that were not
counted because they appeared to contain votes for more
than one candidate) and undervotes (ballots that were not
counted because they appeared not to indicate a vote for
any candidate) totaled more than 175,000—more than three
hundred times the final, certified 537 vote differential between
Bush and Gore (Merzer, 2001). Many of these ballots
seemed to indicate the intent of the voter (for example, in
cases where voters had not pushed the vote-punch machine
hard enough to fully separate the chad from the card; or
where voters had both punched and written in a vote for the
same candidate). Confusing ballot graphics may have led
some people to vote for the wrong candidate. More generally,
the reliability of various voting technologies was called
into question.
So the team of experts tasked with coming up with the
final vote tally might need to be drawn from several disciplines.
For example, there would certainly need to be a
statistics group to develop models of reliability for different
types of voting machines. Statisticians would also need to
develop rigorous error analyses that would characterize the
probabilities that a given tally actually determined the real
victor. A technology evaluation group would need to assess
the sources of failure for different types of machines, while
a cognitive neuroscience group might look at visual perception
problems to try to understand the extent to which
ballot design could contribute to wrong votes. Fundamental
research could address such questions as chad behavior
under different states of compressive stress (material science),
the relation between the physical strength of the
voter and chad behavior (physiology), the variable behavior
of vote-punch machines (mechanical engineering), and the
causes of overvotes (psychology).
The first result of these analyses would likely be reports
with technical-sounding titles such as “Florida’s Residual
Votes, Voting Technology, and the 2000 Election,” or
“Elections: Statistical Analysis of Factors that Affected Uncounted
Votes in the 2000 Presidential Election,” or “The
Butterfly Did It: The Aberrant Vote for Buchanan in Palm
Beach County, Florida.”3 Once the experts began to make
their results known, other experts would need to review
them, and disagreements—over methodology, data, and
conclusions—would undoubtedly emerge. Studies from different
disciplines would need to be integrated, and even then
the final calculations would have to be governed by rules
about what constitutes a valid vote. Normative questions
(such as whether the vote count should capture the intent
of all voters, or simply record “actual” votes, which would
in turn raise questions about what “actual” meant) would
thus govern both the design of studies and the interpretation
of results, and we could expect that the political backgrounds
and affiliations of the experts would be exhaustively
3 In fact, these are the titles of published papers: Leib and Dittmer
(2002), US General Accounting Office (2001), and Wand et al. (2001).
388 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
scrutinized to try to sniff out potential conflicts of interest. To
make matters yet more complex, ideological affinity would
probably influence what type of science one was willing to
accept, because different approaches to counting would have
different implications for the election results. In this light,
because so many of the uncounted overvotes and undervotes
were from precincts with Democratic majorities,4 Bowker
and Star (2001, p. 422) recognized “a party political divide
[that] aligned the purity of numbers with the Republican
right and a faith in statistics with the Liberal left.”
Can we really imagine that such a technical process would
have led to a swift determination of the “real winner” in a
timely fashion, and in a manner that preserved the legitimacy
of the electoral system and the eventual winner? Would
the experts have been able to arrive at a number—a simple
integer—that everyone could agree on as the “right” answer,
and that all contesting interests would have accepted? Indeed,
the Miami Herald sponsored an unofficial recount of
over- and undervotes which showed that either Gore or Bush
could have been the winner depending on criteria used to
judge the validity of ballots.
In contrast, it should be remembered that the political/judicial
process that actually was followed did accomplish
these goals, conferring a final decision in 36 days,
and yielding a new president who was broadly accepted
despite the fact that more than half of the nation’s voters
had opposed him, and in the absence of any agreement of
what the final vote tally “actually” was.
This story and thought experiment are meant to highlight
four points.
1. Even apparently simple systems can display unprecedented,
surprising behavior. Fifty-two previous presidential
elections were not enough to reveal all possible system
behaviors and permit accurate prediction of future
outcomes.
2. The same uncertainties that were revealed in the Florida
election no doubt exist in all elections. They became
significant because the election was so close (both
sides could reasonably visualize themselves as potential
winners—or losers), and because the stakes were enormously
high—the presidency would be determined by
its outcome.
3. The dispute was not resolved by addressing the technical
aspects of the vote count, but by subjecting the vote
count process to political and judicial mediation procedures
that were legitimated by their capacity not to arrive
at “truth” but to transparently negotiate among competing
players. But because this system was broadly accepted
as legitimate—that is, people understood and agreed on
the rules—its results were also broadly accepted. More-
4 Studies by various social scientists (e.g., Wand et al., 2001 and Heron
and Sekhon, 2003) have sought to show that the intent on many overvoted
ballots could be inferred, and have concluded that high prevalence of
uncounted overvotes in strongly Democratic counties worked strongly in
favor of Bush.
over, the result is not permanent—it will be revisited in
the next election.
4. A purely technical approach, aimed at overcoming uncertainty
about the vote count, and subject both to the
strictures of scientific method and the close attention of
the public, could not have achieved resolution as quickly,
as decisively, or as legitimately, as the political/legal ap-
proach.
3. Excess of objectivity
I want to explore the possibility that environmental controversies
typically bear a much greater likeness to the 2000
Florida election controversy than might at first seem apparent.
To do so I begin by considering why facts5 often fail
to behave in the manner that both Lomborg and his critics
claim they should.
In July 2003, two conservative think-tanks, the Hoover
Institution on War, Revolution and Peace at Stanford University,
and the George C. Marshall Institute in Washington,
DC, published a book entitled Politicizing Science: The
Alchemy of Policymaking (Gough, 2003). The book visited
a number of examples, from a right-wing perspective, of
how science had been manipulated, distorted, or suppressed,
mostly in support of liberal causes, mostly related to the
environment. The underlying theme of the book was that
science could guide politics only when it was free from
ideology. “The more that political considerations dominate
scientific considerations, the greater the potential for policy
driven by ideology and less based on strong scientific
underpinnings” (2003, p. 3). The point, of course, is that
“policy driven by ideology” is supposed to be undesirable.
The next month, Congressman Henry Waxman, a liberal
Democrat, released a report entitled “Politics and Science
in the Bush Administration” (United States House of
Representatives, 2003), which pointed to numerous examples
of how the Administration “manipulated the scientific
process and distorted or suppressed scientific findings” to
yield results that favored the interests of its supporters.
While neither of these publications were works of scholarly
research, and both made some points that seem reasonable
and others that are less so, the more interesting
observation is that, in coming from strongly contrasting
ideological positions, they (along with the combatants in
the Lomborg controversy) shared a view of science as a
disinterested force that could guide political decision making
by providing appropriate facts—so long as it was kept
separate from politics. Yet the simultaneous appearance of
these two products amusingly highlights what neither side
was willing or able to contemplate: if everyone politicizes
the science, maybe there is something about science that
lends itself to being politicized?
5 I am content to use a conventional definition of “fact,” e.g., a statement
about the world whose truth or falseness can be tested.
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 389
Consider climate change, which may variously be understood
as a “problem” of climate impacts, weather impacts,
biodiversity, land use, energy production and consumption,
agricultural productivity, public health, economic development
patterns, material wealth, demographic patterns, etc.
Each of these ways of looking at the problem of climate
change involves a variety of interests and values, and each
may call on a body of relevant knowledge to help understand
and respond to the problem. Not only may the interests, values,
and knowledge relevant to one way of understanding
the problem be, in small part or large, different from those
associated with another way, but they may also be contradictory.
Conversely, those holding different value perspectives
may see in the huge and diverse body of scientific information
relevant to climate change different facts, theories, and
hypothesis relevant to and consistent with their own normative
frameworks. This condition may be termed an “excess
of objectivity,” because the obstacle to achieving any type
of shared scientific understanding of what climate change
(or any other complex environmental problem) “means,”
and thus what it may imply for human action, is not a lack
of scientific knowledge so much as the contrary—a huge
body of knowledge whose components can be legitimately
assembled and interpreted in different ways to yield competing
views of the “problem” and of how society should
respond. Put simply, for a given value-based position in an
environmental controversy, it is often possible to compile a
supporting set of scientifically legitimated facts.
A familiar illustration is the documentation of global
warming. While the observation of a global warming
signal over the past 20 years is well accepted, discrepancies
between surface temperature measurements and
lower-to-middle troposphere temperature data from satellites
and radiosondes continue to offer scientifically credible
facts for global warming “contrarians.” A National
Academy of Sciences report (NRC, 2000) failed to resolve
this conflict, concluding that, on the one hand, “the warming
trend in global-mean surface temperature observations
during the past 20 years is undoubtedly real” and also that
“the troposphere actually may have warmed much less
rapidly than the surface from 1979 into the late 1990s”
(NRC, 2000, p. 2).6
Yet resolving the discrepancy to everyone’s satisfaction
would not really solve anything. After all, the fact of global
warming is not itself inherently problematic; what worries
us is the possibility that warming will cause a variety of undesirable
outcomes. When global warming is considered in
terms of its specific potential social consequences, however,
the availability of competing facts and scientific perspectives
quickly spirals out of control. Consider the following
6 The first goal listed in the Strategic Plan for the US Climate Change
Science Program (Climate Change Science Program, 2003) is to reconcile
surface and lower atmosphere temperature records, whose inconsistencies
“reduce confidence in understanding of how and why climate has
changed.”
chain of logic: human greenhouse gas emissions are causing
global warming; global warming will lead to increased
frequency and severity of extreme weather events; reducing
greenhouse emissions can thus help reduce the impacts of
extreme weather events. Each link in this chain is saturated
with the potential for competing, fact-based perspectives.
For example, climate models and knowledge of atmospheric
dynamics suggest that increased warming may contribute to
a rising incidence and magnitude of extreme weather events
(Houghton et al., 2001, p. 575); but observations of weather
patterns over the past century do not show clear evidence
of such increases, while model results are still ambiguous,
and “data continue to be lacking to make conclusive cases”
(Houghton et al., 2001, p. 774). While economists can show
how tradable permit schemes combined with mandated
emissions targets can reduce greenhouse gas emissions
(Chichilnisky and Heal, 1995), they cannot agree on plausible
future rates of emissions increase (The Economist Print
Edition, 2003). Furthermore, perspectives on the history
and economics of innovation suggest that decarbonization is
likely to depend primarily on technology evolution and diffusion,
not policies governing consumption (Ausubel, 1991;
Nakicenovic, 1996). Social science research on natural
hazards suggests that socioeconomic factors (such as land
use patterns, population density, and economic growth),
rather than changing magnitude or frequency of hazards,
are responsible for increasing societal losses from extreme
events (Pielke et al., 2003; Changnon et al., 2001). And
in any case, climate scientists disagree about the extent to
which greenhouse gases are responsible for warming trends,
given that other phenomena, such as land use patterns, may
also strongly influence global climate (e.g., Marland et al.,
2003). Finally, climate models that as yet have no capacity
to accurately predict regional variability in extreme events
are thus even further from providing useful information
about how greenhouse gas emissions reductions might influence
future incidence and magnitude of extreme events.
