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The Challenges of Planning for High-Impact Research  

Brian L. Foster

In major universities, research must be seen in many dimensions: the different disciplines, basic vs. applied, incremental vs. transformative, disciplinary or interdisciplinary, single researcher or collaborative, and much more. A fundamental difference that receives increasing attention is the distinction between incremental research vs. transformative research. Incremental research takes existing research results to the next step while transformative research opens up whole new ways of framing questions, often challenging what is “known,” and leading to new paths of knowledge creation that could lead to new academic disciplines or completely new approaches to practical issues/problems. Incremental research is critical to bring existing results to their most valuable ends. Transformative research has high impact in opening up new paths to important knowledge, but it poses daunting challenges in being unpredictable, long term, and high risk. Providing appropriate infrastructure is critical for all kinds of research (e.g., facilities, lab space, special equipment, staff support). To assure sustained access to these resources, effective planning is necessary, which poses a significant challenge given the long-term, high-risk, and unpredictable nature of transformative research. To address these planning challenges, it is necessary to explore ways of creating an environment and resources that make successful transformative research more likely to happen rather than planning for incremental research. Such strategies include supporting uniquely powerful facilities that fit with academic strengths (e.g., a strong research reactor, radio-astronomy facility). Another is to maintain a supportive environment for interdisciplinary research. Yet another strategy is to orient performance evaluation away from productivity, which is the enemy of long-term, risky, unpredictable research. And lastly, it is critical to have a positive mindset for challenges to existing knowledge.


The Challenges of Making Research Collaboration in Africa More Equitable  

Susan Dodsworth

Collaborative research has a critical role to play in furthering our understanding of African politics. Many of the most important and interesting questions in the field are difficult, if not impossible, to tackle without some form of collaboration, either between academics within and outside of Africa—often termed North–South research partnerships—or between those researchers and organizations from outside the academic world. In Africa in particular, collaborative research is becoming more frequent and more extensive. This is due not only to the value of the research that it can produce but also to pressures on the funding of African scholars and academics in the Global North, alongside similar pressures on the budgets of non-academic collaborators, including bilateral aid agencies, multilateral organizations, and national and international non-government organizations. Collaborative projects offer many advantages to these actors beyond access to new funding sources, so they constitute more than mere “marriages of convenience.” These benefits typically include access to methodological expertise and valuable new data sources, as well as opportunities to increase both the academic and “real-world” impact of research findings. Yet collaborative research also raises a number of challenges, many of which relate to equity. They center on issues such as who sets the research agenda, whether particular methodological approaches are privileged over others, how responsibility for different research tasks is allocated, how the benefits of that research are distributed, and the importance of treating colleagues with respect despite the narrative of “capacity-building.” Each challenge manifests in slightly different ways, and to varying extents, depending on the type of collaboration at hand: North–South research partnership or collaboration between academics and policymakers or practitioners. This article discusses both types of collaboration together because of their potential to overlap in ways that affect the severity and complexity of those challenges. These challenges are not unique to research in Africa, but they tend to manifest in ways that are distinct or particularly acute on the continent because of the context in which collaboration takes place. In short, the legacy of colonialism matters. That history not only shapes who collaborates with whom but also who does so from a position of power and who does not. Thus, the inequitable nature of some research collaborations is not simply the result of oversights or bad habits; it is the product of entrenched structural factors that produce, and reproduce, imbalances of power. This means that researchers seeking to make collaborative projects in Africa more equitable must engage with these issues early, proactively, and continuously throughout the entire life cycle of those research projects. This is true not just for researchers based in the Global North but for scholars from, or working in, Africa as well.


University Technology Transfer in Innovation Management  

Tom Hockaday and Andrea Piccaluga

University technology transfer (UTT) has been growing in importance for many decades and is of increasing importance to university leadership, university researchers, research funding agencies, and government policy makers. It is of interest to academic researchers in the fields of business management, economics, innovation, geography, and public policy. UTT is a subset of the broader field of technology transfer, and it involves the transfer of university research results from the university to business so that the business can invest in the development of products and services that benefit society. The research results can arise from any academic discipline, are not limited to a particular definition of technology, and can be transferred to existing and new for-profit and not-for-profit organizations. The core activity involves licensing patent applications and other intellectual property to existing companies and establishing new companies that raise investment finance, to develop the early-stage research outputs into new products and services. In recent decades, research universities have set up technology transfer offices (TTOs) to manage their UTT activities. TTOs adopt a project management approach to supporting university researchers who wish to transfer the results of their research to business. Project stages include identifying, evaluating, protecting, marketing, deal making, and post-deal management. TTOs are also involved in other activities, beyond patenting, licensing, and entrepreneurship, which generate positive impact on society. Measuring and evaluating UTT is a topic of continuing debate, with an early focus on activity metrics developing into a more sophisticated assessment of the impact of university research outputs on society. Current issues in UTT involve understanding the position of UTT in the broader area of research impact, as well as funding and organization models for UTT within a university. The COVID-19 global crisis is highlighting the importance of university research and its transfer out to organizations that develop and deliver products and services that benefit society. It has further emphasized the importance of UTT as an activity where much more has to be researched and understood in order to maximize the benefits for society of all the activities performed by universities.


