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Introduction

The social in social science: The challenge of change - OpenLearn - Open University - D_1

OSO version 0. University Press Scholarship Online. Sign in. Not registered? Sign up. Publications Pages Publications Pages. Search my Subject Specializations: Select Users without a subscription are not able to see the full content. Instead, multiple descriptive policy process models offer ways to understand how policy is made and how science might enter into that process. There are, for example, rational models—including linear, cycle or stage, incrementalism, and interactive.

There are models that question rational model assumptions, including behavioral economics, path dependency, and bureaucratic inertia. There are political models, including policy networks, agenda setting, policy narratives, advocacy coalition frameworks, punctuated equilibrium theory, and deliberative analysis models see Baumgartner and Jones, ; Hajer and Wagenaar ; Kingdon, ; Lindblom, ; Neilson, ; Sabatier, ; Sabatier and Jenkins-Smith, ; Stone, Maxwell, and Keating, There are models that focus on different stages of the policy process and thus on different ways that social science can contribute, including: descriptive analyses that present conditions needing policy attention, such as a slowdown in small business start-ups; social indicators that document long-term trends, such as gender differences in pay scales; social experiments on alternative policy designs, such as school vouchers; and evaluation research on the effectiveness of a policy, such as neighborhood policing.

Political science is the discipline that has devoted the most attention to the policy process. On the issue of use, it has reached a general conclusion Henig, in press :. Although generalizations about an entire discipline inevitably are oversimplifications, the center of gravity within the field encourages skepticism about proposals for a rational, comprehensive, science of public policy making and regards data and information as sources of power first and foremost. It is difficult to assess how widely this characterization is accepted outside of political science, but it is clear that the various models and frameworks do not coalesce into anything remotely resembling a powerfully predictive, coherent theory of policy making.

Lacking that, it is improbable and perhaps impossible to reach a widely agreed-upon understanding of the use of science in policy making. A political psychologist at the Central Intelligence Agency concerned with what transforms an angry, unemployed teenager into a terrorist uses research evidence very differently from an economist at the RAND Corporation designing a randomized controlled field trial RCFT on classroom size and school performance.

Many researchers underscore the conceptual confusion about use and conclude that different definitions of use are needed and appropriate for different purposes e. This conclusion is consistent with the fact that policy choices are context dependent. A school district deciding whether to establish charter schools is less interested in a comparative study of charter and public schools across the country than in wanting to know how well a charter school will perform under its conditions, which differ depending on whether the district is in the central city or suburb, with a homogenous or diverse population, with a historically competent or incompetent school administration.

The usefulness of research is not assessed in terms of variance explained from a large sample of schools, but whether it is informative about a very specific choice.

Given the context-dependent nature of the use of science, typologies are a common way of mapping the landscape for a summary, see Nutley et al. A frequently cited typology is that of Weiss , ; see also Weiss et al. Other scholars add a fifth category, symbolic or ritualistic use—that is, the organizational practice of collecting information with no real intent to take it seriously, except to persuade others of a predetermined position or even to delay action Leviton and Hughes, ; Shulha and Cousins, It is a frequent complaint among scientists that policy makers use scientific evidence as confirmation of prior beliefs.

This complaint, however, overlooks the fact that, when policy makers argue on the basis of evidence, it is more difficult for their opponents to ignore that evidence, or to leave it unchallenged. Weiss emphasizes that each of the four uses—which also applies to the fifth use noted—can be found in particular situations, but that no one of them offers a complete picture. Scholars who debate typologies of use generally conclude that, although typologies are heuristically valuable, they are not easily applied empirically.

In fact, it is unlikely that users themselves can make sharp distinctions in explaining how they use knowledge Contandriopoulos et al. Typologies of use fail to meet the standard criteria of scientific typologies in which each category consists of an internally coherent set of variables,.

In the periodic table of chemical elements, for example, hydrogen is distinguished from other chemical elements by its atomic weight, its specific gravity, its bonding properties, the temperature at which it freezes and boils, and other traits.

Each of these traits differs consistently and predictably from those same traits in helium or in any other chemical element see Stinchcombe, In the social world it is impossible, in any practical sense, to construct typologies that meet this standard. Typologies of social conflict, ethnic or racial groups, or government corruption are never going to have categories with internally coherent variables whose values covary in completely predictable ways. It is unrealistic to expect a clear and unambiguous typology for a phenomenon as complex as the use of science in policy.

To address the charge given to this committee—to understand the use of science in policy—is thus to simultaneously deal with three elusive phenomena:.

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With this challenging landscape in mind, we turn to the recent scholarship on knowledge utilization. The scholarship on knowledge utilization has, virtually from its beginnings, been skeptical of rational models of the relationship between research and policy. Rational models assume that decisions unfold through five stages Nutley and Webb, , p. A policy problem requiring action is identified and goals, values, and objectives are clearly set forth;. All significant ways of addressing the problem and achieving the goals or objectives are enumerated;.