Each level of analysis is not only associated with its own
competing bodies of contestable knowledge and facts, but
is also dependent on how one views the other levels of analysis.
Facts can be assembled to support entirely different
interpretations of what is going on, and entirely different
courses of action for how to address what is going on.
As Michael (1995, p. 473) explained, in the context not
of global warming but ecosystem management: “More information
provides an ever-larger pool out of which interested
parties can fish differing positions on the history of
what has led to current circumstances, on what is now happening,
on what needs to be done, and on what the consequences
will be. And more information often stimulates the
creation of more options, resulting in the creation of still
more information” (also see Herrick and Jamieson, 1995;
Herrick and Sarewitz, 2000; Sarewitz, 2000).
As an explanation for the complexity of science in
the political decision making process, the “excess of
objectivity” argument views science as extracting from
390 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
nature innumerable facts from which different pictures of
reality can be assembled, depending in part on the social,
institutional, or political context within which those doing
the assembling are operating. This is more than a matter of
selective use of facts to support a pre-existing position.7 The
point is that, when cause-and-effect relations are not simple
or well-established, all uses of facts are selective. Since
there is no way to “add up” all the facts relevant to a complex
problem like global change to yield a “complete” picture
of “the problem,” choices must be made. Particular sets
of facts may stand out as particularly compelling, coherent,
and useful in the context of one set of values and interests,
yet in another appear irrelevant to the point of triviality.8
4. Value in discipline
While this argument may help make clear why “more
science” often stokes, rather than quenches, environmental
controversies, I believe it does not go far enough. It seems to
me that there is likely to be a causal connection between the
ways that we have organized scientific inquiry into nature,
and the ways we organize human action (and thus political
decision making) related to the environment.
For example, consider the controversy over the Acoustic
Thermometry of Ocean Climate (ATOC) experiment. The
history of this controversy is discussed in detail in Oreskes
(2004). In brief, oceanographers at the Scripps Institution
of Oceanography designed a clever experiment to measure
changes in the global average temperature by monitoring
how the velocity of sound waves traveling over long distances
in the ocean were changing over time. ATOC was
promoted as the experiment that could finally settle the question
of whether, and how fast, global warming was actually
occurring. However, an alliance of environmentalists and biologists
opposed the experiment because of concerns about
its effects on whales and other marine mammals. While designers
of the experiment sought to assure the opponents
that the experiment would not harm marine mammals, they
lacked both the scientific legitimacy, and the institutional
disinterest, to make a convincing case. A National Research
7 My point is not to excuse conscious manipulation of facts, or to
deny that some research simply is not of a very good quality. But the
elimination of these two problems would have little if any effect on the
phenomenon I am describing. The problem is not “good” versus “bad”
but “ours” versus “theirs” (e.g., see Herrick and Jamieson, 2001 on “junk
science”).
8 A conspicuous example of such of non-intersecting worldviews is the
almost complete lack of cross fertilization between scientists who generate
model-based scenarios of future climate behavior, and researchers who
study hazards and their reduction. As one indication of this divide, these
communities use the word “mitigation” in opposite senses. To the climate
modeling community, mitigation means prevention of climate change
through greenhouse gas emissions reduction (mitigation of cause). To the
hazards community, mitigation means protection from climate impacts
through, e.g., better land use planning or infrastructure (mitigation of
effects).
Council (NRC) study was commissioned to resolve the dispute,
and while it was unable to confirm the potential for
ATOC to harm marine mammals, neither could it entirely
discount the possibility. Oceanographers working on the experiment
interpreted the report as a green light for ATOC,
while biologists saw it as a vindication of their opposition.
Oceanographers were primarily concerned about conducting
an oceanographic experiment that would document
global warming. Biologists were primarily concerned about
the effects of acoustic transmissions on the well-being of
marine mammals already under assault from human activities.
These positions are not reconcilable because there is
nothing to reconcile—they recognize and respond to different
problems. They also point to a direct connection between
scientific perspectives and values. Oceanographers chose
to interpret the uncertainty associated with the National
Research Council study as an endorsement of the safety of
ATOC. Biologists interpreted the same study as an affirmation
of potential harm. Scientific orientation helped to determine
one’s assessment of the level risk posed by ATOC,9
one’s willingness to face that risk, and one’s view about the
potential benefits of ATOC (Oreskes, 2004). There is a notable
incoherence in this debate—an incommensurability of
contesting fact-value positions (“contradictory certainties,”
to use Schwarz and Thompson’s (1990, p. 60) memorable
term). The benefits of performing ATOC, as understood and
articulated by physical oceanographers, had no bearing on
the well-being of marine mammals, as understood by biologists.
To put it bluntly, but perhaps not too simplistically,
oceanographers’ values were represented by the conduct
and outputs of oceanography; biologists’ values were not.
Could scientific orientation be related to the values that
one holds? Science divides up the environment partly by
disciplinary orientations that are characterized by particular
methods, hypotheses, standards of proof, subjects of interest,
etc. My point is certainly not that disciplines are associated
with monolithic worldviews and value systems. But,
while some see a grand unification of all knowledge as an
inevitable product of scientific advance (Wilson, 1998), thus
far the growth of disciplinary scientific methods and bodies
of knowledge results in an increasing disunity that translates
into a multitude of different yet equally legitimate scientific
lenses for understanding and interpreting nature (e.g., Dupré,
1993; Rosenberg, 1994; Cartwright, 1999; Kitcher, 2001,
chapter 6). Similarly, individual humans can have only the
most partial of understandings of the world in which they
reside, and it is in the context of these always-incomplete
understandings that they make their decisions and judgments
(e.g., Simon, 1997 and Simon, 1983). Without saying anything
about direction of causation, it seems entirely plausible
to suggest that the formal intellectual framework used
by a scientist to understand some slice of the world may be
9 Similarly, Barke and Jenkins-Smith (1993) showed that scientists’ perception
of risk related to nuclear waste disposal was related to disciplinary
orientation.
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 391
causally related to that scientist’s normative framework for
interpreting and acting in the world.
The ongoing debate over genetically modified organisms
(GMOs) in agriculture helps to illustrate the idea. There
are many ways to “understand” GMOs: in terms of their
connection to food production, human health, economic development,
ecosystem dynamics, biotechnology innovation
processes, plant genetic diversity, even culinary arts. Each of
these perspectives is associated in part with separate disciplinary
perspectives. What might such diverse perspectives
mean for how one views the “value” or “risks” of GMOs?
Environmental benefits typically attributed to GMOs include:
better resistance to environmental stresses; more
agricultural productivity; fewer agrochemical inputs such as
pesticides; and design of crops that can actually remediate
polluted soils and aquifers. Environmental risks typically
attributed to GMOs include: uncontrolled introgression of
genes into other varieties or species; harmful mutations
of inserted genes; competition and breeding with wild
species; negative effects of insecticidal GMOs on beneficial
non-target organisms such as birds and pollinating insects;
and growing resistance of insects to insecticidal GMOs
(Wolfenbarger and Phifer, 2000; Food and Agriculture
Organization, 2003a,b). One obvious attribute of these two
lists is that the putative benefits derive from straightforward
cause-and-effect relations that reflect the intent of scientists
working on GMOs, whereas the putative risks arise from
more complex interactions that are largely unintended. It
thus seems reasonable to expect that scientists from disciplines
involved in design and application of GMOs, such as
plant geneticists and molecular biologists, would be potentially
more inclined to view GMOs in terms of their planned
benefits, and ecologists or population biologists would be
more sensitized to the possibility of unplanned risks at a
systemic level.
These sorts of relations become palpable in trying to unravel
the vicious debate sparked by the publication of a paper
in Nature by Ignacio Chapela, a microbial ecologist, and his
graduate student, David Quist, documenting the occurrence
of transgenic corn in Mexico, and the introgression of the insecticidal
(Bt) transgenes into native maize varieties (Quist
and Chapela, 2001). The original article, which went through
Nature’s standard peer review process, was attacked vociferously
by numerous scientists, including former Berkeley
colleagues of Quist and Chapela. Both the methods and
the conclusions of the original paper were strongly criticized.
One scientist called the paper “a testimony to technical
incompetence,” another termed it “so outlandish as to be
pathetic,” and a third dismissed it as “trash and indefensible”
(Lepkowski, 2002a). These and other critics initially insisted
that the issue was simply one of the quality of the science,
but in reality the dispute was inextricably intertwined in the
larger controversy over biotechnology. If the original results
were correct it meant that GM corn had made its way into
Mexico despite the fact that it was banned by the Mexican
government, and, more damningly, that genes from the GM
corn had moved into native Mexican varieties that are the
original source of the world’s genetic diversity for corn. If
these conclusions turned out to be true, it could damage the
prospects of the agricultural biotechnology industry, because
it would indicate that the ecological and genetic impacts of
GM corn were not predictable and could not be controlled.
An underlying theme of the debate was that Quist and
Chapela’s attackers were in the pocket of the biotechnology
industry, or, from the opposite perspective, that
Quist, Chapela, and their allies were shills for the
anti-biotechnology lobby. Environmental and industry
groups mobilized their constituencies on behalf of the
scientists who best represented their interests. Scientists
themselves traded accusations about the political motives
and economic interests of those whose science they were
attacking (Lepkowski, 2002a; Nature, 2002). If nothing
else, the high stakes of the debate ensured that it would
attract much more attention than a disagreement that was
merely “scientific.” As Nature editor Maxim Clarke observed:
“scientists with strong interests scrutinize published
papers more intently than they would otherwise do . . .
because they are very motivated to find any flaws which
can be used to undermine or support the conclusions of the
paper” (Lepkowski, 2002b).
Yet on another level that was never discussed, the disciplinary
structure and disunity of science itself was at the
roots of the controversy. The two sides of the debate represented
two contrasting scientific views of nature—one concerned
about complexity, interconnectedness, and lack of
predictability, the other concerned with controlling the attributes
of specific organisms for human benefit. In disciplinary
terms, these competing views map onto two distinctive
intellectual schools in life science—ecology and molecular
genetics (e.g., see Holling, 1998).
Thus, it is not surprising that Quist and Chapela’s
strongest scientific critics were those whose own research
focused on the genetic engineering of individual plant varieties,
while their scientific supporters focused on ecosystem
behavior (as did Quist and Chapela). Those representing
the molecular genetics perspective aimed their critique at
flaws in Quist and Chapela’s techniques and the ambiguity
of their results (Metz and Fütterer, 2002; Kaplinsky et al.,
2002). Wayne Parrott of the University of Georgia, one of
their most aggressive attackers, said:
“[W]hen we do our work, we run a PCR [polymerase
chain reaction] first. Then we take our positive samples
and do a more reliable test on them. Chapela used it in
its entirety. He could have taken his positive samples and
followed them up with something more definitive, such
as spraying the things with a herbicide. Or he could have
looked for a protein. There are many things he could have
done that would have taken maybe a couple more weeks.
