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9 - Two Models for Scientific Transparency in Environmental Law

Published online by Cambridge University Press:  04 August 2010

David E. Adelman Ph.D., J.D.
Affiliation:
associate professor, University of Arizona
Wendy Wagner
Affiliation:
University of Texas, Austin
Rena Steinzor
Affiliation:
University of Maryland, Baltimore
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Summary

Transparency in Science and in Law

Maximizing the transparency of scientific determinations is critically important to the disciplines that inform environmental policy. Environmental issues are riven by disputes over the use of quantitative methods and by uncertainty about risk. Despite the obvious limits of science, or perhaps because of them, agency officials and political actors who use science often fail to represent scientific uncertainty accurately, and instead overstate the role that science played in supporting particular findings to elevate the outcomes to which they are predisposed. As a result, science without transparency risks devolving into consequentialist science.

Chemical risk assessment provided the impetus for much of the debate over how science is used in a regulatory context. Objections to chemical risk assessment methods stem from the high uncertainties in risk estimates that exist at the low exposure levels relevant to regulatory standards. The controversy is also driven by the potential consequences of inaction – failures to protect workers against asbestos exposures, for example, may result in 250,000 additional cancers in the United States. These uncertainties require scientists to make difficult judgments, including critically important decisions to rely on highly simplified models to obtain the quantitative results needed to derive regulatory standards.

The vulnerability of scientific judgment to political pressure is evident in the high-profile controversies surrounding the Bush Administration's stacking of scientific advisory committees in agencies throughout the federal government.

Type
Chapter
Information
Rescuing Science from Politics
Regulation and the Distortion of Scientific Research
, pp. 193 - 214
Publisher: Cambridge University Press
Print publication year: 2006

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