By Katie Moon, Chris Cvitanovic, Deborah A. Blackman, Ivan R. Scales and Nicola K. Browne
How can we reduce the barriers to successful integrative research processes? In particular, how can we understand the different epistemologies that underpin knowledge?
Epistemology is the branch of philosophy that asks: how do we know what we know? It is concerned with how we can ensure that knowledge is both adequate and legitimate, by considering:
- what constitutes a knowledge claim, including the assumptions that are made
- how knowledge is produced or acquired
- how the extent of its applicability can be determined.
Accordingly, understanding and accounting for different epistemologies is important for developing solutions to contemporary challenges where a range of disciplines and practices converge, each with their own methods and assumptions regarding the adequacy and legitimacy of knowledge.
To help researchers understand different epistemologies and their influence on integrative research practices we have come up with five questions they can ask themselves (and one another).
Question 1: What Do We Seek to Create Knowledge About?
- What is it that the researcher seeks to create or discover knowledge about?
- Why and how do they determine what to study?
- What are the objects of study – are they tangible or intangible?
For example, the natural sciences focus on the biophysical dimensions of systems, where the object of study is usually tangible. The focus on physical objects stems from the aims of understanding and describing natural phenomena, which is typically achieved through observation and experimentation focused on establishing a high level of validity and reliability in the knowledge.
In contrast, the social sciences focus on human dimensions of the system. These dimensions can be physical and observable (eg., a person’s behaviour), and non-physical and non-observable (eg., a person’s beliefs).
Question 2: How Do We Create Knowledge in Integrated Research Sciences?
- What beliefs underpin the research?
- How have the researchers sought to justify their beliefs as true?
It can be helpful to think, quite broadly, about knowledge as a ‘justified, true belief,’ that is, the way in which an individual or group ‘knows’ something is true. Yet, people can construct the meaning of the same object or phenomenon in different ways on the basis of their cultural, historical and social perspectives, and interactions with human communities (eg., their social network). It therefore becomes necessary to consider how different beliefs are justified (eg., via reason, emotion, perception and language) and accepted as knowledge.
Question 3: Who Accepts Knowledge as ‘True’ and How?
- What methods of data collection have been used? How we they justified?
- What sampling strategies were adopted and why?
- How did the researchers identify and reflect bias in designing and implementing the research?
- Who determines whether the methods, results and truth claims are valid?
- What criteria were used to assess the quality of the truth claims?
Generally speaking, for knowledge to be ‘accepted’ (ie., justified, true beliefs), an epistemic community is required. An epistemic community is a group of people who are considered experts in a knowledge domain, for example, within a discipline (eg., physics, ecology, anthropology), industry (eg., aquaculture, diving tourism) or cultural group (eg., religious, indigenous). The important role of epistemology here is asking us to be involved in an ongoing examination of ‘what I know’, ‘how I know it’ and ‘how it corresponds (or not) with the knowledge of others’. This last question is particularly important in integrated research, where different knowledge sets often exist.
By recognising that (groups of) people create or discover and assess knowledge in a variety of ways, we can begin to open our minds to multiple ways of knowing, all of which can be validated in different ways within and across defined epistemic communities.
Question 4: How Do We Determine the Epistemology Underpinning the Research Processes?
- What assumptions about reality underpin the research?
- What methodologies and methods were used?
- How was the data analysed and interpreted?
We have developed a simple heuristic device to assist in understanding the epistemology of integrated research and what it means in terms of research practice and outcomes (see figure below). The intention here is not to be comprehensive, but to provide a simple map of how to get a sense of where researchers’ assumptions might lie in relation to how they have sought to create knowledge.
Question 5: What Are the Implications of Epistemology for Applied Integrated Research?
- In what ways could the data be applied (eg., can it be generalised to the population or is it context- or site- specific)?
- How were different stakeholders engaged in the research process?
- How were marginalised groups considered and engaged?
Two particularly important benefits arise from understanding the role of epistemology in the application of integrated research:
- an understanding of epistemology can increase our awareness of the partiality of our knowledge, which can only ever be provisional, qualified and even uncertain due to the nature of research questions and designs that only focus on a part of the system
- an understanding of epistemology provides opportunities to consider power relations in research and practice. Academic knowledge is only one type of knowledge, yet it is often privileged above others, such as Indigenous, experiential and cultural knowledge.
What is the dominant epistemology of your research practice, and how might it differ from that of others? What methods have you used to account for differences in assumptions of research team members? How have you sought and and worked with different stakeholders to share knowledge?