No one would have questioned it. The thing is that he tried
to get into a top journal by using a preliminary test. Then
he makes all sorts of claims based on this. He used the
392 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
wrong enzyme, he used the wrong extraction procedure,
everything he did was wrong. And it’s not worth the paper
it’s written on” (Lepkowski, 2002a).
But Allison Snow, a researcher at Ohio State University
who studies gene flow in the environment, had a more generous
view, despite acknowledging the methodological flaws:
“I don’t think the science in the second half of their paper
was very good. They said there were multiple insertions of
transgenes, where they were going in the genome wasn’t
predictable, and that therefore that there was something
scary about transgenes. But the first half of the paper,
while you could always have asked them to do a better job,
I thought was well supported. And anyway, a lot of people
already believe that transgression has already happened
and the Mexican government has confirmed it and talked
about it in several news releases. What was interesting was
Chapela’s positive control with the grain from the local
store. That had been shipped in from the United States as
animal feed and was definitely transgenic. It was not for
human consumption but people are planting it. So there
are all those different parts to this puzzle” (Lepkowski,
2002a).
Parrott, whose analytical frame of reference is the gene,
assessed Quist and Chapela’s work strictly in terms of its
adherence to the standards necessary for genetic engineering.
Failing to pass muster from that perspective, he deemed
the work worthless. Snow, whose focus is on the ecosystem
scale, could acknowledge these flaws but still recognize that
parts of the research had important implications for ecosystem
behavior, and as well that the research reflected such
scientific virtues as replicability of results and the clever
identification of a control case.
The implications of these competing perspectives are
readily apparent in the ways that Parrott and Snow describe
their own work. Parrott’s website says: “Our laboratory
conducts research on crop genetic engineering, although
its members also dabble in molecular markers. The bulk
of the work deals with the development of protocols for
. . . genetic transformation of soybean, peanut, alfalfa, and
maize” (Parrot Lab, 2003). In contrast, Snow says of her
research: “I study microevolutionary processes in plant populations,
with an emphasis on breeding systems, pollination
ecology, and conservation biology . . . Most recently, my
research focuses on the applied question of how gene flow
from cultivated species affects the evolutionary ecology of
weedy relatives” (Snow, 2003). Parrott’s concerns end with
the “genetic transformation” of specific crops, while this
transformation is the starting point for Snow’s work.
In this context, there is nothing inherently implausible in
the claims of scientists on both sides that their positions
were scientific, not political or economic. Two of Quist and
Chapela’s critics, accused in a letter to Nature of having
conflicts of interest because their research was partly funded
by the biotechnology industry (Nature, 2002, p. 898) defended
themselves in the following manner: “We are not
unlike many scientists in that we have shared research and
funding with industry at some point. In stating that we have
‘compromised positions,’ [our critics] wrongly imply that
private-sector funding strips us of integrity and legitimacy in
the arena of scientific discourse.” One may accept this argument
and still see a connection between the type of science
being conducted, a worldview compatible with that science,
and the interests of those who might find the science compelling
and valuable.10
This alignment of disciplinary perspective and worldly interests
is critically important in understanding environmental
controversies, because it shows that stripping out conflicts
of interest and ideological commitments to look at “what the
science is really telling us” can be a meaningless exercise.
Even the most apparently apolitical, disinterested scientist
may, by virtue of disciplinary orientation, view the world
in a way that is more amenable to some value systems than
others. That is, disciplinary perspective itself can be viewed
as a sort of conflict of interest that can never be evaded. In
cases such as the Mexican corn controversy, it might be most
accurate to look at the scientific debate not as tainted by values
and interests, but as an explicit—if arcane—negotiation
of the conflict between competing values and interests embodied
by competing disciplines.
From a similar perspective, the economist Richard
Norgaard (2002) assessed Lomborg’s The Skeptical Environmentalist.
Norgaard notes that economists have been
generally sympathetic with Lomborg’s optimistic evaluation
of the state of the world’s environment, while ecologists and
other environmental scientists have been largely outraged.11
The reason, he suggests, is that “the thinking of economists
requires the existence of scarcity,” (2002, p. 288) and
the history of industrial economies is one of overcoming
scarcity through innovation. Progress through innovation
and economic growth is a first principle underlying conventional
economic dogma, and this principle dictates that
current scarcity of environmental assets will be overcome
in a similar manner. One presumes, although Norgaard is
not explicit about this, that he sees environmental scientists
as inherently less inclined toward an optimistic view of the
future, perhaps because their disciplines do not include the
faith in the inevitability of progress that he attributes to
economics.
To summarize thus far: central to the idea that science
can help resolve environmental controversies is the expectation
that science can help us understand current conditions
under which our decisions are being made, and the potential
future consequences of those decisions. This expectation
must confront the proliferation of available facts that can be
10 The point applies equally to Chapela, a long-time opponent of GM
crops.
11 For this reason, he also speculates—correctly, it turns out (Harrison,
2004)—that some or most of the peer reviewers of Lomborg’s book must
have been economists.
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 393
used to build competing pictures of current and future conditions,
and the embeddedness of such facts in disciplinary
perspectives that carry with them normative implications.
These problems are in part a reflection of the diversity of
human values and interests, but they also reflect the richness
of nature, and the consequent incapacity of science (at least
in this stage of its evolution) to develop a coherent, unified
picture of “the environment” that all can agree on. This lack
of coherence goes by the name of “uncertainty.”
5. Origins of uncertainty
Reduction of uncertainty is a central, perhaps the central,
goal of scientific research carried out in the context of environmental
controversies ranging from climate change to
ecosystem restoration, as variously articulated in innumerable
policy documents, research reports, and scientific articles.
The standard model, of course, is that if uncertainty
surrounding the relevant scientific facts can be reduced, then
the correct course of action will become more apparent. Uncertainty
is thus portrayed as the cause of inaction. But the
notion of a clearly demarcated body of relevant fact is highly
problematic. And, as the 2000 election story shows, uncertainty
about facts need not be an impediment to political
resolution of heated controversy. The standard model will
hold up. To begin to develop a more satisfactory alternative,
I examine how estimates of uncertainty have changed in the
arenas of earthquake prediction, nuclear waste disposal, and
climate change. Based on these examples, I present the idea
that uncertainty in environmental controversies is a manifestation
of scientific disunity (excess of objectivity; disciplinary
diversity) and political conflict.
5.1. The Parkfield prediction
In 1985, seismologists from the US Geological Survey
estimated with 95% probability that a mid-size earthquake
along the Parkfield segment of the San Andreas fault would
occur by the year 1993. The 95% certainty level assigned
to the event was derived from a statistical analysis of the
recurrence interval of past earthquakes along the Parkfield
segment (Bakun and Lindh, 1985) and it was endorsed by
the scientific judgment of the seismological community as
a whole, as expressed by expert oversight bodies at the state
and national level (Nigg, 2000).
The earthquake, however, did not take place, and by the
end of 2003 had still not occurred. One possible explanation
is that reality is occupying the tail of the probability
curve—that is, the 95% probability was “correct,” and the
non-occurrence of the earthquake was indeed a highly unlikely
event reflecting aberrant behavior of the fault system
(analogous, perhaps, to the uniquely rare confluence of
events in the 2000 Florida election). If this were true, we
would expect, for example, that if similar predictions were
made for nineteen other, similar fault segments, earthquakes
would occur in all cases. But the state of seismological
knowledge has only rarely allowed scientists to issue earthquake
predictions with confidence, and even more rarely
have those predictions been borne out (Nigg, 2000). Indeed,
subsequent analysis has shown that the Parkfield prediction
was based on insufficient analysis of available data and
incomplete understanding of the fault’s behavior (Kagan,
1997; Roeloffs and Langbein, 1994). From this perspective,
the uncertainty estimate needs to be recognized as a statement
not about the actual behavior of a natural phenomenon,
but about the state of scientific understanding of that phenomenon
at a particular time, and the state of confidence
that scientists had in that state of understanding at that time.
Uncertainty estimates, that is, are in part a measure of the
psychological state of those making the estimates, which is
in turn influenced by political context within which the science
is carried out. In the case of the Parkfield prediction,
an important aspect of the story was that the fault segment
ran through a sparsely populated agricultural region of California.
Thus, the political and economic stakes of a false
prediction (or, for that matter, an accurate one) were low.
If seismologists had arrived at similar probabilities for an
earthquake in San Francisco, the consequences of both the
prediction itself, and the predicted event, would have been
considerably greater. Under such circumstances, scientific
and political scrutiny of the prediction would have greatly
intensified, the pressure on the scientists to be “right” would
have been intense, and the population of scientists and perhaps
of disciplines involved in the prediction process would
have expanded. It is difficult to imagine that such conditions
would not have influenced the certainty levels expressed by
scientists, or undercut the unanimity of opinion surrounding
particular statements of certainty. If the stakes had been
higher, certainty would have been lower.
5.2. Water flowing underground
One key attribute that determines the performance of any
nuclear waste site is its hydrological system. If water flows
through a site, it may accelerate degradation of waste containment
vessels that could in turn lead to mobilization of
radionuclides and contamination of water supplies and the
environment adjacent to the site. Because radioactive waste
decays over periods of tens of thousands of years, assessing
the behavior of a potential site involves efforts to understand
how the hydrological system might evolve over long time
frames.12
Since the early 1980s, hydrologists have been estimating
percolation flux, or the rate at which a volume of water flows
through a unit area of rock, at the proposed US high level
nuclear waste site at Yucca Mountain, Nevada. Initial estimates,
made in the early 1980s based on field studies, indicated
a flux of between 4 and 10 mm per year, but further
research reduced these estimates to between 0.1 and 1 mm
12 The Yucca Mountain story is taken from Metlay (2000).
394 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
per year, an uncertainty range that was reinforced by additional
studies over the next 12 years. These estimates, based
on combinations of expert judgment, numerical models, and
laboratory experiments, were a crucial input for integrated
performance assessment models of overall repository site
behavior. Indeed, the 0.1–1 mm per year range allowed such
performance assessments to conclude that the site was sufficiently
dry to meet safety standards set by the US Environmental
Protection Agency. As a result of this combined scientific
stability and political desirability, by the mid-1990s,
“thinking about percolation flux had almost achieved the
status of conventional wisdom” (Metlay, 2000, p. 210).
