Susan Cozzens

Among the new expectations articulated for S&T policy is strengthening social cohesion and reducing inequality (Conceicao 2003; Freeman 2000). An overly narrow emphasis on innovation for economic growth and competitiveness in Europe is being complemented with calls for quality of life objectives for research policy (Cozzens, Kallerud et al., 2007). In many developing countries, inequality is a prominent problem, and goals for science and technology are geared to address it (for example, Persley 1999, Singer 2005).

Nonetheless, the research and innovation policy community knows little empirically about the effects of its instruments on social cohesion. On the one hand, those instruments may inadvertently reinforce or exacerbate existing inequalities; but there have been few studies of those effects. On the other hand, outside the domain of human resources, there is little empirical evidence on the effectiveness of S&T program designed to reduce inequalities.

This paper presents preliminary results from a cross-national, cross-technology study of the distributional effects of emerging technologies.2 The research aims to

1. Describe the dynamics that link emerging technologies to patterns of inequality;
2. Identify the roles of public interventions in those dynamics; and
3. Develop a framework that policy actors can use prospectively to analyze the distributional valence of a specific new technology in a particular national context. Our central research question is how policy interventions affect distributional outcomes for the same technology under different national conditions.

Innovation is a process of problem solving. In its broadest sense, innovation means doing things in new ways. When conditions change and routines no longer work, humans experiment and learn. In a narrower sense, innovation means developing new ideas into new products or processes. Whether the process happens in the public domain or in the market, the sign of successful innovation is something new being used widely to solve a problem.

Many problems that face humanity today take on global dimensions, and their solutions are likely to involve cooperation as well as competition across national boundaries. Global climate change is the clearest example: human activity has set changes into motion that affect people in various parts of the world in ways that they did not choose but have to work together to address. Disease is another example, in which growing networks of transportation are spreading pathogens faster and wider than ever. No one country can protect its health without joint information gathering and international public health efforts.

To address global challenges, humanity needs to be able to solve problems at global scale. In our research, we aim to deepen understanding of one form of global problem-solving, namely, global systems of innovation. A global system of innovation (GSI) is a learning space (Arocena and Sutz 2000) in which a multi-level network of diverse actors interacts to address a world-level challenge, accumulating knowledge across national borders and developing, testing, and adopting new approaches.

This paper helps to develop the GSI concept using information on responses to global challenges in the household water supply and sanitation sector (WSS).3 In this research, we use a broad concept of innovation that encompasses both new technologies and new approaches, such as community-demand driven systems and privatization.4 The paper reports preliminary observations based on interviews with nearly100 people who work in organizations in the sector, at global, national, and local levels, including intensive interviews in Costa Rica, Mozambique, and South Africa. In addition, we have analyzed the published literature in this area and consulted an extensive set of documentary sources.

The first section of the paper introduces the concept of a global system of innovation. The second section describes how preliminary data from the WSS sector match or modify the GSI concept. The final section raises further research questions and points to possible policy implications.

Over the last four years, a new generation of research on science and innovation policy has begun in the United States. The development is very welcome after a hiatus in funding for the field of a decade or more. Although research in the new generation builds on a solid base of earlier scholarship, the new wave is quite different from its
predecessors in a variety of ways. This paper reviews the past development of the field and describes the emergence of the present generation, pointing to its distinctive structural features.

In brief, the first generation of science and innovation policy studies (SIPS) was commissioned through policy analysis offices whose primary mission was short-term analysis of current issues directly for decision makers. Research done in this mode had a high probability of being useful in the policy process, both because its subjects were prescreened and because there was an intermediate organization that absorbed the results and
applied them in short-term policy analysis requested by decision makers. In this paper, I call this the mediated model for policy-relevant research.

The second generation of SIPS, in contrast, is steered more generally by a roadmap developed collectively across government agencies, and the research program that supports it is working on building a broader “community of practice” that includes agency and Congressional staff, short-term analysts, and researchers. In this paper, I call
this the distributed model for policy-relevant research.

It is impossible to compare the results of the two models -- too late to collect data for the first generation and too early to see the results of the second. They are by no means mutually exclusive. Both belong on any menu of options for new program structures in other countries.

Among the new expectations articulated for S&T policy is strengthening social cohesion and reducing inequality (Conceicao 2003; Freeman 2000). An overly narrow emphasis on innovation for economic growth and competitiveness in Europe is being complemented with calls for quality of life objectives for research policy (Cozzens, Kallerud et al., 2007). In many developing countries, inequality is a prominent problem, and goals for science and technology are geared to address it (for example, Persley 1999, Singer 2005).

Nonetheless, the research and innovation policy community knows little empirically about the effects of its instruments on social cohesion. On the one hand, those instruments may inadvertently reinforce or exacerbate existing inequalities; but there have been few studies of those effects. On the other hand, outside the domain of human resources, there is little empirical evidence on the effectiveness of S&T program designed to reduce inequalities.

This paper presents preliminary results from a cross-national, cross-technology study of the distributional effects of emerging technologies.2 The research aims to

1. Describe the dynamics that link emerging technologies to patterns of inequality;
2. Identify the roles of public interventions in those dynamics; and
3. Develop a framework that policy actors can use prospectively to analyze the distributional valence of a specific new technology in a particular national context. Our central research question is how policy interventions affect distributional outcomes for the same technology under different national conditions.

Innovation is a process of problem solving. In its broadest sense, innovation means doing things in new ways. When conditions change and routines no longer work, humans experiment and learn. In a narrower sense, innovation means developing new ideas into new products or processes. Whether the process happens in the public domain or in the market, the sign of successful innovation is something new being used widely to solve a problem.

