Historical Arc of Universities

Statistical Modeling, Causal Inference, and Social Science 2014-05-14

This post is by David K. Park

Even though I’m an engineer with a PhD in political science, I tend to gravitate toward history to anchor my contextual lens. (If fact, if I were pressed to put a methodological stake in the ground, I would say I’m a historical comparative institutional ecologist.) In that regard, it may be helpful to situate this discussion within the broader historical arc of intellectual pursuits at universities. As we know with the birth of universities, we had scholars who embodied so many disciplines such as mathematics, philosophy, religion law, etc into one individual. Then in the 50′s and 60′s we started going into hyper-specialization mode, and it was necessary because we needed to better understand our specific domains. In the 80s and 90s, certain disciplines started to recognize the importance of other disciplines on their work but the tendency was to bring those skills into a single individual. So we produced, by way of e.g., law professors who could do game theory, political scientists who could run sophisticated statistical models, sociologists who could run network analysis, etc.

However, we are now at a juncture where there maybe a self awareness among a generation of scholars that not only do they need to read across disciplinary lines but truly interact with colleagues outside their disciplines to make new insights and discoveries. The recognition seems to be that the grand challenges we face are larger than one individual, one discipline, but not necessarily one institution. Therefore, embedded in this discussion is this narrative of what should or can a university do to enable truly “transdisciplinary” research to help tackle and answer some of the larger intellectual questions as well as pressing grand challenges facing society .

Can we design and implement an institutional framework and mechanism which allows for this type of research? Interestingly, by way of analogy, Acemoglu and Robinson, in Why Nations Fail, do a wonderful job laying out the case for this type of framework for the success of countries, which could readily apply to this discussion as well.

As is often the case, it’s understanding the processes by which we get to the breakthroughs that is more challenging that understanding the breakthrough itself.

The post Historical Arc of Universities appeared first on Statistical Modeling, Causal Inference, and Social Science.