However, the Yucca Mountain site was the focus of intense
political controversy, and the scientific results that issued
from the Department of Energy (DoE), which had responsibility
for the site, were under constant fire. DoE was
also subject to the oversight of two external bodies that reviewed
the science and made recommendations for further
research.13 In this politically contentious environment, DoE
was pushed to drill a tunnel that would enable direct sampling
of rocks at the actual level of the proposed repository.
Subsequent analysis of water in those rocks indicated
the presence of radioactive isotopes generated from atmospheric
nuclear weapons tests in the early years of the Cold
War. That water containing these isotopes had made it from
the surface to the repository site—300 meters beneath the
surface—in less than 50 years was evidence that percolation
flux was perhaps ten times faster than indicated in modeling
studies over the previous decade. Following this discovery,
an aggregation of estimates from seven outside experts concluded
that the 95% probability range for percolation flux
lay between 1 and 30 mm per year—far higher rates than
were encompassed by the “conventional wisdom” born during
the prior decade or more of research. To complicate the
story even further, efforts to reproduce the isotopic analysis
of the repository water have yielded highly inconsistent results
(Nuclear Waste Technical Review Board, 2000). After
20 years of research, uncertainties surrounding percolation
flux seem only to have increased.
A key aspect of this story is that the decade or more of
research reinforcing the belief that percolation flux lay between
0.1 and 1 mm per year was sponsored by the agency
which had general responsibility for developing the repository
site and strong institutional and political motivations to
keep the project moving forward. As Metlay (2000, p. 211)
observed, “when faced with the need to resolve uncertainty
about percolation flux, the scientists [at DoE laboratories]
had little organizational incentive to settle on a higher value
or, more important, to question whether a lower value was
correct. This approach to addressing uncertainty need not
have been adopted consciously; in fact, it probably was not.
More likely, it arose simply because organizational norms
13 These bodies were the Nuclear Waste Technical Review Board, an
independent government agency, and the nongovernmental Board on Radioactive
Waste Management of the National Research Council.
and culture have a well-documented and pervasive effect on
individuals’ actions and judgments.”14 Moreover, initial estimates
of percolation flux emerged from an organizational
and scientific context that was relatively homogeneous in
terms of both scientific and political goals. As the research
process opened up to more diverse scientific and political
players, a greater diversity of values of interests were implicated,
leading to the introduction of new sources of uncer-
tainty.
5.3. Climate change
In climate change science, one closely scrutinized area
of uncertainty is climate sensitivity, or the average global
temperature increase associated with a doubling of atmospheric
carbon dioxide. More than a century ago the Swedish
chemist Arrhenius estimated this value at 5.5 ◦C (Rayner,
2000), a number remarkably close to the likely temperature
range of 1.5–4.5 ◦C estimated by modern climate scientists
using highly sophisticated numerical models, and adopted
by the Intergovernmental Panel on Climate Change (IPCC)
(Houghton et al., 2001, p. 67). While this latter temperature
spread is very commonly used as an indication of the uncertainty
range associated with climate sensitivity, the spread itself
is not a probability range—that is, the probability of any
particular temperature increase within this range is unspecified
(as is the probability of the doubling temperature falling
outside this range). Rather, the uncertainty range purportedly
reflects the difference between the smallest and largest
predicted temperature increases generated by a suite of 15
climate models (Houghton et al., 2001, p. 561). Yet, as van
der Sluijs et al. (1998) have pointed out, a notable attribute
of the canonical, IPCC-endorsed uncertainty range is that,
for more than two decades, it has not changed, despite huge
increases in the sophistication of climate models over that
time—a fact that they explain in terms of an ongoing process
of evolving judgment and negotiation among climate modelers
working in a politically heated area of science, where
significant changes in scientific conclusions could have considerable
political repercussions.
Outside the IPCC process, however, the uncertainty associated
with climate sensitivity has been expressed in several
different ways. One effort (Morgan and Keith, 1995)
elicited probabilities from 16 climate experts, and arrived
14 A similar dynamic has been demonstrated in the area of clinical
medical trials, where a number of studies have shown that trials directly
or indirectly supported by pharmaceutical companies often yield more
favorable assessments of new therapies—greater certainty about positive
results—than trials that are not tied to the private sector in any way. The
point here is not that scientists are engaging in fraudulent research in
an effort to bolster a desired conclusion. The reality seems to be more
interesting—that “close and remunerative collaboration with a company
naturally creates goodwill [that] can subtly influence scientific judgment
in ways that may be difficult to discern” (Angell, 2000, p. 1517). This
conclusion is similar to Metlay’s suggestion that “organizational norms
and culture” influenced uncertainty estimates at Yucca Mountain.
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 395
at a mean sensitivity of 2.6 ◦C with a mean standard deviation
of 1.4 ◦C. This type of “subjective probability” presumes
that all experts are providing equally “probable” estimates.
Another method estimates climate sensitivity based
on a simple climate/ocean model that simulates the observed
hemispheric-mean near-surface temperature changes for the
past century or so (Andronova and Schlesinger, 2001). This
approach concludes that the 90% confidence interval for climate
sensitivity is 1.0–9.3 ◦C—much wider than the more
familiar model uncertainty spread used by the IPCC. Other
recent studies (Knutti et al., 2002; Forest et al., 2002) also
indicate considerably wider spreads than the IPCC estimate.
Thus, as in the Yucca Mountain case, an expansion of the
institutional and scientific players destabilizes estimates of
uncertainty.
This phenomenon threatens the claim that scientific research
will help resolve scientific controversy through reduction
of uncertainty. My own experience on the Climate
Research Committee of the National Research Council illustrates
how institutions central to the mainstream of scientific
research may nevertheless seek to buttress this claim. During
2001–2003 I was part of a panel writing a report that was
originally to be entitled Climate Change Feedbacks: Characterizing
and Reducing Uncertainties. The panel’s formal
tasks in the report were to:
(1) characterize the uncertainty associated with climate
change feedbacks15 that are important for projecting the
evolution of the Earth’s climate over the next 100 years;
and
(2) define a research strategy to reduce the uncertainty associated
with these feedbacks . . . .
Because the report was to deal directly with the problem
of uncertainty in climate science, the panel decided to
include a section discussing some of the complexities surrounding
the concept of uncertainty in science and policy.
This decision was particularly notable because such an approach
had not been taken before. Numerous previous NRC
reports on climate science, while frequently using the word
“uncertainty,” and asserting the importance of reducing it,
did not make a serious effort to distinguish among the various
meanings of the word, even while repeatedly making
the claim that more research would reduce uncertainty, and
reduced uncertainty would aid policy makers.16
A draft of the report was circulated to outside reviewers.
The draft included a brief discussion of the concept of uncertainty,
illustrated by a discussion of differing approaches
15 Climate feedbacks are processes in the climate system that can either
magnify or reduce the system’s response to climate forcing such as
greenhouse gas emissions.
16 Perhaps most notable among these was the massive Pathways report,
which states on its opening page (NRC, 1999a, p. 1), first that “we can
now focus attention on the critical unanswered scientific questions that
must be resolved to fully understand and usefully predict global change,”
and therefore, that “we need to reduce uncertainties in the projections
that shape our decisions for the future.”
to estimating the uncertainty associated with climate sensitivity.
The draft also included the statements that “characterizing
the uncertainty is not the same as reducing it,” and
that “there is no guarantee that further research will soon
reduce the uncertainty in climate projections.”17
Reviewers were extremely critical of this discussion, noting
especially that the word “uncertainty” was used in many
different ways without clearly defining them. “This is not
a trivial issue,” one reviewer acutely noted, “because it is
a matter of objectives. Each definition of uncertainty represents
a different definition of objectives, which leads to a
different definition of metrics.” Reviewers also strongly criticized
the report’s focus on “model uncertainty,” which was
deemed “unacceptable for institutional reasons. It states the
objective of a multibillion dollar program in strictly insider’s
terms, i.e., understandable and of interest only to scientists,
and makes a point of saying that societal links cannot be
established.”18
Yet the reviewers did not suggest that a revised draft include
a more careful definition and delineation of the various
uses of the word “uncertainty,” but rather recommended
the opposite—that the specific discussion of uncertainty be
omitted. This seems to indicate that the problem was not
the various meanings and uses of the word throughout the
report, but the calling attention to them in the introductory
discussion. Indeed, prior NRC climate reports also used
“uncertainty” in a similar variety of ways without defining or
distinguishing them (e.g., NRC, 1999a; NRC, 2000; NRC,
2001).
The panel’s subsequent set of revisions included a very
reduced section on uncertainty, but did not eliminate the discussion
of climate sensitivity, which was felt to be an important
illustration of how uncertainty could be characterized
in different ways. Statements about the difficulties of
reducing uncertainty were also left in. Reviewers again objected,
and it was made clear to the panel that unless the
offending language was removed, the report would not be
published.19 Thus, in the final report all discussion of uncertainty
was removed. Even the word “uncertainty” was
stripped from the title, which was changed to Understanding
Climate Change Feedbacks (NRC, 2003). The multiplicities
of meaning and use of the word “uncertainty” remain
(unacknowledged) in the report,20 as does the promise, both
17 Quotes from a 6 June 2002 draft of the report.
18 Quotes from an 8 August 2002 internal memo to the panel from NRC
staff.
19 Memo to the panel, 9 July 2003.
20 As just one example: in a discussion of cloud feedbacks, successive
paragraphs refer first to “reduction in the uncertainty of climate
sensitivity,” which is generally reported as a model uncertainty, and then
states that “[a]nother key uncertainty in cloud–climate interactions is the
response of anvil clouds to surface temperature.” The second use of the
word seems simply to mean “incomplete knowledge” (NRC, 2003, p. 27).
Two pages later “uncertainty” is used to mean the difficulty of quantifying
a specific value (“the amount of radioactive heating that occurs within the
atmosphere versus how much heating occurs at the surface . . . ”) (NRC,
2003, p. 30).
396 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
explicit and implicit, that more research, and better models,
will reduce uncertainties.21 Absent, however, is any discussion
of these issues.
The conspicuous contradiction between the reviewers’
comments and their suggested changes makes it very difficult
to understand the review process as anything other than an
effort to reinforce what Shackley and Wynne (1996, p. 285)
termed the “condensation” of uncertainty’s many meanings
and complexities into “one undifferentiated category” that
allows broad claims to be made about how the key to a given
problem is more research and more time. Moreover, by presenting
uncertainty as a vague but putatively coherent concept
that is “reduced” through more research, the scientific
community assures that the phenomenon of uncertainty remains
located in our imperfect (but always-improving) understanding
of nature, and is not an attribute of nature itself,
of the structure of disciplinary science, or of the social and
political context within which research is conducted. In this
way, scientists can maintain control over the management of
uncertainty while also, in the words of Shackley and Wynne
(1996, p. 287), “strengthening the authority of science [that]
in turn reinforces a particular policy order.”