To find out more:
Moon, K., Cvitanovic, C., Blackman, D. A., Scales, I. R. and Browne, N. K. (2021). Five questions to understand epistemology and its influence on integrative marine research. Frontiers in Marine Science, 8, 173. (Online – open access): https://www.frontiersin.org/articles/10.3389/fmars.2021.574158/full
Katie Moon PhD is a senior lecturer in the Public Service Research Group, School of Business at the University of New South Wales, Canberra, Australia where she focuses on areas of policy implementation and stewardship. She is also affiliated with the Centre for Ecosystem Science. Her research focuses on the interactions between people and nature, examining how people make decisions and why. She applies different and novel combinations of methods to increase understanding of socio-ecological systems, seeking different types of knowledge, experiences, perceptions and interpretations.
Chris Cvitanovic PhD is a transdisciplinary marine scientist in the Centre for the Public Awareness of Science at The Australian National University in Canberra. His research is focused on improving the relationship between science, policy and practice to enable evidence-informed decision-making for sustainable ocean futures.
Deborah A. Blackman PhD is head of School and professor in Public Sector Management Strategy, School of Business at the University of New South Wales, Canberra, Australia. Her research interests include public sector policy implementation, systems level change, organisational learning, soft knowledge management, organisational effectiveness, psychological contract and governance. She researches knowledge transfer in a range of applied, real world contexts. The common theme of her work is developing effective knowledge acquisition and transfer in order to improve organisational effectiveness.
Ivan R. Scales PhD is a fellow and lecturer in Human Geography at St Catharine’s College, University of Cambridge in the United Kingdom. His interests lie in applying interdisciplinary approaches to understanding and tackling issues such as tropical deforestation, biodiversity conservation, and food security.
Nicola K. Browne PhD is a senior research fellow in the School of Molecular and Life Sciences at Curtin University, Perth, Australia. Her main areas of research include coral reef ecology and conservation, and coastal carbonate landforms. She is currently working with experts from a range of disciplines to develop an ecological model to improve understanding of climate change impacts on the long-term stability of coral reefs and associated carbonate landforms (eg., islands).
14 thoughts on “Five questions to understand epistemology and its influence on integrative research processes”
I appreciate the thoughtfulness and thoroughness of the article. It has application to foresight, offering some ways to integrate rigor into futures work and analysis. Consider as a complement to point three the question: “Who Does Not Accept Knowledge as ‘True’ and How?” Asking that would seem to take back one of your critical invitations to identify and look at assumptions. Again, well done. Jim
Dear colleagues, I tried to reflect on the topic: what philosophical context is able to integrate the epistemologies underlying knowledge? The result was a short essay about a person and the nature of his knowledge. I hope you will like it.
A person, like any object, is a natural fragment of the planetary nature. All objects, including a person, participate in a single process of transformation of planetary matter. For this reason, every person initially has the necessity and mission. The mission of man is that no one but him will be able to transform a certain amount of planetary matter. The necessity of a person is that only a person is able to transform this volume of planetary matter according to certain rules, with certain results, by a certain deadline. Otherwise, these results will not be demanded by other objects on the planet, and the continuous process of transformation of planetary matter may be interrupted.
The phenomena of “reflection” and “display” help a person to realize his necessity and mission. Reflection is the process of passing through ourselves without distortion of planetary matter and energy (every second a lot of radiation and chemical elements and substances pass through our body, to which we consciously do not react). It is important to note that the reflection process initiates the display process. Display is a psychophysiological process of forming a worldview, what the world, the planet is, a detailed disclosure of the meaning of what is hidden behind the terms necessity and mission of a person.
This information allows us to conclude that knowledge is the result of a person’s psychophysiological interaction with the world, the result of a subjective representation of the world. Human consciousness is a mechanism for comparing the subjective representation of the world with its objective unmanifested analogue belonging to the world itself. If consciousness discovers the correspondence of the subjective to the objective, then a person feels knowledge about the world as true. Thus, the production of true knowledge is a consequence of the necessity and a mission of man, as well as an inevitable product of the mechanism of reflection and display of the world, working under the control of the mechanism of consciousness.
What is the use of this seemingly complex philosophical context for successful integration research processes? This context allows us to form unambiguous answers to five questions that researchers can ask themselves (and each other). If the knowledge about the world (planet and man), the ways of obtaining, processing and all further manipulations with them in their entirety describe, support and preserve the unity of the inner and outer world of person, society and planetary nature, ensure sustainable development, then this knowledge is objectively true (such as it should be). This epistemological context makes every integration research process successful, regardless of the complexity of the problem. Moreover, the success of the research process based on true knowledge is a condition for a single natural process of transformation of planetary matter. Further joint work on the answers to the five questions, in such a philosophical context, can turn them into a prototype of the moral and ethical code of integration research processes.
