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Closing the Gap: S&T, Evaluation, and Inequalities

This presentation explores the connections between science and technology policies and programs, and the resulting inequalities. It aims to find ways to design and evaluate these policies and programs to reduce rather than increase inequalities.

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Closing the Gap: S&T, Evaluation, and Inequalities

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  1. Closing the Gap: S&T, Evaluation, and Inequalities Susan E. Cozzens Technology Policy and Assessment Center School of Public Policy Georgia Institute of Technology scozzens@gatech.edu Presented at the American Evaluation Association Annual Meeting, Toronto, Ontario, 27 October 2005

  2. Collaborators, Colleagues, and Support • AAAS Committee on Science, Engineering, and Public Policy, especially Steve Nelson • Graduate students: Kamau Bobb, Isabel Bortagaray, Albert George, Kendall Deas, Sonia Gatchair, Gonzalo Ordonez • Colleagues: Tim Turpin, Johann Mouton, Peter Healey • Supported by NSF Grants SES 0354362 and SES 0354356 Evaluation and Inequality, Cozzens, AEA 2005

  3. Science, technology, and inequalities • Question: What are the connections between S&T policies and programs and inequalities? • Goal: Find ways to design and evaluate S&T policies and programs so that they reduce rather than increase inequalities. Evaluation and Inequality, Cozzens, AEA 2005

  4. Outline of presentation • Issues of scope • Descriptive summary: what are the connections now? • Options and issues • for program design • for evaluation Evaluation and Inequality, Cozzens, AEA 2005

  5. Inequality is deep and growing • In the United States • Income inequality has been rising steadily for several decades. • Health disparities persist. • Globally • Gap between rich and poor nations is growing. • Life expectancies can be twice as much in rich nations as poor ones. • Wealth is accumulating fast in some parts of the global economy and not in others. Evaluation and Inequality, Cozzens, AEA 2005

  6. What dimensions? • Economic inequalities (goal: reducing inequality) • High, middle, and low income regions • High, middle, and low income individuals and families within regions • Poverty vs. inequality • The identity inequalities (Goal: achieving equality) • Gender • Ethnic • Creates three-dimensional space Evaluation and Inequality, Cozzens, AEA 2005

  7. Who cares? • Inequality is a multi-dimensional space • We have been focusing on inequalities in basic needs areas: health, food, environment • Distributional ethics • Libertarian theory – rights based • Utilitarian – maximize the Good • Rawlsian – benefit the least advantaged • Communitarian – decrease inequality for the sake of community Evaluation and Inequality, Cozzens, AEA 2005

  8. Types of S&T Policies Government actions to … • Research: stimulate production of new knowledge • Innovation: stimulate new products or processes • Human Resource: recruit and educate a scientific and technical workforce Evaluation and Inequality, Cozzens, AEA 2005

  9. Central hypothesis Unless they are specifically designed to reduce inequality, these policies probably increase it. Evaluation and Inequality, Cozzens, AEA 2005

  10. Human resource policies • Recruitment to S/E careers is not neutral on gender or ethnic status – witness the results. • Causes lie up and down the education and career chain • Within countries: • Gender and ethnic status are rising as conscious goals in this area. • Economic status gets little or no attention. • Between countries: • International mobility of S/E – the world is flattening. Evaluation and Inequality, Cozzens, AEA 2005

  11. Innovation policies • Income inequality within rich countries attributed to skill-biased technological change • Education seen as the panacea solution • High technology development strategies focus on growing the upper end of the distribution. • But may provide new entry points for under-represented groups. • Intellectual property laws protect the accumulation of wealth. • And therefore limit access to products, sometimes ones that are essential for basic needs. Evaluation and Inequality, Cozzens, AEA 2005

  12. Research policies • Often seen as both “the problem” and “the solution” to inequality problems • Relatively accessible to civil society • The content of the research agenda is the issue. • Orientation to industry makes this a subset of innovation policy. • Organized public has an influence – in some areas, but unlikely to work very effectively on global gaps. Evaluation and Inequality, Cozzens, AEA 2005