As it pertains to environmental controversy, the word
“uncertainty” refers most generally to the disparity between
what is known and what actually is or will be. Uncertainty,
that is, reflects our incomplete and imperfect characterization
of current conditions relevant to an environmental problem,
and our incomplete and imperfect knowledge of the future
consequences of these conditions. For a well bounded
problem, these insufficiencies can to some extent be addressed
(although never eliminated) through additional research,
but there are many reasons why such an approach
might not succeed, for example, when additional research
reveals heretofore unknown complexities in natural systems,
or highlights the differences between competing disciplinary
perspectives, and thus expands the realm of what is known
to be unknown.
But as the previous examples show, the characterization
of uncertainty also reflects the political and institutional contexts
within which science is conducted and debated, the diversity
of scientific practice, and the psychological states of
those making the characterizations.22 Uncertainty is in part
a manifestation of the disunity of science and the plurality of
institutional and political players (and their competing value
commitments) involved in the conduct and interpretation of
21 For example, “Research into carbon uptake by the land and ocean
as outlined in the US Carbon Cycle Plan . . . should be undertaken to
characterize and reduce the uncertainty associated with carbon uptake
feedbacks” (NRC, 2003, p. 10).
22 For example, the propensity of experts to display overconfidence in
probability estimates has long been recognized (Kahneman et al., 1982).
Moreover, as Rosenberg (1994) points out, the very act of estimating
probabilities increases the complexity of the system being studied because
that system now includes the cognitive states of the experts who are doing
the estimating.
Fig. 1. Schematic illustration of influence of political context on level of
uncertainty.
scientific research. It is the location where conflicts between
competing sets of facts and disciplinary perspectives reside.
One simple way to think about these relations is shown
in Fig. 1. When political stakes associated with a controversy
are relatively low, high certainty is more permissible
than when the stakes are high (e.g., Collingridge and Reeve,
1986). Fewer disciplines, institutions, and stakeholders are
likely to have strong and competing interests in any particular
assertion of uncertainty levels. This relation is illustrated
by the Parkfield prediction. But when the costs and benefits
associated with action on a controversy begin to emerge
and implicate a variety of interests, both political and scientific
scrutiny of the problem will increase, as will sources of
uncertainty, as shown by the climate sensitivity and nuclear
waste cases.23 Moreover, when political controversy exists,
the whole idea of “reducing uncertainty” through more research
is incoherent because there will never be a single
problem for which a single, optimizable research strategy
or solution path can be identified, let alone characterized
through a single approach to determining uncertainty. Instead,
there will be many different problems defined in terms
of many competing value frameworks and studied via many
disciplinary approaches.
Recent developments in the Yucca Mountain story starkly
illustrate the implications of these observations. In July 2002
President Bush signed a Congressional resolution that allows
the US Department of Energy to apply for a license
to actually construct the nuclear waste repository at Yucca
Mountain (Holt, 2003). This crucial political step was taken
even though uncertainty about site behavior has increased
significantly in recent years, due both to controversy over
the hydrogeology, discussed above, and new insights into the
effects of corrosion on waste containment vessels (Nuclear
23 Jamieson (1995, p. 37) has made a similar point in arguing that
“[r]ather than being a cause of controversy, scientific uncertainty is often
a consequence of controversy.” However Shackley and Wynne (1996,
p. 276) suggested the opposite—that “the less a science is tied to policy
uses, the more its practitioners would be free to express uncertainty.”
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 397
Waste Technical Review Board, 2003). What allowed political
action to take place was the consolidation of national
political power in the hands of the Republican party, which
is sympathetic to the interests of the nuclear power industry,
and thus supports moving ahead with development of the
waste site. The diversity of political interests controlling the
decision process was curtailed, and as a result the optimistic
views on uncertainty of scientists and bureaucrats at the Department
of Energy were able to prevail over other perspectives
and interests. While these events are unlikely to mark
an end to the controversy, they can allow action to proceed,
and thus mark the beginning of what Schön and Rein (1994,
p. xix) have called a “policy drama,” where the discussion
increasingly focuses on assessing progress toward a particular
goal, e.g., the safe storage of nuclear waste, rather than
on impossible-to-resolve questions such as whether “safe”
storage is possible.
6. Why scientize?
The organization of science—its methodological and
disciplinary diversity; the multiple institutional settings in
which it is conducted—make it a remarkably potent catalyst
for political dispute. Recognizing that simple, linear formulations
leading from “more science” to “less uncertainty”
to “political action” are inherently flawed, others have suggested
that society needs to adopt new ways of thinking
about the conduct of science, new ways of evaluating how
and when science is valid or potentially useful, new institutions
for mediating the processes by which science is integrated
into political decision making, and new geographic
and temporal scales for conducting and using science (e.g.,
Funtowicz and Ravetz, 1992; Gallop´ın et al., 2001; Lee,
1993; Nowotny et al., 2001; Gibbons, 1999; NRC, 1999b;
Jasanoff, 1990, 1996b). While accepting the value and
salience of all of these suggestions, they focus on the problem
of understanding how scientific knowledge, in all its
multifarious, social complexity, can best be integrated into
contentious decision making processes. In cases where problems
are fairly well circumscribed in terms of institutional
players and problem definition, such approaches may make
particular sense. Yet they do not engage this overarching observation:
we have few good examples of science providing
sufficient clarification to point the way through politically
charged, open-ended environmental controversies,24 yet in-
24 The successful negotiation of the Montreal Protocol, mandating the
phase out of stratospheric-ozone-depleting chlorofluorocarbons (CFCs), is
the most obvious candidate for such a success story. The identification of a
single chemical culprit (CFCs) as the major cause of ozone depletion suggests
that this problem was scientifically “easier” than other high-profile
controversies. Yet the incentives for policy action were strongly enhanced
by a political and diplomatic climate that was receptive to reductions in
CFC use even before the resolution of the major scientific questions about
ozone depletion (Benedick, 1991; Sarewitz, 1996). Also important was
the invention of CFC alternatives by DuPont (Rowlands, 1993), which
numerable examples of decisive political action in all realms
of society taken despite controversy and uncertainty, and
with science playing little or no formal role in the debate.
One must wonder if it is worth approaching the problem from
the opposite direction. So I would like to conclude by briefly
exploring the following question: why is it that some political
controversies become scientized, while others do not?
To return to the 2000 Presidential election, on its face,
the vote count should have been much more amenable to
scientific investigation and uncertainty reduction than even
the simplest environmental controversy. On the other hand,
the election was broadly accepted as a relatively pure process
for adjudicating competing values and interests. Moreover,
those values and interests had been on public display for
months through the election campaign process. Even though
the adjudication process itself was a technical one (counting
votes), once the authoritativeness of that process was called
into question, numerous other mechanisms for adjudicating
value disputes were available and mobilized. Because these
mechanisms were unabashedly political (or, in the case of
the US Supreme Court, perhaps abashedly so), they were not
subject to criticism for using junk science or for politicizing
scientific results. Contesting sides were overtly seeking to
advance their own interests. If there are complaints to be
made about this process, they must address the mechanisms
by which interests are advanced, such as campaign financing
or the process of selecting judges, rather than the mechanism
by which the controversy was ended.
What are the interests and values at stake in controversies
over global climate change, nuclear waste disposal, or
genetically modified foods? While it may not be very hard
to arrive at plausible hypotheses about the value preferences
of people holding various positions in such controversies,
the scientific debate itself conceals those preferences behind
technical arguments. This camouflaging process reflects, in
part at least, the enduring social commitment to the idea of
scientific facts as detached from values, and the consequent
desire of everyone on all sides of a given controversy to legitimate
their value preferences with an allegedly independent
body of facts (e.g., Nelkin, 1995). This commitment is
codified through a variety institutions and agreements, for
example, the Intergovernmental Panel on Climate Change,
which is supposed to provide the scientific basis for making
international decisions about climate, and the World Trade
Organization, which allows nations to regulate trade in agricultural
goods based on risks to human, animal, and plant
health only if such regulation is based on accepted scientific
principles and standards (World Trade Organization, 1995).
What Wynne (1991, p. 120) observed more than a decade
ago seems to be no less true today: despite the policy implications
of scholarly insight into the contextual origins
allowed private sector interests to align with calls for a CFC phase out.
The ozone story is less one of controversy resolved by science than of
positive feedback among convergent scientific, political, diplomatic, and
technological trends.
398 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
of scientific knowledge, “the overall trend in the structure
and control of science is currently running in the opposite
direction.”
Any political decision (indeed, any decision) is guided by
expectations of the future. Such expectations can in turn be
less or more informed by technical knowledge, but the capacity
of such knowledge to yield an accurate and coherent
picture of future outcomes is very limited indeed. Ultimately,
most important decisions in the real world are made with a
high degree of uncertainty, but are justified by a high level of
commitment to a set of goals and values. Such past political
acts as the passage of civil rights legislation, the reform of
the US welfare system, or the decision to invade Iraq were
not taken on the basis of predictive accuracy or scientific
justifications about what the future would look like, but on
the basis of convictions about what the future should look
like, informed by plausible expectations of what the future
could look like. From this perspective it is useful to recall
that, when comprehensive environmental laws were enacted
in the US during the late 1960s and early 1970s, scientific
knowledge about the state of the environment was much less
comprehensive and sophisticated than it is today, when almost
all environmental laws and regulations are under political
attack. The implementation of a broad legal framework
for environmental protection in the US was a response to a
social and political consensus, not authoritative knowledge
(e.g., Kraft and Vig, 1997).
It is difficult to avoid the conclusion that there is no a priori
reason why some types of political controversies should
be highly scientized, and others should not be. For example,
from a purely technical standpoint, the difficulties of predicting
future climate outcomes and impacts over the next
century, or predicting the behavior of a nuclear waste site
over the next 10,000 years, cannot be much less complex,
and are likely much more complex, than predicting the future
of, say, different immigration policies or medical insurance
systems.
Why, then, do some controversies become more scientized
than others? Possibilities include:
1. advocates or opponents of action believe that scientific
knowledge will advance their value positions or interests;
2. advocates or opponents of action believe that scientific
uncertainty will advance their value positions or interests;
3. scientists are involved in the political framing of the controversy;
and
4. available policy options for addressing the controversy
are insufficiently broad or appealing to attract a political
consensus.
In contrast, reasons why some controversies do not become
highly scientized might include:
1. value positions are well articulated from the beginning
of the controversy;
2. values underlying the controversy are widely viewed as
inappropriate for scientific adjudication;
3. effective mechanisms for eliciting and adjudicating value
disputes are already in place and well-accepted; and
4. available policy options are broad and appealing enough
to attract a political consensus.