Many problems that face humanity today take on global dimensions, and their solutions are likely to involve cooperation as well as competition across national boundaries. Global climate change is the clearest example: human activity has set changes into motion that affect people in various parts of the world in ways that they did not choose but have to work together to address. Disease is another example, in which growing networks of transportation are spreading pathogens faster and wider than ever. No one country can protect its health without joint information gathering and international public health efforts.

To address global challenges, humanity needs to be able to solve problems at global scale. In our research, we aim to deepen understanding of one form of global problem-solving, namely, global systems of innovation. A global system of innovation (GSI) is a learning space (Arocena and Sutz 2000) in which a multi-level network of diverse actors interacts to address a world-level challenge, accumulating knowledge across national borders and developing, testing, and adopting new approaches.

This paper helps to develop the GSI concept using information on responses to global challenges in the household water supply and sanitation sector (WSS).3 In this research, we use a broad concept of innovation that encompasses both new technologies and new approaches, such as community-demand driven systems and privatization.4 The paper reports preliminary observations based on interviews with nearly100 people who work in organizations in the sector, at global, national, and local levels, including intensive interviews in Costa Rica, Mozambique, and South Africa. In addition, we have analyzed the published literature in this area and consulted an extensive set of documentary sources.

The first section of the paper introduces the concept of a global system of innovation. The second section describes how preliminary data from the WSS sector match or modify the GSI concept. The final section raises further research questions and points to possible policy implications.

Over the last four years, a new generation of research on science and innovation policy has begun in the United States. The development is very welcome after a hiatus in funding for the field of a decade or more. Although research in the new generation builds on a solid base of earlier scholarship, the new wave is quite different from its
predecessors in a variety of ways. This paper reviews the past development of the field and describes the emergence of the present generation, pointing to its distinctive structural features.

In brief, the first generation of science and innovation policy studies (SIPS) was commissioned through policy analysis offices whose primary mission was short-term analysis of current issues directly for decision makers. Research done in this mode had a high probability of being useful in the policy process, both because its subjects were prescreened and because there was an intermediate organization that absorbed the results and
applied them in short-term policy analysis requested by decision makers. In this paper, I call this the mediated model for policy-relevant research.

The second generation of SIPS, in contrast, is steered more generally by a roadmap developed collectively across government agencies, and the research program that supports it is working on building a broader “community of practice” that includes agency and Congressional staff, short-term analysts, and researchers. In this paper, I call
this the distributed model for policy-relevant research.

It is impossible to compare the results of the two models -- too late to collect data for the first generation and too early to see the results of the second. They are by no means mutually exclusive. Both belong on any menu of options for new program structures in other countries.

Inequality is an important global challenge. Inequalities between countries are growing. While some poor countries are rapidly expanding their economies, others are stuck at a low level and the gap is therefore widening between countries. Inequality is also growing within many countries, including affluent ones. Inequalities in basic needs such as food and water violate human rights as identified by the international community.

An inequality is a barrier ¨C a steep differential that someone must scale to achieve his or her full potential. Human progress as a whole is therefore hampered by inequalities, which keep our efforts from adding up to all they could. This happens through vertical inequalities, differences between individuals and households generated by the structure of the economy, and through horizontal inequalities, differences by culturally-defined categories like gender, ethnicity, and religion.

Why talk about inequalities in the context of science, technology, and innovation (STI) policies? On the one hand, STI policies link directly to basic needs, when they deal with food, health, and the environment ¨C all topics that are virtually universal on national STI policy agendas. On the other hand, STI policies link indirectly to inequalities in income when they affect the dynamics of economic growth. STI policy practitioners think of their work as providing a public benefit, but any public intervention can contribute to cumulative advantage if it is more accessible to the members of society who have greater resources. Public interventions, including STI policies and programs, need to be specifically designed to reach disadvantaged groups if they want to be redistributive.

My colleagues and I distinguish three types of redistributive policies: (1) Pro-poor policies aim to reduce poverty or alleviate its conditions. (2) Fairness policies work on eliminating horizontal inequalities, e.g. by gender or race. (3) Egalitarian policies attempt to reduce vertical inequalities, through economic activities that increase income for people in the middle of the distribution. I illustrate each type here, drawing on a mix of research, human resource, and innovation policies from the STI realm.

Global inequality is a changing phenomenon molded by a variety of interlocking dynamic forces. Technological change is one of these. If we picture the world system as a cross-tabulation of nation states and technological capabilities, we see a core of advanced and advancing nations, a small set of countries rapidly developing their capabilities, and a large number of countries struggling to maintain or build (Sagasti 2004). These groups correspond roughly to the economic hierarchy of nations, in which only four countries have moved into the top group in the last five decades: South Korea, Taiwan, Singapore, and Hong Kong (Milanovic 2005). It is no accident that these four are also the models constantly offered for technology-based economic development.

Dr. John Marburger’s recent calls for a new science of science policy open up new opportunities to reconceptualize, retest, and revise as needed the theories, models, descriptions, and mainstream propositions underlying United States’ science and innovation policies and programs.

We respond to these calls by presenting a research agenda directed at two objectives. First, as academic researchers who have long worked in the field of science and innovation policy, albeit from different analytical and disciplinary perspectives, we seek to insure that efforts to promote the “science” of science and technology, or innovation policy produce substantive scholarly work that in fact advances our fundamental understanding of underlying processes. Second, as participants in numerous U.S. and international science and innovation policy advisory forums and commissions, we seek to promote a closer, better fitting, coupling between the research communities who are addressing questions of the science of science policy -- themselves a disparate disciplinary lot -- with the policy communities who are seeking improved understandings of whether or how the decisions they have made or are being called upon to make in fact have led to the intended results. Our strategy to achieve these two objectives is to identify questions that are simultaneously intellectually challenging and policy relevant.