...VERSUS SOCIAL VALUE IV. CONCLUSIONS

I. INTRODUCTION

Wildlife management problem that superficially appears science ought to be able to resolve handily. Yet, successful wildlife management has proven to be far from simple and is exemplary of the complex dynamics that can emerge from simple biological interactions. Wildlife populations, for example, can be modeled using a formula with just one variable, (1) but this analytic simplicity is deceptive. Non-linear feedbacks, such as the responses of predators, can cause populations to crash unpredictably. (2) This dynamic is reflected in the formula, which is stunningly sensitive to minor variations in its single parameter--a difference of just one tenth of one percent can lead to widely divergent predictions for the same management decision. (3)

This example highlights a basic truth that is often overlooked. Science is limited by both the power of its methods and the characteristics of its subject matter. Ideal scientific problems are ones with sufficient complexity and generality to make them interesting, but not so much that they become intractable. Identifying good scientific problems is therefore essential to success as a scientist and to successful science. In this light, "[i]f politics is the art of the possible, [scientific] research is surely the art of the soluble." (4)

Scientists working in fields relevant to environmental law are rarely able to select problems with an optimal balance of broad implications and potential solutions. Escaping from the aridity of the laboratory comes at a steep price the inchoate swamp of the natural world. Issues ranging from the toxicity of industrial chemicals to the protection of endangered species and the projected magnitude of global warming transcend existing scientific knowledge.

This complexity poses an unsettling question: if scientific uncertainty is so pervasive, what exactly do scientific methods contribute to environmental policymaking? Resolving this question has proven to be exceedingly difficult, both because of the technical challenges and the high stakes. Typically, it is answered in the negative folks know bad science when they see it--which more often than not simply involves dissecting the inevitable gaps in an opponent's scientific methods. (5)

The resulting war of attrition has spawned a corrosive brand of skepticism fueled by vague terms, such as "sound" or "junk" science, that are used to label science as either good or bad. (6) More recently, it has led to dubious legislative actions, such as the Data Access Amendment (or "Shelby Amendment") and the Information Quality Act, that purport to be good-science reforms. (7) Both of these laws give the appearance of enhancing peer review and oversight of regulatory science, but their primary utility is as tools for partisan challenges to agency science. They appear, if anything, designed to heighten strife and to create new barriers to the effective use of science in regulatory decision making. (8)

These types of reforms succeed, in part, because of long-standing misconceptions about science. Critics on both sides of the debate, for example, baldly challenge environmental science for being reductive--a position akin to criticizing a painting by Picasso for its failure to represent its subject matter realistically--and ignore the unavoidable epistemological constraints. (9) Arthur Left has framed the dilemma incisively: "the less [a scientist] accepts as relevant, the less he can say that is not misleading; the more he accepts as relevant, the less he can say at all." (10) Environmental science is vulnerable to attack because striking this balance so often rests on tenuous grounds. (11)

Determining the proper role of science is complicated further by the thorny moral questions that are interwoven with methodological considerations. (12) Most risk assessments, for instance, focus on certain risks of human mortality, such as contracting cancer, while omitting other mortality risks and only rarely considering morbidity. (13) Yet, regardless of whether the relevant data are obtainable, undercounting potential risks to human health will skew the analysis. This blurring together of difficult methodological and moral judgments has exacerbated controversies over environmental science.

The image of science that has emerged from this debate is distorted by expectations that are simultaneously too great and too modest. By clinging to a classical vision of science, critics set environmental science up for failure; by presuming that scientific results are primarily the product of ideology, they risk trivializing their value. (14) These polarized views have mired debate between a world of inviolable, deterministic science and an overly cynical one in which science cannot be trusted unless it is purified of all corrupting influences.

This Article develops an alternative account of what science offers environmental policy. As prefigured above, the simple answer is that the power of science depends on the nature of the problem and the strength of the tools available to analyze it. Good science ranges from the highly precise and accurate methods found in the hard sciences (15) to heuristic models based on objective aggregating methods that expose general patterns in complex systems. (16) Science is thus inherently pluralistic, as the different scientific disciplines attest, and a unitary conception of environmental science is neither a desirable end nor a viable goal. (17)

It follows from this pluralistic view that a general standard for judging scientific results does not exist. Even the most widely accepted scientific convention, that empirical findings satisfy a ninety-five percent significance level, is not universal. (18) To give just one example, subtle effects can matter a lot in environmental policy. Just as stealing a penny from every bank account in the United States would make you rich, weak effects spread over large populations can, in the aggregate, have significant consequences. In such cases, statistical significance will rarely be met, but this failure only confirms the subtlety of the effect, not its absence. This does not diminish the value of statistical testing; it shows only that scientific standards cannot be applied mechanically and that, similar to legal rules, exceptions to them will exist.

This Article seeks to identify benchmarks for science that respect the contingencies of environmental problems (and policies) without lapsing into a serf-defeating form of scientific relativism. The Article begins by examining the controversy over the role of science in environmental law and placing it in a broader context by drawing on parallel debates in finance theory and ecology. It then argues that relatively simple models that embody aggregate patterns observed in a system, supplemented by narrower, more realistic assessments, are essential to understanding even the most complex environmental problems. The Article concludes by briefly identifying misconceptions that unnecessarily exacerbate the gulf often perceived between social values and quantitative methods.