Political decision making can fruitfully be understood as
a process of adjudicating value disputes (Lasswell, 1977,
pp. 184–185; Sandel, 1996, pp. 17–18). This understanding
certainly does not imply that facts have no place in political
debate. People can only make sense of the world by finding
ways to reconcile their beliefs with some set of facts about
how reality must operate (e.g., Simon, 1983; Schön and
Rein, 1994). So politics can isolate values from facts no more
than science can isolate facts from values. The nature of
this interaction has been a central subject of science studies
scholarship (e.g., Jasanoff, 1987; Jasanoff, 1990).
The problem is that this symmetry does not manifest in
political processes. Political debate permits the mobilization
of a broad range of weaponry, including scientific facts, religious
dogma, cultural norms, and personal experience, in
defense of one’s values and interests. But scientized debate
must suppress the open discussion of value preferences;
were it not to do so it would have no claim to distinction
from politics.25 This need can strike at the heart of democratic
vitality. For example, as mentioned, World Trade
Organization rules require that nations can only restrict
trade in genetically modified foods on the basis of scientific
risk assessments. These rules, of course, are meant to ensure
a more open flow of goods across national boundaries,
and thus give precedence to economic values over all others.
But the well documented opposition in many European
countries to GM foods appears to have little to do with scientifically
determined levels of risk, and much to do with
non-economic values. In many European nations, a majority
of people surveyed say that they would not purchase GM
foods even if they were known to be safe, environmentally
friendly, and cheaper than non-GM equivalents. Survey data
show that people’s concerns are related more to a desire for
transparency in decision making about GM foods, a suspicion
about the economic motives of multinational companies
who sell such foods, a concern about the implications
of GM products for the European agricultural system (which
in turn connects to concerns about landscape and culture),
and worries about the implications of globalization for quality
of life (Marris et al., 2001; Gaskell et al., 2003; Rayner,
2003). In the scientized controversy over GM foods, these
diverse values have no legitimated part in the debate over
levels of risk. Thus, not only are expressions of these values
suppressed, but they are suppressed in favor of an alternative
value—economic openness—that remains camouflaged
25 In reality, of course, scientists are constantly engaged in a process
of sub rosa, perhaps even subconscious, negotiation that is unavoidably
political, whether working in the closed context of a research community
(e.g., Fleck, 1979; Collins, 1985), or in the more highly charged
atmosphere of a science advisory panel (Jasanoff, 1990).
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 399
behind the commitment to carrying out the debate in scientific
terms alone.
Scientization of controversy also undermines the social
value of science itself. In the absence of agreed upon values
that can inform the articulation of social goals, we cannot
recognize the broad range of policy options that might be
available to achieve those goals, nor can we possibly know
how to prioritize scientific research in support of the goals.26
Scientific resources end up focused on the meaningless task
of reducing uncertainties pertinent to political dispute, rather
than addressing societal problems as identified through open
political processes. The opportunity cost may be huge.27
Consider what has taken place in the climate change arena.
Certainly the Kyoto Protocol stands as the most significant
political achievement related to climate change thus far. The
Protocol represents the translation of a set of scientific insights
about the relation between greenhouse gas emissions
and global temperatures into a political decision to take a
first step toward reducing those emissions.28 But no one can
possibly know what the consequences of these emissions
reductions will be, either in terms of climate behavior or socioeconomic
outcomes. Thus, the only coherent value that
can be extracted from the decision to adopt such reductions
is that reducing greenhouse gas emissions is an inherently
good thing to do. But this raises its own set of problems. The
Kyoto goals could be achieved, for example, through a variable
combination of emissions and sequestration schemes,
which might or might not actually result in decreased hydrocarbon
consumption. They could be pursued by enhancing
global economic equity, for example, through diffusion of
new technologies, or by further concentrating global wealth,
for example, through policies that fail to spur economic development
in poor countries (thus keeping energy consumption
low).29 And the pursuit of the Kyoto goals is not likely
to have any discernible effect at all on the impacts of climate
on society. If concerns about the negative impacts of climate
change are a motivating value behind emissions reductions,
those concerns will not be met.
Were such goals and values as, say, absolute reductions
in hydrocarbon consumption through greater energy efficiency,
more equitable global economic development, and
26 Some environmental controversies, such as climate change, only exist
because of scientific research that allowed the problem to be recognized
in the first place. However, the role of bringing an environmental problem
to public attention is not at all the same as resolving the value-based
controversies raised by the problem (e.g., Herrick and Sarewitz, 2000;
Alario and Brün, 2001).
27 As one indication of this opportunity cost, consider that the US federal
commitment to basic research on climate change has been about four times
more than its expenditures on renewable energy research (EIA, 2001).
28 That is, for industrialized nations, by 5% below 1990 levels by the
year 2012.
29 In this light it is notable that the Kyoto Protocol’s relatively modest
commitment to technology development and diffusion is more than offset
by a variety of economic and technology policies endorsed by many
signatory nations that increasingly undermine the development prospects
of poor countries (e.g., Stiglitz, 2003).
decreased impacts of climate on society openly adopted as
worthy of pursuit by society with the help of science, then
global scientific priorities would look considerably different
than they do now (e.g., Sarewitz and Pielke, 2000; Pielke
and Sarewitz, 2003), perhaps corresponding more closely
to what some have termed “sustainability science” (NRC,
1999b; Kates et al., 2001).
From these brief discussions I hope to have made clear
that there is no reason why environmental controversies must
be highly “scientized.” Even if science brings such a controversy
into focus (for example, by documenting a rise in
atmospheric greenhouse gases), the controversy itself exists
only because conflict over values and interests also exists.
Bringing the value disputes concealed by—and embodied
in—science into the foreground of political process is likely
to be a crucial factor in turning such controversies into successful
democratic action, and perhaps as well for stimulating
the evolution of new values that reflect the global
environmental context in which humanity now finds itself
(Jamieson, 1992). Moreover, the social value of science itself
is likely to increase if scientific resources relevant to
a particular controversy are allocated after these value disputes
have been brought out into the open, their implications
for society explored, and suitable goals identified.30
A variety of researchers have sought to develop methods
for integrating values into environmental research, for example,
by developing scenarios of the future evolution of environment
and society that respond to different sets of value
preferences (e.g., van Asselt and Rotmans, 1996; Rotmans
and De Vries, 1997; Costanza, 2000; UK Climate Impacts
Programme, 2001). It is not clear whether or not this is a
step in the right direction because these approaches still depend
on the ability of mathematical models to yield plausible
scenarios of the future, where plausibility will in part be
judged within the normative perspectives of those using the
models (which themselves embody the normative perspectives
of those who build the models). Moreover, the process
of articulating concrete future alternatives through models
could have the affect of exacerbating political controversy
by claiming to make it clearer who future winners and losers
are likely to be, given a set of decisions and predicted outcomes
(e.g., Glantz, 1995). These approaches also beg the
question of how values will actually be elicited and adjudicated
in choosing what scenarios society should actually
pursue.
What I am suggesting is that progress in addressing environmental
controversies will need to come primarily from
advances in political process, rather than scientific research.
Perhaps such advances will require the formal or informal
imposition of a sort of “quiet period” for scientific debate
30 At this point I must, unfortunately, emphasize that this is neither a
brief for nor against “basic research.” There is, indeed, every reason to
believe that the political determination of value preferences and goals in
the realm of the environment would need to be followed by research of
many different kinds aimed at helping to pursue those goals.
400 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
when environmental controversies become highly publicized
and gridlocked, to create time and space for underlying value
disputes to be brought into the open, explored, and adjudicated
as such in democratic fora. During such a “quiet
period,” those who make scientific assertions in fora of public
deliberation would have to accompany those claims with
a statement of value preferences and private interests relevant
to the dispute. This rule would be enforced for scientists
as well as lay people. Science does not thereby disappear
from the scene, of course, but it takes its rightful place as
one among a plurality of cultural factors that help determine
how people frame a particular problem or position—it is a
part of the cognitive ether, and the claim to special authority
vanishes.
If this suggestion seems not just playful but frivolous,
consider where my discussion began, with the election and
Lomborg controversies. In the former case, the factual dispute
was subjugated to the practical necessity of arriving at
a resolution, and politics was allowed to do its job. In the latter
case, an insistence by all parties that the dispute is about
who is in charge of the right environmental facts merely recapitulates
in miniature the escalating political gridlock surrounding
environmental politics. The technical debate—and
the implicit promise that “more research” will tell us what
to do—vitiates the will to act. Not only does the value dispute
remain unresolved, but the underlying problem remains
unaddressed.
The point is not that stripping away the overlay of scientific
debate must force politicians to take action. But if
they choose not to act they can no longer claim that they are
waiting for the results of the next round of research—they
must instead explain their allegiance to inaction in terms of
their own values and interests, and accountability now lies
with them, not with science or scientists. To the extent that
our democratic political fora are incapable of enforcing that
accountability, the solution must lie in political reform, not
more and better scientific information.
Yet one question remains: what, then, becomes of science?
One part of the answer is: nothing, it is still there, in the
background, along with all the other influences on people’s
political interests and behavior. But the other part of the
answer is that science is liberated to serve society and the
environment, for, as I have suggested, it is only after values
are clarified and some goals agreed upon that appropriate
decisions about science priorities can emerge.
No longer able to hide behind scientific controversy,
politics would have to engage in processes of persuasion,
reframing, disaggregation, and devolution, to locate areas
of value consensus, overlapping interests, or low-stakes options
(e.g., “no regrets” strategies) that can enable action in
the absence of a comprehensive political solution or scientific
understanding (Sarewitz and Pielke, 2000; Pielke and
Sarewitz, 2003). In particular, the abandonment of a political
quest for definitive, predictive knowledge ought to
encourage, or at least be compatible with, more modest, iterative,
incremental approaches to decision making that can
facilitate consensus and action. Such approaches call upon
science not to be a predictive oracle to guide policy choices,
but a tool to support, monitor, and assess the implementation
of policies that have been selected through the political
process (Brunner, 2000; Herrick and Sarewitz, 2000; Lee,
1993). “Sustainability,” write Rayner and Malone (1998,
p. 132) “is about being nimble, not being right.” And being
nimble is about taking small steps and keeping one’s eyes
open. Politics helps us decide the direction to step; science
helps the eyes to focus.
Acknowledgements
Roger Pielke Jr., Beth Raps, Richard Nelson, Charles Herrick,
and Naomi Oreskes provided valuable comments on
this paper. I also thank three anonymous reviewers for their
extraordinarily penetrating critiques of the penultimate version
(to the numerous arguments against anonymity in peer
review, add this: one is deprived of the pleasure and benefit
of continued engagement with thoughtful reviewers). Discussions
with Daniel Metlay have contributed greatly to my
understanding of the Yucca Mountain story, as well as to the
broader question of how institutions confront uncertainty.