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The consequences are then compared with the goals and objectives; and. A strategy is selected in which consequences most closely match the goals and objectives. Weiss and Bucuvalas , p. Criticisms of this model have focused on several significant defects; for example, that decisions made are optimal, that is, based on complete information and an examination of all possible alternative courses of action see the work of Simon [], who introduced satisficing as a replacement for maximizing ; or, that the model is a normative account of policy making see the work of Braybrooke and Lindblom [] and Lindblom [], authors who substitute incrementalism for rational models.

More recent examinations of the relationship between research and policy making echo these concerns.

The Production of Knowledge: The Challenge of Social Science Research

For example, Gormley , pp. A hypodermic needle theory of scientific impact on policy, which anticipates direct, immediate, and powerful effects, is flawed for several reasons. First, scientific research is one of many inputs into the policy process. Fifth, the use of scientific information by public officials, when it is occurs, is more likely to involve justification.

There also are situations in which a user is considered sovereign in her or his capacity to mobilize evidence and, consequently, to modify her or his behavior on the basis of that evidence—for example, the choice of a preferred clinical treatment Contandriopoulos et al. But these examples are exceptions to the rule, and uncommon at that. It is estimated that evidence-based programs accounted for less than 0.

No single decision maker has the independent power to translate and apply research knowledge. In criticizing rational models and decisionist thinking, Weiss and others suggest that use is less a matter of straightforward application of scientific findings to discrete decisions and more a matter of framing issues or influencing debate Weiss, , p.


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Social science research does not so much solve problems as provide an intellectual setting of concepts, propositions, orientations and empirical generalizations. They come to play a part in how policy makers define problems and the options they examine for coping with them. Bush administration piloted a program linking federal financing to clear demonstration of program effectiveness. Although Weiss suggested that this enlightenment model is perhaps the way science is most frequently used in policy making, she did not claim it was the way it ought to happen.

Knowledge utilization research, in agreement about what is ruled out, is less clear about what should be ruled in. Viewing use from the perspective of two communities has been a recurring motif in knowledge utilization studies see Caplan, The basic idea is refreshingly simple. Scientists and policy makers are separated by their languages, values, norms, reward systems, and social and professional affiliations. The primary goal of scientists is the systematic search for a reliable and accurate understanding of the world; the primary goal of policy makers is a practical response to a particular public policy issue.

Like any binary distinction, this one oversimplifies, though there is a crude truth to several distinctions rooted in the different tasks facing researchers and policy makers. They differ in the outcomes they value—knowledge about the world in all its complexities versus knowledge helpful in reaching feasible solutions to pressing problems—and in the incentives, rewards, and cultural assumptions associated with these different outcomes.

They also differ in habits of expression—probabilistic versus certain statements about conditions or people. And they differ even in modes of. Differences between the two communities are associated with a contrasting list of supply-side and demand-side problems Bogenschneider and Corbett, ; Furhman, ; Nutley et al. On the supply side are researchers who fail to focus on policy-relevant issues and problems, cannot deliver research in the time frame generally necessary for effective policy making, do not relate findings from specific studies to the broad context of a policy issue, ineffectively communicate their findings, depend on technical arguments that are inaccessible to policy makers, and lack credibility because of perceived career interests or even partisan biases.

On the demand side are policy makers who fail to spell out objectives in researchable terms, have few incentives to use science, and do not take time to understand research findings relevant to pending policy choices. This framing of the use problem offers little guidance as to which of the long list of factors, from either side, best explains variance in use, let alone how the factors interact and whether they apply only in specific settings or have general applicability Bogenschneider and Corbett, ; Johnson et al.

Although the two communities framework has been helpful in understanding the differing expectations of researchers and policy makers and problems of communication between them, it has not been able to offer a systematic explanation of use. Thinking about how best to bridge the gap between the two communities has, however, led to practices of translation and brokering and to more intensive interactions between researchers and policy makers. Translation is a supply-side solution to the use problem.

It was developed in clinical diagnostic, preventive, and therapeutic practices. The idea is simple: basic science is translated into clinical efficacy, efficacy is translated into clinical effectiveness, and effectiveness is translated into everyday health care delivery Drolet and Lorenzi, Department of Health and Human Services initiative, Translating Research into Practice TRIP Program, that focuses on implementation techniques and factors associated with successfully translating research findings into diverse applied health care settings see Agency for Healthcare Research and Quality, Translational strategies have now moved beyond health care, introducing additional and somewhat differently focused activities.

One is evidence-based registries, a compilation of scientifically proven interventions. They are considered tools to improve practice in various fields, including social services, criminal justice, and education. Language English. Creator Starbuck, William H. Medium [electronic resource] Content Types text Carrier Types online resource Physical Description 1 online resource vii, pages : illustrations. Subjects Starbuck, William H. Organization -- Research.


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