  13. Summary • S&T policies are part of the problem. • They are also seen as part of the solution. • Our analyses moved in two directions: • Technology-based economic development strategies • Case studies in research and innovation policies. Evaluation and Inequality, Cozzens, AEA 2005

  14. Technology-based economic development • “High-technology” strategy • Goal: produce high-skill, high-wage jobs • Adds jobs at the high end of the distribution • Increases inequality by definition if it succeeds • “Good jobs” strategy • Add jobs in the middle of the distribution • “Better life” strategy • Make life better for those at the lower end of the distribution Evaluation and Inequality, Cozzens, AEA 2005

  15. Case studies • Access to essential medicines • Patent policy issue • Use provision for public march-in • Health disparities research • Multi-pronged approach • African agriculture • Institutional design for distributed innovation Evaluation and Inequality, Cozzens, AEA 2005

  16. Generic approaches • Derived from case studies; see summary available • Vary in breadth of participants • Participatory • Capacity building • Public research • Private sector stimulation Evaluation and Inequality, Cozzens, AEA 2005

  17. More hypotheses • The more empowering the approach, the more likely it is to lead to long-term, sustainable inclusion. • The more involved the affected community, the more likely the approach is to set priorities that reduce inequality. Evaluation and Inequality, Cozzens, AEA 2005

  18. Implications for program design • Need to take inequalities explicitly into account. • Need to think about process as well as product. • Total outcome should look more equal on several dimensions. Evaluation and Inequality, Cozzens, AEA 2005

  19. Implications for evaluation • Need to measure impacts in several dimensions • Economic • Gender • Ethnic status • Easy? Evaluation and Inequality, Cozzens, AEA 2005

  20. Impact indicators • Long-standing quest in the indicators community • No lack of impact indicators themselves • Lack the logic that connects them to research programs • Leads to work with logic modeling Evaluation and Inequality, Cozzens, AEA 2005

  21. Generic Logic Model Next-stage Users: Public Outcomes In Everyday Life S&T Policy or Program Public MARKETS Private Next-stage Users: Private Evaluation and Inequality, Cozzens, AEA 2005

  22. Am Heart Assoc Am Soc Hyper­ tension NHLBI -- Natl Heart Lung and Blood Institute: Research Other voluntary health orgs Place of work Patients with high blood pressure Centers for Disease Control Education Programs GA Dept of Public Health Community organizations Primary care physician Pharmaceu­ tical ndustry: Drugs Lifestyle National Center for Minority Health and Health Disparities: Research Health Disparity Centers Hypertension Evaluation and Inequality, Cozzens, AEA 2005

  23. Department of Energy Department of Defense Private philanthropies GA Dept Community Affairs USDA Nat Res Cons Service Black and low income families live with environmental contamination Black and Low Income Communities: research and action EPA: EJ Program GA Env Protection Division Industry: source of pollution and mitigation Community pollutants Evaluation and Inequality, Cozzens, AEA 2005

  24. Hunger in Georgia Food Banks (private) Food insecure and hungry families Food stamps and school lunches (USDA) Food industry programs Evaluation and Inequality, Cozzens, AEA 2005

  25. 21 national programs, plus regional cooperative programs Major research institutions, with research agenda Field trials, by who is doing them IP skills Packaging and sale Biosafety processes Farmer acceptance Hectares planted; increased productivity Lower urban food prices Increased rural incomes Biotechnology example Evaluation and Inequality, Cozzens, AEA 2005

  26. Conclusions so far • The key step is paying attention to inequalities. • The benefits of S&T are not automatically distributed equally. • Consideration can be built into strategic planning and performance assessment. • Need to accumulate knowledge from specific programs into overall principles of distributional impacts. Evaluation and Inequality, Cozzens, AEA 2005

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