References
Alario, A., Brün, M., 2001. Uncertainty and controversy in the science
and ethics of environmental policy making. Theory Sci. 2 (1),
http://theoryandscience.icaap.org/content/vol002.001/02alariobrun.html.
Andronova, N., Schlesinger, M.E., 2001. Objective estimation of the
probability distribution for climate sensitivity. J. Geophys. Res. 106
(D19), 22605–22612.
Angell, M., 2000. Is academic medicine for sale? N. Engl. J. Med.
342 (20), 1516–1518.
Ausubel, J., 1991. Energy and environment: the light path. Energy Syst.
Policy 15, 181–189.
Bakun, W.H., Lindh, A.G., 1985. The Parkfield, California, earthquake
prediction experiment. Science 229, 619–624.
Barke, R., Jenkins-Smith, H., 1993. Politics and scientific expertise:
scientists, risk perception, and nuclear waste policy. Risk Anal. 13,
425–439.
Benedick, R., 1991. Protecting the ozone layer: new directions in
diplomacy. In: Mathews, J.T. (Ed.), Preserving the Global Environment:
The Challenge of Shared Leadership. W.W. Norton, New York.
Bowker, G., Star, S.L., 2001. Pure, real and rational numbers: the American
imaginary of countability. Social Stud. Sci. 31 (3), 422–425.
Brunner, R., 2000. Alternatives to prediction. In: Sarewitz, D., Pielke Jr.,
R.A., Byerly Jr., R. (Eds.), Prediction: Science, Decision Making, and
the Future of Nature. Island Press, Covelo, CA, pp. 299–313.
Cartwright, N., 1999. The Dappled World, A Study of the Boundaries of
Science. Cambridge University Press, Cambridge, UK.
Changnon, S.A., Pielke Jr., R.A., Changnon, D., Sylves, R.T., Pulwarty,
R., 2001. Human factors explain the increased losses from weather
and climate extremes. Bull. Am. Meteorol. Soc. 81 (3), 437–442.
Chichilnisky, G., Heal, G., 1995. Markets for tradable CO2 emission
quotas principles and practice. OECD Economics Department
Working Papers No. 153, OCDE/GD(95)9, Organization for Economic
Co-Operation and Development, Paris.
Climate Change Science Program, 2003. Strategic Plan for the US
Climate Change Science Program. Climate Change Science Program,
Washington, DC.
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 401
Collingridge, D., Reeve, C., 1986. Science Speaks to Power: The Role
of Experts in Policy. St. Martin’s Press, New York.
Collins, H., 1985. Changing Order: Replication and Induction in Scientific
Practices. Sage, London.
Costanza, R., 2000. Visions of alternative (unpredictable) futures
and their use in policy analysis. Conserv. Ecol. Online 4 (1),
http://www.ecologyandsociety.org/vol4/iss1/art5/index.html.
Dupré, J., 1993. The Disorder of Things, Metaphysical Foundations of
the Disunity of Science. Harvard University Press, Cambridge, MA.
The Economist Print Edition, 2003. Hot potato revisited. Economist
November, 76.
EIA (Energy Information Agency), 2001. Renewable energy 2000:
issues and trends. Available at www.eia.doe.gov/cneaf/solar.renewables/
rea issues/reatabp2.html.
Ezrahi, Y., 1990. The Descent of Icarus: Science and the Transformation
of Contemporary Democracy. Cambridge University Press, Cambridge,
MA.
Fleck, L., 1979. Genesis and Development of a Scientific Fact. University
of Chicago Press, Chicago (original published in 1935).
Food and Agriculture Organization of the United Nations, 2003a.
Weighing the GMO arguments: against. Available at http://www.fao.
org/english/newsroom/focus/2003/gmo8.htm.
Food and Agriculture Organization of the United Nations, 2003.
Weighing the GMO arguments. Available at http://www.fao.org/
english/newsroom/focus/2003/gmo7.htm.
Forest, C.E., Stone, P.H., Sokolov, A.P., Allen, M.R., Webster, M.D.,
2002. Quantifying uncertainties in climate system properties with the
use of recent climate observations. Science 295, 113–117.
Funtowicz, S.O., Ravetz, J.R., 1992. Three types of risk assessment and
the emergence of post-normal science. In: Krimsky, S., Golding, D.
(Eds.), Social Theories of Risk. Praeger, Westport, CT, pp. 251–273.
Gallop´ın, G.C., Funtowicz, S., O’Connor, M., Ravetz, J., 2001. Science
for the twenty-first century: from social contract to the scientific core.
Int. Social Sci. J. 53, 219–229.
Gaskell, G., Allum, N., Stares, S., 2003. Europeans and biotechnology in
2002. A report to the EC Directorate General for Research from the
project ‘Life Sciences in European Society’, QLG7-CT-1999-00286,
http://europa.eu.int/comm/public opinion/archives/eb/ebs 177 en.pdf.
Gibbons, M., 1999. Science’s new social contract with society. Nature
402 (Suppl.), C81–C84.
Glantz, M.H., 1995. Assessing the impacts of climate: the issue of winners
and losers in a global climate change context. In: Zwerver, S., van
Rompaey, R.S.A.R., Kok, M.T.J., Berk, M.M. (Eds.), Climate Change
Research: Evaluation and Policy Implications. Elsevier, Amsterdam.
Gough, M., 2003. Politicizing Science. Hoover Institution Press, Stanford,
CA.
Harrison, C., 2004. Peer review, politics and pluralism. Environ. Sci.
Policy 7 (5), 357–368.
Heron, M.C., Sekhon, J.S., 2003. Overvoting and representation:
and examination of overvoted presidential ballots in Broward and
Miami-Dade counties. Electoral Stud. 22 (1), 21–47.
Herrick, C., Jamieson, D., 1995. The social construction of acid rain: some
implications for science/policy assessment. Global Environ. Change 5,
105–112.
Herrick, C., Jamieson, D., 2001. Junk science and environmental policy:
obscuring public debate with misleading discourse. Philosophy Public
Policy Q. 21 (Spring), 11–16.
Herrick, C., Sarewitz, D., 2000. Ex post evaluation: a more effective role
for scientific assessments in environmental policy. Sci. Technol. Hum.
Values 25 (3), 309–331.
Holling, C.S., 1998. Two cultures of ecology. Conserv. Ecol. 2 (2),
http://www.consecol.org/vol2/iss2/art4.
Holt, M., 2003. Civilian nuclear waste disposal. Congressional
Research Service, Order Code IB92059, Washington, DC, http://www.
NCSEonline.org/NLE/CRS/abstract.cfm?NLEid=17012.
Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J.,
Dai, X., Maskell, K., Johnson, C.A., 2001. Climate Change 2001:
The Scientific Basis. Contribution of Working Group I to the Third
Assessment Report of the Intergovernmental Panel on Climate Change.
Cambridge University Press, Cambridge, UK.
Hull, D.L., 1988. Science as a Process: An Evolutionary Account of the
Social and Conceptual Development of Science. University of Chicago
Press, Chicago.
Jamieson, D., 1992. Ethics, public policy, and global warming. Sci.
Technol. Hum. Values 17 (2), 139–153.
Jamieson, D., 1995. Scientific uncertainty and the political process, annals.
Am. Acad. Political Social Sci. 545, 35–43.
Jasanoff, S., 1987. Contested boundaries in policy-relevant science. Social
Stud. Sci. 17 (2), 195–230.
Jasanoff, S., 1990. The Fifth Branch: Science Advisors as Policymakers.
Harvard University Press, Cambridge, MA.
Jasanoff, S., 1996a. Beyond epistemology: relativism and engagement in
the politics of science. Social Stud. Sci. 26 (2), 393–418.
Jasanoff, S., 1996b. The dilemma of environmental democracy. Issues
Sci. Technol. 13 (1), 63–70.
Jasanoff, S., Wynne, B., 1998. Science and decision making. In: Rayner,
S., Malone, E. (Eds.), Human Choice and Climate Change, vol. 1: The
Societal Framework. Battelle Press, Columbus, OH, pp. 1–87.
Kagan, Y.Y., 1997. Statistical aspects of Parkfield earthquake sequence and
Parkfield prediction experiment. Tectonophysics 270 (3–4), 207–219.
Kahneman, D., Slovic, P., Tversky, A., 1982. Judgment Under Uncertainty:
Heuristics and Biases. Cambridge University Press, New York.
Kaiser, R.G., 2000. Is this any way to pick a winner. Washington Post
26 May, A1.
Kaplinsky, N., Braun, D., Lisch, D., Hay, A., Hake, S., Freeling, M., 2002.
Maize trangene results in Mexico are artefacts. Nature 416, 601–602.
Kates, R.W., Clark, W.C., Corell, R., Hall, J.M., Jaeger, C.C., Lowe, I.,
McCarthy, J.J., Schellnhuber, H.J., Bolin, B., Dickson, N.M., Faucheux,
S., Gallopin, G.C., Grübler, A., Huntley, B., Jäger, J., Jodha, N.S.,
Kasperson, R.E., Mabogunje, A., Matson, P., Mooney, H., Moore III,
B., O’Riordan, T., Svedin, U., 2001. Sustainability science. Science
292 (5517), 641–642.
Kitcher, P., 2001. Science, Truth, and Democracy. Oxford University
Press, New York.
Knutti, R., Stocker, T.F., Joos, F., Plattner, G.K., 2002. Constraints on
radiative forcing and future climate change from observations and
climate model ensembles. Nature 416, 719–723.
Kraft, M.E., Vig, N.J., 1997. Environmental policy from the 1970s to the
1990s: an overview. In: Vig, N.J., Kraft, M.E. (Eds.), Environmental
Policy in the 1990s. CQ Press, Washington, DC, pp. 1–30.
Lasswell, H.D., 1977. Psychopathology and Politics. University of Chicago
Press, Chicago.
Lee, K., 1993. Compass and Gyroscope, Integrating Science and Politics
for the Environment. Island Press, Covelo, CA.
Leib, J.I., Dittmer, J., 2002. Florida’s residual votes, voting technology
and the 2000 election. Political Geography 21, 91–98.
Lepkowski, W., 2002a. Biotech’s OK corral. Sci. Policy Perspect. 13,
http://www.cspo.org/s&pp/060902.html.
Lepkowski, W., 2002b. Maize, genes, and peer review. Sci. Policy Perspect.
14, http://www.cspo.org/spp/102502.html.
Lomborg, B., 2001. The Skeptical Environmentalist: Measuring the State
of the Real World. Cambridge University Press, Cambridge, UK.
Lovejoy, T., 2002. Biodiversity: dismissing scientific process.
Scientific American.com, January, http://www.sciam.com/article.cfm?
articleID=000F3D47-C6D2-1CEB-93F6809EC5880000&pageNumber
=12&catID=2.
