The use of the phrase “basic research” as a term used in science policy discussion dates only to about 1920. At the time the phrase referred to what we today commonly refer to as applied research in support of specific missions or goals, especially agriculture. Upon the publication of Vannevar Bush’s well-known report, Science – The Endless Frontier, the phrase “basic research” became a key political symbol, representing various identifications, expectations and demands related to science policy among scientists and politicians. (...) This paper tracks and evaluates the evolution of “basic research” as a political symbol from early in the 20th century to the present. With considerable attention having been paid to the on-going evolution of post-Cold War science policy, much less attention has focused on the factors which have shaped the dominant narrative of contemporary science policies. (shrink)

Today many scholars seem to agree that citizens should be involved in expert deliberations on science and technology issues. This interest in public deliberation has gained attraction in many practical settings, especially in the European Union, and holds the promise of more legitimate governance of science and technology. In this article, the authors draw on the European Commission’s report ‘‘Taking the European Knowledge Society Seriously’’ to ask how legitimate these efforts to ‘‘democratize’’ scientific expertise really are. While the report borrows (...) from deliberative democrats’ normative accounts of legitimacy, the authors identify a tension between the principles for legitimate rule prescribed by deliberative democratic theory and the report’s celebration of diversity and dissent. While this inconsistency suggests that the legitimacy of deliberative governance arrangements is justified on empirical rather than normative grounds, it remains an open question whether studies of science and technology offer enough empirical support for such a justification. In this article, the authors address this pressing question and propose three possible responses. (shrink)

This paper critiques the so-called “Green Revolution” as a political myth of averted famine. A “political myth,” among other functions, reflects a narrative structure that characterizes understandings of causality between policy action and outcome. As such, the details of a particular political myth elevate certain policy options over others. One important narrative strand of the political myths of the Green Revolution is a story of averted famine: in the 1950s and 1960s, scientists predicted a global crisis to emerge in the (...) 1970s and beyond, created by a rapidly growing global population that would cause global famine as food supplies would not keep up with demand. The narrative posits that an intense period of technological innovation in agricultural productivity led to increasing crop yields which led to more food being produced, and the predicted crisis thus being averted. The fact that the world did not experience a global famine in the 1970s is cited as evidence in support of the narrative. Political myths need not necessarily be supported by evidence, but to the extent that they shape understandings of cause and effect in policymaking, political myths which are not grounded in evidence risk misleading policymakers and the public. We argue a political myth of the Green Revolution focused on averted famine is not well grounded in evidence and thus has potential to mislead to the extent it guides thinking and action related to technological innovation. We recommend an alternative narrative: The Green Evolution, in which sustainable improvements in agricultural productivity did not necessarily avert a global famine, but nonetheless profoundly shaped the modern world. More broadly, we argue that one of the key functions of the practice of technology assessment is to critique and to help create the political myths that preserve an evidence-grounded basis for connecting the cause and effect of policy action and practical outcomes. (shrink)

The president’s science advisor was formerly established in the days following the Soviet launch of Sputnik at the height of the Cold War, creating an impression of scientists at the center of presidential power. However, since that time the role of the science advisor has been far more prosaic, with a role that might be more aptly described as a coordinator of budgets and programs, and thus more closely related to the functions of the Office of Management and Budget than (...) the development of presidential policy. This role dramatically enhances the position of the scientific community to argue for its share of federal expenditures. At the same time, scientific and technological expertise permeates every function of government policy and politics, and the science advisor is only rarely involved in wider White House decision making. The actual role of the science advisor as compared to its heady initial days, in the context of an overall rise of governmental expertise, provides ample reason to reconsider the role of the presidential science advisor, and to set our expectations for that role accordingly. (shrink)

In recent years, US policy makers have faced persistent calls for the price of flood and hurricane insurance cover to reflect the true or real risk. The appeal to a true or real measure of risk is rooted in two assumptions. First, scientific research can provide an accurate measure of risk. Second, this information can and should dictate decision-making about the cost of insurance. As a result, contemporary disputes over the cost of catastrophe insurance coverage, hurricane risk being a prime (...) example, become technical battles over estimating risk. Using examples from the Florida hurricane rate-making decision context, we provide a quantitative investigation of the integrity of these two assumptions. We argue that catastrophe models are politically stylized views of the intractable scientific problem of precise characterization of hurricane risk. Faced with many conflicting scientific theories, model theorists use choice and preference for outcomes to develop a model. Models therefore come to include political positions on relevant knowledge and the risk that society ought to manage. Earnest consideration of model capabilities and inherent uncertainties may help evolve public debate from one focused on “true” or “real” measures of risk, of which there are many, toward one of improved understanding and management of insurance regimes. (shrink)