Dissecting the components of research innovation -- what is scientific impact?

As stated in previous posts, the goal of BRIL is to generate scientific innovation that starts by the sharing of research resources across groups. The underlying idea is that if two groups have complimentary resources, two researchers can collaborate. For example, if researcher A has a clinical database and researcher B knows a data analysis method that can be applied to her database, and assuming it has not been implemented before, then a research collaboration can be established to generate a unique scientific finding. The finding will be unique since that particular data analysis method has not been previously used to evaluate that particular database. However, a combination of two resources such as these does not guarantee scientific impact. In other words, I might have a new database from my clinic containing information about osteoarthritis and pain, and although a data analysis method might find a positive association between the two variables, this finding will not necessarily shake the scientific community. So, what exactly constitutes scientific impact and how can we dissect its components?

In the best sociology of science tradition, scientific impact is primarily a social phenomenon since it relies on reactions from members of the scientific society to a given scientific statement. Although the definition cannot be precise, the central characteristic of any impact measure is its ability to spread across other areas, the so called hub effect. In this post we argue that a change in conceptualization is inherent to the hub effect, this conceptual change affecting the way researchers perceive and act upon their objects of study.

But how does a change in conceptualization actually occurs? There is no quick and dirty answer. Mechanisms are multiple and their boundaries are frequently not clear. However, two main cognitive mechanisms are fairly frequent. First, change in research frequently occurs through the use of a change in the metaphors underlying the scientific concepts. These changes have been demonstrated in multiple scientific areas, and even in what is considered the hardest and most objective of all sciences: mathematics (Lakoff, 2001). For example, when the central metaphor "good medicine is experience" was changed to "good medicine is randomized controlled trial", Evidence-Based Medicine was created. The second mechanism explored in the literature is the change in image schemata, sometimes represented in three-dimensional models (Waskan, 2006). For example, when the central image associated with the consolidation of fractures changed from "bone healing is complete immobilization" to "healing is pure axial movement", the orthopedic method of Ilizarov was created. It should be noticed that cognitive mechanisms do not have to be restricted to the individual level, but they also occur at the social level, but we will leave those to future posts.

At the researcher level, the change in conceptualization can lead into a change in scientific methods, the latter enabling scientific changes in multiple fields. For example, when Kahneman and Tversky proposed a conceptual change from expected utility theory to prospect theory (Kahnman, 1979), not only a whole new field was created but Economics was also perceived by many researchers in a dramatically different manner.

Finally, although methodological changes are a great influence among peers, an even greater hub effect will occur in society at large if researchers can achieve a change in reflexivity among members of the general population. Reflexivity affects the perception human beings have about their own life, including changes in the way they perceive economic factors, suffering, purpose of human life, or even entertainment. Reflexivity thus plays with emotion and its ability to influence how we perceive ourselves and the world around us. Examples of authors who attempted to create texts that were understandable to lay people abound, including the multiple books by Lorenz attempting to reach the masses with the concept of ethology (e.g., Lorenz, 2002), a concept that gave him the Nobel Prize of 1970.

1. Daniel Kahneman, Amos Tversky, Prospect Theory: An Analysis of Decision under Risk, Econometrica, XLVII (1979), 263-291.
2. George Lakoff, Rafael E. Nunez, and Rafael Nuñez, Where Mathematics Comes From: How the Embodied Mind Brings Mathematics into Being (Basic Books, 2001).
3. Jonathan A. Waskan, Models and Cognition (The MIT Press, 2006).
4. Konrad Lorenz, King Solomon's Ring: New Light on Animal Ways (Routledge, 2002).