Evidence-Based Policy  

Linda Courtenay Botterill

Since the late 1990s, increased attention has been given by governments and scholars to evidence-based policymaking (EBPM). The use of the term EBPM appears to have emerged with the election of Tony Blair’s government in the United Kingdom (UK) and a desire to be seen to be taking ideology and politics out of the policy process. The focus was on drawing on research-based evidence to inform policymakers about “what works” and thereby produce better policy outcomes. In this sense, evidence-based policy is arguably a new label for an old concern. The relationship between knowledge, research, and policy has been a focus of scholarly attention for decades—Annette Boaz and her colleagues date it to as early as 1895 (Boaz et al., 2008, p. 234). In its more recent form, EBPM has been the subject of much debate in the literature, particularly through critiques that question its assumptions about the nature of the policy process, the validity of evidence, the skewing in favor of certain types of evidence, and the potentially undemocratic implications. The first concern with the concept is that the EBPM movement runs counter to the lessons of the critique of rational-comprehensive approaches to policymaking that was launched so effectively in Lindblom’s article “The Science of ‘Muddling Through’” and never really refuted, in spite of attempts by advocates of the policy cycle and other rational models. The second problem is that the rhetoric of evidence-based policy does not recognize the contested nature of evidence itself, an area that has been the subject of a large body of research in the fields of the sociology of science and science and technology studies. These studies draw attention to the value-laden nature of scientific inquiry and the choices that are made about what to research and how to undertake that research. Third, the emphasis has been on particular types of evidence, with particular methodologies being privileged over others, running the risk that what counts as evidence is only what can be counted or presented in a particular way. The choice of evidence is value-laden and political in itself. Finally, attempts to take the ideology or politics out of policy are also potentially undemocratic. Policymaking is the business of politics. In democratic systems, politicians are elected to implement their policies, and those policies are based on particular sets of values. Leaders are elected to make collective decisions on behalf of the electorate and those decisions are based on judgments, including value judgments. Evidence surely must inform this process, but, equally, it cannot be decisive. Trade-offs are required between conflicting values, such as between equity and efficiency, and this can include deciding between solutions that the evidence suggests are optimal and other societal priorities.


The Economics of Physics: The Social Cost-Benefit Analysis of Large Research Infrastructures  

Massimo Florio and Chiara Pancotti

In economics, infrastructure is a long-term investment aimed at the delivery of essential services to a large number of users, such as those in the field of transport, energy, or telecommunications. A research infrastructure (RI) is a single-sited, distributed, virtual, or mobile facility, designed to deliver scientific services to communities of scientists. In physical sciences (including astronomy and astrophysics, particle and nuclear physics, analytical physics, medical physics), the RI paradigm has found several large-scale applications, such as radio telescopes, neutrino detectors, gravitational wave interferometers, particle colliders and heavy ion beams, high intensity lasers, synchrotron light sources, spallation neutron sources, and hadrontherapy facilities. These RIs require substantial capital and operation expenditures and are ultimately funded by taxpayers. In social cost–benefit analysis (CBA), the impact of an investment project is measured by the intertemporal difference of benefits and costs accruing to different agents. Benefits and costs are quantified and valued through a common metric and using the marginal social opportunity costs of goods (or shadow price) that may differ from the market price, as markets are often incomplete or imperfect. The key strength of CBA is that it produces information about the project’s net contribution to society that is summarized in simple numerical indicators, such as the net present value of a project. For any RIs, consolidated cost accounting should include intertemporal capital and operational expenditure both for the main managing body and for experimental collaborations or other external teams, including in-kind contributions. As far as social intertemporal benefits are concerned, it is convenient to divide them into two broad classes. The first class of benefits accrue to different categories of direct and indirect users of infrastructure services: scientists, students, firms benefiting from technological spillovers, consumers of innovative services and products, and citizens who are involved in outreach activities. The empirical estimation of the use value of an RI depends on the scientific specificities of each project, as different social groups are involved to different degrees. Second, there are benefits for the general public of non-users: these benefits are associated with social preferences for scientific research, even when the use of a discovery is unknown. In analogy with the valuation of environmental and cultural goods, the empirical approach to non-use value aims at eliciting the willingness to pay of citizens for the scientific knowledge that is created by an RI. This can be done by well-designed contingency valuation surveys. While some socio-economic impact studies of RIs in physics have been available since the 1980s, the intangible nature of some benefits and the uncertainty associated with scientific discoveries have limited the diffusion of CBA in this field until recently. Nevertheless, recent studies have explored the application of CBA to RIs in physics. Moreover, the European Commission, the European Strategy Forum on Research Infrastructures, the European Investment Bank, and some national authorities suggest that the study of social benefits and costs of RIs should be part of the process leading to funding decisions.


Research Challenges and Innovative Methodologies, Approaches, and Processes  

S. Anthony Thompson

Investigative practices, including research methodologies, approaches, processes, as well as knowledge dissemination efforts continue to evolve within inclusive or special education. So too do such practices evolve within related fields such as nursing, psychology, community-based care, health promotion, etc. There are several research approaches that promote the tools required to effect inclusive education, such as: evidence-based practice (EBP), EBP in practice, creative secondary uses of (anonymous) data, collective impact, qualitative evidence synthesis (QES), and lines of action (LOA). Other approaches that promote a more inclusive education research agenda more generally, include action research and participatory action research, inclusive research, appreciative inquiry, and arts-based educational research.