Disciplines vary greatly in how they conduct their scholarship and research.
In some of the humanities, the scholar has great freedom in creating new approaches to new topics. Creativity and novelty are highly valued. The evaluation of the work is heavily weighted toward the production of new ways of interpreting long-lasting questions and phenomena.
Other fields ground their research on a large set of prior studies. They justify the questions they pursue by noting the past findings are flawed, incomplete, or inadequate in some other way. That logic justifies asking the new research question. Solving puzzles remaining in the paradigm is the day-to-day goal.
While the style of scholarship may be quite variable across fields, in many ways the fields, as they evolve, share a feature – as the field evolves, the complexity of work increases. For fields that do not possess strong unifying paradigms, the challenge of creating a novel approach to a long-studied area is increasing complex. Imitative work is less highly valued. The new is applauded when it survives scrutiny on its impact to understanding of the issues. Discovering what is new is increasingly difficult.
Fields that depend on well-developed theory to identify research questions yet unanswered suffer from their own increasing complexity. Many of these fields have had decades or centuries of increasing depth of understanding of the key phenomena in the field. The basic questions have been answered; the second order issues have been largely settled. The remaining questions involve combinations of issues in a system of interacting elements. The complexity of cutting edge research grows dramatically.
These disciplinary differences manifest themselves in new ways when fields work together to address real problems. When fields that have very different research styles come together, they face challenges. Some of these arise from normal needs to share concepts and nomenclature. These are difficult enough for collaborations.
Added to these difficulties, however, can be starkly different ways of approaching an agreed-upon shared problem. Interdisciplinary research is exposing these. They include the contrast between qualitative methods and quantitative methods. They involve the role of emotion in motivating action, versus purely rational logic. They involve lab work and experimentation versus field work and observational studies. They involve tendencies to value deduction versus induction or vice versa. They involve the struggle of one adept at working alone to work in teams where one might not be directing the whole project.
In short, as each field evolves, its knowledge becomes more elaborated and typically more complex. As then the fields combine to solve a problem that needs multiple fields, the complexity of combining both knowledge and research methods increases.
As world problems demand multi-field input for their solutions, learning how to navigate these differences is critical to our success.
There is much we can learn from the design professions regarding methods, processes, and strategies to navigate complex multi-disciplinary problem domains. Check out the book Design Unbound: Designing for Emergence in a White Water World, by Ann M. Pendleton-Jullian and John Seely Brown for more on this topic:
https://mitpress.mit.edu/books/design-unbound-designing-emergence-white-water-world-volume-1
In the context of artistic endeavor, there is yet another strand of complexity : a feedback loop actualizing a former mode of vision.
At present I am directing a contemporary play in France based on a Manuel of good manners dating from 1889. Obviously, the general audience of mature-age spectators is reacting to the parody of yesteryear. Yet, the much younger folk in the audience applaud a sense of social ritual which their parents rejected after the counter-culture of the 1960’s and 70’s. Consequently, a scholar investigating audience reaction to this particular work in the year 2019 will need to recognize a complex differentiality of criteria.
Interesting comments on the complexities of doing research. It’s good to remember what Einstein once said “ Remember to keep things as simple as possible… if not more simple !” Hard to do with complex problems but that theory seemed to work out pretty well for him!