II. SCIENCE BEYOND ENVIRONMENTAL LAW AND POLICY

The risks posed by industrial chemicals represent an extreme example of how implacable scientific problems can be. The methods available for testing chemicals are hampered, above all, by the complex biology of chemical toxicity and its sensitivity to context. (19) Matters are made worse by the subtlety of the effects, which frequently involve harms that are manifest in one person out of thousands. (20) The absence of effective testing methods have, in turn, impeded scientific understanding of the mechanisms underlying toxic responses that could aid in developing new experimental protocols or strengthening existing ones.

The stark nature of these uncertainties, combined with the human drama associated with toxic chemicals, has made toxics regulation a particularly salient issue politically. Failed or faulty regulation of industrial toxins has been the poster child, and at times the whipping post, for the false promise of science in environmental policy. (21) Thus, if commentators wish to expose the evils of "junk science" or to dramatize the significance of value judgments in technocratic approaches to policymaking, toxic risk assessment is the example of choice. (22)

Toxics issues have had a powerful effect on the current understanding of environmental science because of this high visibility. Rachel Carson's seminal book Silent Spring described the environmental harms of pesticides; the Three Mile Island meltdown threatened to release radioactive materials into the environment; and both Love Canal and Bhopal involved widespread exposure to toxic chemicals. (23) Current debates over genetically modified foods and nanotechnology also implicate toxic chemicals. (24) Unfortunately, the salience and uncertainties of toxics issues have polarized the debate and fueled the misperception that science is binary, either good or bad, when science actually spans a broad spectrum of degrees of accuracy and precision.

This section begins with a short discussion of the debate over the science of toxic substances and then looks beyond the domain of environmental law to identify appropriate benchmarks for the role of science in environmental policymaking. The logic of this strategy is straightforward. Just as complex problems are made more accessible by studying simple variants, so too will it be easier to evaluate scientific methods by studying them when their use is not limited by political pressures or resources.

A unique contribution of this Article is identification of such a field--finance theory and modeling. Financial markets provide an exemplary test bed for the practical application of sophisticated scientific methods. They equal, or exceed, the complexity of many natural systems, as suggested by the long history of economics and ecology influencing each other. (25) Equally important, the quantitative skill of financial modelers is superlative, and the resources on Wall Street are unrivaled. Even the strict instrumental rationality of financial analysts is a virtue, as it rigorously selects for scientific methods that work. Unlike environmental science, though, the moral implications of financial models are remote. Collectively these factors create a relatively unconstrained, pragmatic context for applying scientific methods to complex problems, and therefore for understanding the limits of their potential value.

A. Environmental Science in the Shadow of the Toxics Debate

Toxics regulation is intertwined with the long-standing debate over risk assessment, which is the broad analytical framework in which toxicological studies are utilized to establish environmental standards. The uncertainties inherent in risk assessment methods and chemical toxicology are infamous. (26) More than twenty years ago, the National Research Council identified almost fifty decision points in risk assessments for which "inference options" necessitate choosing between several scientifically plausible alternatives that cannot be resolved given existing uncertainties. (27) Legal scholars have frequently pointed to these inferential gaps to challenge the scientific authority of risk assessment methods and to object to them as implicating social values that transcend scientific expertise. (28)

These uncertainties and the resulting regulatory delays have very real consequences. (29) Failures to protect European workers against asbestos exposures before 1980, for example, may result in 250,000 additional cancers. (30) This failure, like many others, demonstrates the limits of epidemiological methods. (31) For example, even among the most heavily used chemicals, toxicity testing is sparse; there are no publicly available toxicity data for forty-three percent of the chemicals used in the highest volumes, and developmental toxicity testing is available for a mere seven percent. (32) Moreover, scientists are pessimistic about the prospects of achieving major advances through improvements in current toxicological test methods. (33)

Criticism of risk assessment methods crosses political lines. Supreme Court Justice Stephen Breyer is among those who have chronicled the many limitations and assumptions built into toxicological test methods. (34) Noting that animal studies, which dominate toxicological testing, are often subject to greater uncertainties than studies of humans, Justice Breyer goes on to describe their specific weaknesses:

The investigator applies a high dose of a supposed carcinogen to the animals; if they develop a higher than average number of tumors, the analyst tries to extrapolate backward to low doses in humans. What assumptions shall be made in doing so? What extrapolation model should be used? Risk analysts tend to use, for both animal and epidemiological studies, a linear model, which extrapolates backward on a straight line.... Critics argue that to use such mathematical models is like saying "If ten thousand men will drown in ten thousand feet of water, then one man will drown in one foot of water." The critics are right, in that there is no consistent scientific rationale for assuming a linear relation between dose and response. Some substances, such as cyanide, are proportionately as deadly in small doses as large ones; others, such as butter, are harmful only when consumed in large quantities; while still others, such as iodine, kill in high doses, are harmless in small doses, and in tiny doses are necessary for life. Science very often does not tell us which of these examples best applies. (35)

By suggesting that chemical toxicity estimates, at a certain point, amount to little more than educated guesses, Justice Breyer's characterization is a clear indictment.

In truth, the steps that Justice Breyer discusses are just the beginning of a longer process in which qualitative judgments are often determinative. Most assessments of whether a chemical is harmful are...

NOTE: All illustrations and photos have been removed from this article.



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