2011 – Integ 220: Scientific Nature of Knowledge Dr. Katie Plaisance
Trandisciplinarity is the key for solving the problems of tomorrow. It is through the use of transdisciplinary teams that problems can be solved in a new, holistic way, but this is much easier said than done. In this paper I will discuss how transdisciplinary teams may be formed, with an epistemological foundation. Examined will be the advantages of transdisciplinary teams as well as the main issues facing their proliferation, the importance of composition of team members regarding their expertise, and the scaling of transdisciplinary teams both temporally and in terms of member size. This will be done through reference to the epistemological framework of each subject and an evaluation of that framework. I will then apply how each subject might apply to a fictional real world consultancy firm.
Transdisciplinary teams hold the advantage of being able to approach problems in a holistic way. By working together across traditional disciplinary boundaries solutions for problems of a systemic nature can be created. I believe that the most realistic type of transdisciplinary team that could be created is one with a specific mandate and problem to solve.
The key advantage of trandisciplinarity is its use of epistemological pluralism. This refers to how multiple disciplinary perspectives can be used when approaching a problem (Miller). A variety of perspective helps to unify problem formulation across traditional boundaries to create a scope that views the problem in an entirely new way (Miller). By doing so, the limits and biases of our traditional knowledge are circumvented (Miller). There are certainly some issues with this model as it currently exists, especially in the academic realm. Dr. Gorretty Dias mentioned in a lecture to our Integ 220 class that it is a time allocation limit that stymies their participation in transdisciplinary projects. In the academic realm, experts who already have a commitment to achieving a high level of work in their own domain cannot necessarily commit to more unconventional approaches (Dias).
I strongly believe that the potential of transdisciplinary teams is significant, and that work in the field of learning to build effective ones should be undertaken. The main issues with applying the theoretical framework of transdisciplinary teams are that of time constraints and reconciling the ideal of perfect transdisciplinarity with the constraints of reality. To address this, we need to focus for the time being on making transdisciplinarity a problem oriented method that results in the creation of entirely new disciplines that are inherently transdisciplinary: “transdisciplinary disciplines”. They should be project focused in the short-term, and then grow to accept other problems once established.
The first reason for this is because it adds an explicit focus to transdisciplinary research. By making transdisciplinary fields the priority, experts can commit to something that, though new, has the same sense of structure and focus of traditional disciplines. Simply branding transdisciplinarity as cutting edge fields adds conventionality to something previously eluding definition. This could improve the confidence of disciplinary experts to contribute their time to new fields. Building “transdiciplinary disciplines” will limit the ideal open-endedness of transdisciplinarity, and could also improve the foothold of transdisciplinarity in peoples mindset. With the confidence of experts in transdisciplinarity, more unconventional approaches can be taken in future.
People who are experts in “transdisciplinary disciplines” should be essentially the managers of knowledge for those disciplines. The experts here should have a base knowledge of all the contributing disciplines into their field. But most importantly they should have very high skill in not only integrating that knowledge, but in managing and integrating the skills and knowledge of the experts from other disciplines who contribute to the new field. This managerial role will allow transdisciplinary teams to function effectively with purpose.
For example, a private transdisciplinary consultancy firm might be tasked with the complex problem of how to improve the efficiency passenger and freight movement to, from, and through the Calgary Metropolitan Region, in order to make it a global logistics hub. The initial project would involve gathering a group of engineers, transport theorists, urban planners, architects, business people including ones with expertise in supply chain, environmental scientists, and political theorists. The hiring draw would be to solve a tightly focused problem. The leaders of this team would take a synthesis, integrative, and management role. It would be someone with a high level of general knowledge that covers these areas, as well as has a strong base of an iterative problem solving process. The result of this work could lead to a tight and holistic solution in the form of report with specific outcomes and details that make it implementable. The team created is now expert in the transdisciplinary field of global logistics hub planning, and can use this expertise to initiate new projects or products or solve related problems in a consultant role.
Composition of members is a key aspect of the effectiveness of transdisciplinary teams. This stems mainly from the nature of expertise itself, and how expert knowledge can be used. I believe that in order to ensure a team runs smoothly and effectively the levels of expertise of the members of the group must be considered in the group’s formation.
