During a review of a series of research project proposals, I quite frequently came across the phrase: ‘…and the project proposes a truly transdisciplinary approach’. The word ‘truly’ caught my attention and prompted me to raise a discussion about what a transdisciplinary, multidisciplinary or interdisciplinary approach means in research.
In the common view, multidisciplinarity draws on knowledge from different disciplines but stays within their boundaries. Interdisciplinarity analyses, synthesises and harmonises links between disciplines into a coordinated and coherent whole. Transdisciplinarity transcends their traditional boundaries with the expectation of an emergent approach… in other words, the resulting approach should be more than the sum of its parts.
From the experience I have working on various projects aimed at being “transdisciplinary”, I know that the need to understand and respect the different disciplinary semantics is crucial.
A semantic dispute
To speak of a particular experience, I was participating in an interesting debate about the use of ‘models’ in scientific research within a ‘transdisciplinary’ research project in which SIRIS Lab is a research partner (EPNet – www.roman-ep.net). Historians, computer scientists and physicists were all involved in this debate. Each of them presented their own disciplinary vision about ‘why to use models’.
For the historians, the key aspect for building the ‘useful’ model was the selection of the right parameters, case-based and aimed at supporting the specificity of the historical narrative. The computer scientists stressed the importance of the requirements and the purpose of the model (emphasising that all the models are wrong by definition), and the fact that models need robustness, consistency and coherence to be computable. For the physicists, the most important aspect was ‘keeping everything as simple as possible’ and looking for universality (in opposition to particularity, which was the historians’ aim). Our discussion went on for three hours!
The results? The computer scientists and physicists found a common ground promoting the quantitative and controlled approach. The physicists, in particular, had stressed the importance that models should be tested by making predictions and checking them against real world data, otherwise they remain pure theory-building exercises (something the computer scientists seemed to like). The historians were accused of introducing too many parameters into the model. On the other side, the historians remained sceptical of how such an approach could improve their understanding or their work: there was little use in trying to convince a historian who had spent half his life reading ancient epigraphy and collecting data on a specific period in the past that everything should be reduced to a controlled number of parameters and a specific and clear starting hypothesis.
Anyway, the interesting aspect was that for those three hours, all the scholars involved were clearly thinking at the use of ‘modelling’ in their disciplinary context and literature, trying to convince the others that their approach was the right one.
A question of indicators and expectations
Now the question I have is: how could academic organisations improve this semantic understanding and facilitate a process whereby scholars are less interested in defending their own approach in favour of going beyond traditional boundaries with the expectation of a different approach that could be more than the sum of its parts?
This is not a very new topic and several scholars and policymakers working in science organisations (from epistemology to sciencemetrics) are debating if and how universities and research policies should change to allow the crossing of disciplinary boundaries and new emergent lines of research. However, this is still an open debate and the issue of how research projects will achieve a ‘truly’ transdisciplinary approach has not yet been solved.
All scholars with experience in research project coordination and management know that successful projects are strictly related to project team expectations and rewards, as well as internal communication between the project members.
Personal interests and research curiosity should be the major driving force for a research project. However, from my personal experience, budget allocations and career development probably represent the most important issues in terms of project team expectations and rewards.
Why? Apart from the lack of regular resources for basic research (which forces scholars to apply for project-based funding), the two most important indicators for a scholar’s career development are:
a) productivity: number and impact of publications and prestige of the journal
b) fundraising: ability to acquire and manage funded projects.
For this reason, scholars tend to prefer to publish within their community (because this is better evaluated in terms of career) and try to get more project/resources for their own group, with less incentive to engage in ‘hybridisation’.
This explains why:
a) identifying proper transdisciplinary journals for publications is always a problem (in transdisciplinary projects, it is common to hear things like: ‘this journal makes sense for your community, but it is not evaluable in mine’)
b) hiring research profiles in projects are not normally shared between different groups (co-hiring). On the contrary, each group prefers to hire its own profile, with the aim of having more scholars within their own group to improve the number of publications in the group-specific community and increase the amount of money obtained for their own CV (by now you should have noticed that academic CVs commonly include of the amount of euros obtained via competitive projects in the course of their career).
According to this argument, in the last year the number of ‘transdisciplinary’ journals has grown, and explicit requests for a multi and trans disciplinary approach is clearly a buzzword in the H2020 framework.
Fine. We will have more journals accepting transdisciplinary research results and more funding for supporting this research. Is this enough to create ‘truly’ transdisciplinary research crossing disciplinary boundaries and allowing new lines of research to emerge?
Personally, I wouldn’t be so optimistic. I think that the most challenging aspect is still in the transversal formation and training of a new generation of scholars (young researchers!). We need to break the boundaries, and not just create adjacent laboratories or research groups. In my opinion, it is very difficult for well-established scholars in specific scientific communities to move to a completely new area. At best, they can apply their own experience and knowledge to a different field for solving the problem of this different domain, but this it not be more than the sum of its parts.
The role of academic organisations
In 1997 at Locarno, Switzerland, an interesting event was held to discuss ‘what university tomorrow’ with a great focus on transdisciplinarity and the importance of teaching; one of the topics discussed was the ‘transdisciplinary evolution of learning’. After this event and in more recent years, several scholars have reflected on the role of issues associated with transdisciplinary teaching and suggested ways to overcome the challenges posed by different epistemologies, methods and ethical positions (a good synthesis is found in Klein 2013 and Gibbs 2015). However, the situation has not changed very much.
One problem is probably associated with the fact that in most university contexts, teaching and learning performance is still undervalued in comparison to research performance. This means that the career development of scholars is mainly based on research performance and not on teaching and learning performance. As a consequence, the big effort is in publishing more/better and not in teaching more/better.
Therefore, the point is how could academic organisations find proper ways and incentives for transdisciplinary teaching and learning?
Food for thought and for a future post on this topic.
Gibbs, Paul (Ed.), 2015. Transdisciplinary Professional Learning and Practice. Springer.
Klein, Julie Thompson, et al. (Eds.), 2013 . Transdisciplinarity: joint problem solving among science, technology, and society: an effective way for managing complexity. Birkhäuser, Basel.
Article by Bernardo Rondelli. Founding partner of SIRIS Academic, I’m interested in the combination of quantitative and qualitative approaches for building an innovative framework to understand and improve organizations.
*Note: This article gives the views of the author, and not the position of SIRIS Lab, nor of SIRIS Academic.
Information about Featured Image: © EPNet: http://www.roman-ep.net/epnet/. [October 6th, 2015]
 The recent idea of creating a Teaching Excellence Framework in the UK (https://www.gov.uk/government/speeches/teaching-at-the-heart-of-the-system) could be an interesting starting point.