P.S. The Windows 10 program on my computer uses English. But this program in my brain uses the Russian language. So I turned to my computer for help in translating this message into English. Did my computer successfully cope with the integration process of two languages? Was the translation of the text into English true? Or do you need explanations on the text? Thank you in advance.
Thanks for an insightful article and table! The questions could work wonderful in teaching, I expect. The table raises some issues, though, as I’m wondering whether nowadays the distinction between e.g. the aim for natural scientific research and for social sci. research is less strict than previously. The former is increasingly gathered with the aim of intervening or manipulating the world, developing technology, etc. Another observation is that theoretical and pluralism -which both are increasingly common even in monodisciplinary research but certainly in fields like cognitive neuroscience, biophysics etc. – seem difficult to locate in your table. For example, in transcultural cognitive neuroscience a mix of lab experiment, surveys and interviews might be used with anthropological participatory observation feeding the theoretical framework. I’m curious how you handle such issues with this table?
Thanks for these thoughtful comments Machiel, you’re spot on. It might be helpful to know that the article was written as part of a Special Issue for Frontiers in Marine Science with a focus on Early Career Researchers. Given the audience, we stripped back the content to make some critical points of distinction for those new to the topic. Our audience was certainly not people familiar with the topic, but rather those who might be brand new.
Thank you for the article and I shared via Facebook.
Thank you for such a clear and useful insight. When opaque power intercedes with knowledge work, it blocks any question of philosophy in my experience – despite all the good reasons for it to be otherwise that you give here. I wonder if we can produce something that enables insights about knowledge such as this heuristic to go a step further than being aware of power in knowledge – to make blocking power a better informed agency than something that is often based in primitive self interest and fear?
Really important questions Susan and lots of great literature on the topic. I enjyoyed this one recently:
As an epistemologist who has spent many years studying the logic of complex issues, I offer the following principle, which may be of some use here:
The weight of complex evidence is relative to the observer.
Thus reasonable people of good will can look at the same complex evidence and come to opposite conclusions. Of course someone is wrong when this happens, but deep disagreement is not irrational. The weight of complex evidence often depends on what we already believe and this varies greatly from person to person.
Awareness and accommodation of contrasting perspectives (e.g. based on specialisation, biases and beliefs) and in turn the tendency for contradictory conclusions are a very insightful point, especially since so much of the interdisciplinary competencies seem intent on uniting and reconciling any differences, terminating the ‘problem’ so to speak. In terms of the proposed “simple heuristic device”, my key concern is an assumption that ‘data’ is a primary form of knowledge and a notion of epistemology which seems to focus on the process of ‘acceptance’ of it as ‘true’. In effect, asserting that a consistency between “What beliefs underpin the research?” and “What methods of data collection have been used? How we[re] they justified?” can be reconciled on an empiricist basis, or in fact that data constitutes the knowledge at hand.
My instincts point to a temperament captured (betrayed) in first column “How are beliefs about reality justified?” or more precisely, the emphases and references to ”data’, its validity and related methodologies, i.e. the objectivist epistemology, throughout this report, in contrast with a somewhat marginal treatment of the subjectivist – “Reason (Rationalism)” and in particular Interpretivism, the middle ground of Phenomenological and Constructionist perspective on ‘knowledge’. Given the biases of contemporary paradigm, favouring ‘numbers’ over qualitative descriptions of phenomena, a hypothesis of shared epistemology may leave a bad taste of ‘humanities’ being rather expediently acknowledged, but methodologically underserved. Sadly, this approach. wouldn’t move us any further from the legacy of contemporary failures driven by Rationalistic dogmatism.
In other words, lip service to marginalised voices and qualities of the human condition which don’t lend themselves to data collection mechanisms and measurement in general, are no better than initiatives for whitewashing and greenwashing of corporate interests or meritocratic rationalisations for ingrained asymmetries of power behind the current status quo. All too often, what is measured turns out to be a function of availability of means or access to ‘devices’, ahead of any pressing concerns or expressed needs. Little more than an insidious incarnation of the Goodhart’s law; as a measure becomes the target in itself, the very process intended to improve decision-making is corrupted as a result (borrowing from Donald Campbell’s interpretation of it in terms of impact on social norms). In a nutshell, a ‘simplified’ heuristic workaround for ‘conflict’, with potential to foster a synthetic and flawed epistemology.
Indeed, it is well established that data is often “theory laden” as the saying goes. In many complex issues a lot of the debate is over the validity of proffered data. These are decidedly epistemic issues. The question is not how the world is, it is what do we know about that?