There are five main levels of expertise ranging from Beer-mat Knowledge of a subject to Contributory Expertise in a field (INTEG220). I will define each of them and pinpoint which ones are most useful transdisciplinary teams. Beer-mat Knowledge is the least useful for transdisciplinary teams, it is cursory and simple knowledge with which not much can be done (INTEG220). Popular Understanding is of a higher level, but is still less nuanced than primary source knowledge (INTEG220). It is useful for public decision-making if it lies in fields where the knowledge is not disputed (INTEG220). Primary Source Knowledge is acquired by reading literature from specialists (INTEG220). To be appreciated fully, it should be acquired along side experts in the field- that is the general idea of university style education, to gather this knowledge under the guidance of professors (INTEG220). Finally, the highest levels of expertise come from those with specialist knowledge. These include interactional and contributory experts. Contributory experts actively add new knowledge to their fields by performing research and experiments, whereas interactional experts have the same grasp of the language as contributory experts but do not practice in these fields (INTEG220).
In transdisciplinary teams, we require a variety of expertise. I believe that for the most part, we require people who have interactive or primary source expertise. But to be most useful and effective, these people should have at least a popular understanding of other areas relevant to the disciplines that are being transversed. In this way, transdisciplinary connections can be made between members of the team, and disparate ideas can be combined for the purpose of innovation.
The main focus should be to acquire interactive experts and people with primary source expertise, and to consult contributory experts through interactive experts when necessary. These people will all be from requisite disciplines relevant to the problem. There is also an added bonus if these experts have at least popular knowledge in other fields that are relevant to the problem, or if they have at least popular knowledge in the fields of their transdisciplinary team members. This will improve communications and knowledge connections.
The highest level of knowledge is not a pre-requisite for transdisciplinary teams. In most problem-oriented transdisciplinary teams, it is not necessary or to acquire only specialist contributory experts from other fields. The hope in this kind of scenario would be to bring experts and specialists from segregated fields together to essentially create contributory experts in new fields. So though contributory experts could join transdisciplinary teams, they might be overqualified or unable to do so due to time constraint. It would be challenging to only acquire contributory experts because of their prior commitments to their current fields, which by their nature are more dynamic than interactional expertise. Also, because of their commitment to their current fields, their perspectives may be limited which would hamper the effectiveness of transdisciplinarity.
Interactional experts of transdisciplinary teams will be members who help connect the teams design and decision making to the highest levels of current knowledge. They would do this through their knowledge of the language of contributory experts, and would apply their theoretical specialist knowledge to projects. They would also help to define and connect the new language of the “transdisciplinary discipline” to its sub discipline. But as with contributory experts, it could be difficult to acquire interactional experts due to their relative scarcity.
Members with primary source knowledge would be the backbone of the transdisciplinary teams in the private and public sectors. These are university-educated people with a high level of skill and knowledge who are more plentiful than interactional experts.
A transdisciplinary team of ten might have two or three interactional or contributory experts, if possible, with the rest being members with primary source knowledge. The only exception to that would be the inclusion of a few integrative thinkers. These will be the members who help to tie a teams thinking together because of their broader knowledge and grasp of multiple areas. This could be either an interactional expert or a primary source knowledge member with that level of expertise in two or more areas, or a primary source knowledge generalist. One of these members would likely be the knowledge manager and leader of the group.
In a transdisciplinary consultancy looking at the problem of building a transportation hub strategy for the Calgary metropolitan region, the firm might consider looking at a team of around 10 with a knowledge and member composition like the following. There would be a senior integrative generalist with either interactional or primary source expertise in the areas of at least 2 of 5 areas: business/economics, policy, engineering, transport planning or architecture. There would be at least one junior integrative generalist on the team with the same pre-requisite experience as the senior one, albeit to a lesser extent and in different fields. There would then be a couple interactional experts, probably in the areas of engineering and transport planning who would provide insight into these core essential areas and possible communications with contributory experts in the field. Finally, the rest of the team would be composed of primary source knowledge based members representing the stated areas, the minority of them being senior members. From this base, other knowledge or skills can be outsourced to domain specific experts or workers, with the core transdisciplinary design and problem solving occurring within the main group.
