The Importance of Strong Cross-Sectoral Partnerships

Cross-sectoral partnerships are a key distinguishing characteristic of HIBAR research projects. 

By “cross-sectoral”, we mean partnerships between university researchers and individuals in external organizations, including industry, government, non-profit organizations, civil society, and communities of practice. Importantly, these individuals are knowledgeable of the societal problem that is being addressed by the HIBAR project and they participate in the project as equal partners

What are the distinguishing characteristics of these cross-sectoral partnerships?

  • Partners share an overarching goal to both discover new knowledge and address a specific societal problem.
  • Partners “co-lead” the research: academics and external partners are together actively involved in all phases of the research activity, including consequential decisions related to the research. 

The shared goals and shared decision-making are essential components of these partnerships, because the diverse perspectives that partners bring to the project mean that, together, they make wiser decisions about the direction, participants, and activities within the project – from the start and throughout. (This type of partnership is often what people describe when they refer to “co-production” and “co-creation”.)

Examples of strong cross-sectoral partnerships in successful HIBAR research projects:  

Rebuilding Civic Education

Generations of U.S. students have not received the high quality education in history and civics that they need, and deserve, and the time has come to rebuild civic education. Leaders of an inspiring and large-scale HIBAR project, the Educating for American Democracy initiative, set out to tackle the challenge of developing a balanced, national-consensus framework and a proposed plan of action for civic and history education. This required acquiring a deep, evidence-based understanding of issues from many perspectives and creatively designing, developing, and evaluating new approaches. This project brought together hundreds of ideologically, philosophically, and demographically diverse historians, political scientists, and educators. Together, the collaborators learned to approach disagreement and controversy as an opportunity for learning rather than as a problem to be overcome and, in doing so, they achieved much greater consensus than they had anticipated. Learn more here.

Identifying Early Warning Signs Related to Heart Failure

A significant number of heart failure patients develop serious symptoms that require further hospitalization, and there is currently no straightforward way for patients and their care providers to accurately identify early warning signs, so that patients can receive appropriate treatment before symptoms progress. To address this problem, Dr. Katherine Kim, from the University of California Davis, partnered with other academic researchers, clinicians, and patients to develop a tool for clinicians and patients to identify early warning signs. This work required the integration of new techniques in artificial intelligence with the practical needs of a specific segment of the health care system, with a goal of achieving considerably better health outcomes. The results of this early-stage HIBAR project demonstrated that predictive algorithms can be used to uncover warning signs for individual patients that would otherwise be very difficult to discern. The results also indicated that some subjective measures, such as the patient’s sense of wellness, can be surprisingly accurate indicators of the need for further treatment. The knowledge generated by this insight may prove valuable in a wide range of health care situations. Learn more here. 

Improving the National Flood Insurance Program

HIBAR research collaborations, such as those underway within the Wharton Risk Management and Decision Processes Center at the University of Pennsylvania, have been integral in helping society to better manage low-probability, high-consequence events related to technological and natural hazards. This research has studied how our innate human biases make it difficult for us to assess the risk of unlikely events, and that these biases lead people to decide against buying flood insurance, despite living in flood-prone areas. It has been essential to develop new understanding of the behavioural economics that influences these decisions and to use this to inform and drive effective policies. The important new knowledge generated by this work has informed policies recently developed by the U.S. Federal Emergency Management Agency (FEMA) and is just one example of the importance of behavioral economics in informing and driving effective policies. Learn more here.