Piotr, these are such important points you raise, and ones that we are working on in different capacities and different ways elsewhere, including in the areas of decolonisation.
It is difficult to approach the topic, in few words, and present all of the challenges. One of our concerns, however, is the lack of awareness of the philosophical foundations of many practising scientists. As noted above, the piece was written for ECRs, and so our primary objective was to introduce certain topics in ways that allowed the audience to follow along. We included references to important work for them to follow up on.
I guess it was one part of an ongoing effort to bring more awareness to the assumptions we make, but was always going to have limitations.
It’s important these conversations continue. Thanks for providing space for that here.
Some reading I’ve been enjoying:
In this respect (broadening the philosophical perspective of analysis in the course of scientific enquiry) the diagram will no doubt prove very practical, even if the prevalent disposition deterministic objectivism isn’t likely to be contested by the proposed framework. The essence of my reflections is that the contemporary favouritism of econometrics of empirical evidence and the tendency for ‘mathiness’ in reasoning, which I consider to be a perilously blinkered perspective, isn’t explicitly addressed by the proposed heuristic and indeed, in many ways reinforced by the emphases on establishing validity of data representations or models. While I appreciate the awareness of alternate cultural dimensions, e.g. indigenous value systems, in my observations these are at best instructive in terms of paradigm critique, but less practical in anchoring development of counterpoint methodologies.
Given that the ‘wrongs’ or failures of the paradigm exist in a more general realm, e.g. inequalities of opportunity and material status or discrimination, sense-making grounded in the specific and relative indicators aren’t likely to lead a causal analysis to core instruments of dysfunction. This problem is particularly opaque where the symptoms, e.g. unemployment, poverty or incarceration, are stigmatised in context of cultural myths regarding mechanisms behind polar opposites, like meritocracy or presumption of universal fairness of outcomes through ‘democratic’ governance. Indeed, focusing on the specific tends to detract from more general failures and the findings are likely to be diluted by the sub-context of associated dimensions, e.g. racism, in turn, the resulting propositions become distorted by relative targets, when the ‘real’ cause and failure is in fact more general.
It is my strong belief that dogmas, e.g. efficiencies of free market economy, are best understood and remediated by targeting the most general level of abstraction afflicted by a given phenomenon, for example, poverty as a function of globalised monopolistic practices, be it loss of employment opportunities, commodification of labour or conversely, loss of land in an agrarian society, etc.. Somewhat counterintuitively, a ‘data’ centric orientation tends to elude system analysis in identification of an appropriate scope, a boundary representing the problem at its most general, and instead points to a multitude of symptomatic artefacts, e.g. based on ‘visibility’ or data reflecting legacy variables being measured. In turn, such findings lead to inconsequential interventions, little more than band-aids, which often by design aim to erode the dignity of human condition. The net effect of such initiatives detracts from the fact that nothing is done to address the root causes and instead, the resulting activities only serve in rationalising the notion of integrity behind a flawed status quo.
Yes, David, absolutely.
I’ve been reading and very much enjoying Karen Barad’s 2007 book, Meeting the Universe Halfway. She discusses in great detail the ‘cuts’ that we make in how we come to ‘know’. She says, “It matters which cuts are enacted: different cuts enact different materialised becomings”. In other words, it is our preexisting ideas about the world that shape the evidence we produce.
She defines “objectivity” as being a matter of accoutability for what comes to be.
She provides an interesting discussion of “thingification” here:
Sadly that article is paywalled, but I can say a couple of things based on the page that is displayed. The first is that I know nothing about most of what she is talking about. I just do analysis of complex issues. But I do have to defend the linguistic turn, which happened over 100 years ago with Russell, Wittgenstein et al. The idea was that the big philosophical problems were conceptual confusions so the methodology is concept analysis, hence analytic philosophy, which is my training.
I study conceptual confusions in big public policy issues and there is no lack thereof. I like to paraphrase Will Rogers who said “It is easy to be a comedian when you have the whole government working for you.”
In fact I say that confusion is the price of progress, because major social changes always require crafting new concepts and reconfiguring old ones. Language is how we think about and talk about the world. There is nothing particularly anti-material about this, so I do not know what Barad is talking about (which is linguistic in its way).
What I discovered is that complex issues are indeed complex, far more than people realize, and this matters. I call my discovery the “issue tree” although that term is now used for things far less formal. I describe it briefly here:
Grasping a normal complex issue involves intuitively understanding a structure with several thousand individual ideas in it. That we can do this is pretty amazing. It explains why there is so much confusion when we address big issues. It also shows how complex the weight of evidence is as a human practice.