If a problem-oriented, well-composed and effective transdisciplinary team is created and demonstrated to be effective, there needs to be ways to allow this team to continue to work. There is opportunity to scale the focus, member size, and length of mandate to be larger. But this must be approached carefully and with respect to the nature of teams.
The epistemological framework I will approach in order to evaluate this is that of the model. For my purpose, I will look at the model as analogous to transdisciplinary teams. Models are physical or theoretical representation of the world used to support theory (INTEG220). The greater the scale of a model then the greater range of potential use of the model (Chalmers 44). And without large scale, it is difficult to make generalizations based on the content of the model due to it not being supported by enough instances of fact (42). But models that are grand and account for all cases would require infinite amounts of tests and observations (45), and are limited by economic concerns (James Danckert). Models that contain too much information are somewhat like maps with two much information (INTEG220). For example, if one has specific purpose to make a bus route map, it would not be useful to create a 3D exact representation of the world with bus routes AND power lines AND zoning areas. Editorializing is important to have useful models, like it is for maps.
Like models, transdisciplinary teams have great potential use if they are large and involve people from many different disciplines (like facts). Without their size and a variety of experts, their solutions can be limited in holistic scope because of a lack of requisite knowledge (like generalizations). But creating large transdisciplinary teams that can tackle any problem would be nigh impossible from a management, economic, and talent acquisition perspective (too much information). As well, without editorializing and designing a specific purpose for transdisciplinary teams, they could be rather aimless.
I have discussed how to make small scale, focused transdisciplinary teams which exist for a limited time to solve a certain problem. The opportunity for growth temporally of these teams is simple. The team needs to apply this teams accumulated expertise to new projects that are similar to the first, thus creating the beginnings of a “transdisciplinary discipline”. But the challenge lies with regard to expanding the scope and number of members of the team. It is necessary to grow in order to solve problems in a more holistic way both in terms of scale of focus and team knowledge, and this will represent the progress of the “transdisciplinary discipline”. I believe that this needs to be done slowly and with careful planning. Teams must be expanded with experts that will be assimilated into the “transdisciplinary discipline”, pulling open the scope more with disciplinary knowledge while maintaining transdisciplinary integrity. A focus on outcomes and careful design of internal growth will be essential to maintaining purpose for the team.
For example, at the transdisciplinary consultancy once the initial global logistics hub project is complete, new opportunities arise for working for other cities and also building software to manage and analyze the flow of people and goods through metropolitan areas. For this, the team is both expanding from the initial scope of the “transdisciplinary discipline”, as well as in need of new talent and more time. It will be important to add more experts to bolster the knowledge and effectiveness of the team, without drowning out the unique knowledge created previously by the team. And simply expanding the scope at this point to triple the size of the team with experts from areas like botany to auto engineering will add too much knowledge and size for the team to be successful. Growth must be measured and purposeful, with an eye for addressing needs and problems efficiently.
The creation of transdisciplinary teams with robust epistemological frameworks will be essential for solving the systems-based problems of tomorrow. Setting up a strong benchmark for transdisciplinary teams, designing the composition of members and expanding the mandate of these teams in a purposeful and careful way will ensure their success. For the meantime, the perfect epistemological ideal of transdisciplinarity will not be reached, but its tenets may be synthesized in order to create effective solutions for problems. This is especially true in the private and public sectors. “Transdisciplinary disciplines” must be created and embraced.
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Chalmers, A.F. What is this thing called Science. Indianapolis: Hackett Publishing Company, Inc. 1976. Digital.
Danckert, James. Class Interview. 04 Oct. 2011.
Integ 220 Guest Lecturer. “Scientific Concepts & Models.” University of Waterloo, Waterloo. 22 Sep. 2011. Lecture.
Plaisance, Katie. “Levels of Expertise.” University of Waterloo, Waterloo. 24 Nov. 2011. Lecture.
Dais, Goretty. “Interview.” University of Waterloo, Waterloo. 08 Nov. 2011. Lecture.
Miller, T. R., T. D. Baird, C. M. Littlefield, G. Kofinas, F. Chapin, III, and C. L. Redman. 2008. Epistemological pluralism: reorganizing interdisciplinary research. Ecology and Society 13(2): 46. [online] URL: http://www.ecologyandsociety.org.proxy.lib.uwaterloo.ca/vol13/iss2/art46/