Marland, G., Pielke Sr., R.A., Apps, M., Avissar, R., Betts, R.A., Davis,
K.J., Frumhoff, P.C., Jackson, S.T., Joyce, L., Kauppi, P., Katzenberger,
J., MacDicken, K.G., Neilson, R., Niles, J.O., Sutta, D., Niyogi, S.,
Norby, R.J., Pena, N., Sampson, N., Xue, Y., 2003. The climatic impacts
of land surface change and carbon management, and the implications
for climate-change mitigation policy. Climate Policy 3, 149–157.
Marris, C., Wynne, B., Simmons, P., Weldon, S., 2001. Public perceptions
of agricultural biotechnologies in Europe. Final report of the PABE
Research project, http://www.lancs.ac.uk/depts/ieppp/pabe/docs.htm.
402 D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403
Merzer, M., 2001. “Overvotes” leaned to Gore. The Miami Herald.com,
11 May, http://www.miami.com/mld/miami/news/2067453.htm.
Metlay, D., 2000. From tin roof to torn wet blanket: predicting and
observing groundwater movement at a proposed nuclear waste site. In:
Sarewitz, D., Pielke Jr., R.A., Byerly Jr., R. (Eds.), Prediction: Science,
Decision Making, and the Future of Nature. Island Press, Covelo, CA,
pp. 199–228.
Metz, M., Fütterer, J., 2002. Suspect evidence of transgenic contamination.
Nature 416, 600–601.
Michael, D.N., 1995. Barriers and bridges to learning in a turbulent human
ecology. In: Gunderson, L., Holling, C., Light, S. (Eds.), Barriers
and Bridges to the Renewal of Ecosystems and Institutions. Columbia
University Press, New York, pp. 461–485.
Morgan, M.G., Keith, D.W., 1995. Subjective judgments by climate
experts. Environ. Sci. Technol. 29, A468–A476.
Nakicenovic, N., 1996. Freeing energy from carbon. Daedalus 125 (3),
95–112.
Nature Publishing Group, 2002. Conflicts around a study of mexican
crops. Nature 417, 897–898.
Nelkin, D., 1975. The political impact of technical expertise. Social Stud.
Sci. 5 (1), 35–54.
Nelkin, D., 1979. Controversy: Politics of Technical Decisions. Sage,
London.
Nelkin, D., 1995. Science controversies: the dynamics of public disputes in
the United States. In: Jasanoff, S., Markle, G.E., Petersen, J., Pinch, T.
(Eds.), Handbook of Science and Technology Studies. Sage, Thousand
Oaks, CA, pp. 444–456.
Nigg, J., 2000. Predicting earthquakes: science, pseudoscience, and public
policy paradox. In: Sarewitz, D., Pielke Jr., R.A., Byerly Jr., R. (Eds.),
Prediction: Science, Decision Making, and the Future of Nature. Island
Press, Covelo, CA, pp. 135–156.
Norgaard, R.B., 2002. Optimists, pessimists, and science. BioScience
52 (3), 287–292.
Nowotny, H., Scott, P., Gibbons, M., 2001. Rethinking Science:
Knowledge and the Public in an Age of Uncertainty. Polity, Cambridge.
NRC, 1999a. Global Environmental Change: Research Pathways for the
Next Decade. National Academy Press, Washington, DC.
NRC, 1999b. Our Common Journey. National Academy Press,
Washington, DC.
NRC, 2000. Reconciling Observations of Global Temperature Change.
National Academy Press, Washington, DC.
NRC, 2001. Climate Change Science, An Analysis of Some Key
Questions. National Academy Press, Washington, DC.
NRC, 2003. Understanding Climate Change Feedbacks. National Academy
Press, Washington, DC.
Nuclear Waste Technical Review Board, 2000. Spring 2000 board meeting
transcript. Nuclear Waste Technical Review Board, Arlington, VA,
http://www.nwtrb.gov/meetings/meetings.html.
Nuclear Waste Technical Review Board, 2003. An evaluation of key
elements in the US Department of Energy’s Proposed System
for Isolating and Containing Radioactive Waste. Nuclear Waste
Technical Review Board, Arlington, VA, http://www.nwtrb.gov/
reports/reports.html.
Oreskes, N., 2004. Science and public policy: what’s proof got to do with
it? Environ. Sci. Policy 7 (5), 369–383.
Parrot Lab, 2003. Parrot Lab, http://www.cropsoil.uga.edu/∼parrottlab/.
Pielke Jr., R.A., Rubiera, J., Landsea, C., Fernandez, M.R., Klein, R.,
2003. Hurricane vulnerability in Latin America and the Caribbean:
normalized damage and loss potential. Nat. Hazards Rev. 4 (3), 101–
114.
Pielke Jr., R.A., Sarewitz, D., 2003. Wanted: scientific leadership on
climate. Issues Sci. Technol. Winter, 27–30.
Pimentel, D., 2002. Exposition on skepticism. BioScience 52 (3), 295–
298.
Quist, D., Chapela, I.N., 2001. Transgenic DNA introgressed into
traditional maize landraces in Oaxaca, Mexico. Nature 414, 541–543.
Rayner, S., 2000. Prediction and other approaches to climate change policy.
In: Sarewitz, D., Pielke Jr., R.A., Byerly Jr., R. (Eds.), Prediction:
Science, Decision Making, and the Future of Nature. Island Press,
Covelo, CA, pp. 269–296.
Rayner, S., 2003. Democracy in the age of assessment: reflections on the
roles of expertise and democracy in public-sector decision making.
Sci. Public Policy 30 (3), 163–170.
Rayner, S., Malone, E., 1998. Ten suggestions for policymakers. In:
Rayner, S., Malone, E. (Eds.), Human Choice and Climate Change,
vol. 4: What Have We Learned. Battelle Press, Columbus, OH, pp.
109–138.
Roeloffs, E.A., Langbein, J., 1994. The earthquake prediction experiment
at Parkfield, California. Rev. Geophys. 32 (3), 315–336.
Rosenberg, A., 1994. Instrumental Biology or the Disunity of Science.
University of Chicago Press, Chicago.
Rotmans, J., De Vries, B., 1997. Perspectives on Global Change.
Cambridge University Press, Cambridge, UK.
Rowlands, I.H., 1993. The fourth meeting of the parties to the
Montreal protocol: report and reflection. Environment 35 (6), 25–34,
http://www.ciesin.org/docs/003-077/003-077.html.
Sandel, M.J., 1996. Democracy’s Discontent: America in Search of a
Public Philosophy. Harvard University Press, Cambridge, MA.
Sarewitz, D., 1996. Frontiers of Illusion: Science, Technology, and the
Politics of Progress. Temple University Press, Philadelphia.
Sarewitz, D., 2000. Science and environmental policy: an excess of
objectivity. In: Frodeman, R. (Ed.), Earth Matters: The Earth Sciences,
Philosophy, and the Claims of Community. Prentice-Hall, Upper Saddle
River, NJ, pp. 79–98.
Sarewitz, D., Pielke Jr., R.A., 2000. Breaking the global warming gridlock.
Atlantic Monthly July, 54–64.
Schneider, S., 2002. Global warming: neglecting the complexities. Sci
Am. January, 62–65.
Schön, D.A., Rein, M., 1994. Frame Reflection: Toward the Resolution
of Intractable Policy Controversies. Basic Books, New York.
Schwarz, M., Thompson, M., 1990. Divided We Stand: Redefining Politics,
Technology and Social Choice. University of Pennsylvania Press,
Philadelphia.
Shackley, S., Wynne, B., 1996. Representing Uncertainty in Global
Climate Change Science and Policy: Boundary-Ordering Devices and
Authority. Sci. Technol. Hum. Values 21 (3), 275–302.
Simon, H.A., 1983. Reason in Human Affairs. Stanford University Press,
Stanford, CA.
Simon, H.A., 1997. Administrative Behavior, fourth ed. Free Press, New
York.
Snow, A., 2003. Research interests. The Department of Evolution,
Ecology, and Organismal Biology, The Ohio State University,
http://www.biosci.ohio-state.edu/∼eeob/resints/res snow.html.
Stiglitz, J.E., 2003. Globalization and its Discontents. Norton, New York.
Supreme Court of the United States, 2000. 531 US 98.
US General Accounting Office, 2001. Elections: statistical analysis of
factors that affected uncounted votes in the 2000 Presidential election.
GAO-02-122, 15 October, http://www.gao/gov/cgi-bin/getrpt?gao-02-
122.
United States House of Representatives, 2003. Politics and Science in the
Bush Administration, Committee on Government Reform—Minority
Staff. Washington, DC, http://www.house.gov/reform/min/politicsan-
dscience/.
UK Climate Impacts Programme, 2001. Socio-economic scenarios for
climate change impact assessment: a guide to their use in the UK. UK
Climate Impacts Programme, Oxford, UK, http://www.ukcip.org.uk/
research tools/research tools.html.
van Asselt, M.B.A., Rotmans, J., 1996. Uncertainty in perspective. Global
Environ. Change 6 (2), 121–157.
van der Sluijs, J., van Eijndhoven, J., Shackley, S., Wynne, B., 1998.
Anchoring devices in science for policy: the case of consensus around
climate sensitivity. Social Stud. Sci. 28 (2), 291–323.
D. Sarewitz / Environmental Science & Policy 7 (2004) 385–403 403
Wand, J., Shotts, K., Sekhon, J., Mebane Jr., W., Herron, M., Brady, H.,
2001. The butterfly did it: aberrant vote for Buchanan in Palm Beach
County, Florida. Am. Political Sci. Rev. 95 (4), 793–810.
Wilson, E.O., 1998. Consilience: The Unity of Knowledge. Alfred A.
Knopf, New York.
Wolfenbarger, L.L., Phifer, P.R., 2000. The ecological risks and benefits
of genetically engineered plants. Science 290, 2088–2093.
World Trade Organization, 1995. Agreement on the application of sanitary
and phytosanitary measures. Article 2.2.
Wynne, B., 1989. Sheepfarming after chernobyl: a case study in
communicating scientific information. Environment 31 (2), 11–15,
33–39.
Wynne, B., 1991. Knowledges in context. Sci. Technol. Hum. Values
16 (1), 111–121.
Daniel Sarewitz is Professor of Science and Society and Director of the
Consortium for Science, Policy, and Outcomes (CSPO) at Arizona State
University. Recent publications include Living with the Genie: Essays
on Technology and the Quest for Human Mastery (co-edited with Alan
Lightman and Christina Desser, Island Press, 2003); Prediction: Science,
Decision making, and the Future of Nature (co-edited with Roger Pielke
Jr. and Radford Byerly Jr, Island Press, 2000), and Frontiers of Illusion:
Science, Technology, and the Politics of Progress (Temple University
Press, 1996).