Questioning the status quo in methods

Questioning the status quo

Building on the general recognition that current methods are not enough to approximate knowledge towards the solution needed for the wicked problems we face, the questions arises how we can meaningfully question the status quo in methods, and do this in a way that moves us forward. Too many enthusiastic questions of the status quo in the realms of scientific methods have been proposed without a clear understanding what is actually the problem, or bettie, which knowledge we are lacking. The current state of many lines of thinking urged us to move out of the dimensions of a normal science in the sense of Kuhn. However, calling out a revolution does not mean that all problems are automatically solved. On the contrary are we concerning many aspects still in a state that we do explicitly not know how to solve the wicked problems we face. Let us look at three examples. Climate change is a complex phenomena where at first the emergence that human induced climate change is happening was slowly emerging out of diverse scientific data sources and research approaches. While the majority of society today has accepted that human induced climate change is real, and that it is our responsibility to react and counteract, there is not general agreement on a best way. Instead calls for a globally orchestrated policy-response are on a totally different scale compared to local adaptation. Most importantly, how can we convince citizens in countries that since decades lead in terms of a negative contribution to climate change not only to change their behaviour, but actually to contribute to reversing its catastrophic effects? This is the current frontier in research, and there are many promising suggestions and strategies that are currently being investigated. However, since we may only know in retrospect how this problem was after all at least approachable if not completely solvable, we need to further diversify our research approaches, and also consider the urgency of the problem. A 20 year longitudinal study will not be enough, since we need suggestions as soon as possible. Hence the urgency and the wickedness of the problem showcases the need for novel methods to contribute to the approximation of solutions.

Actor participation

Research about normative challenges as well as research about joined problem framing between actors and researchers has been on the rise, hence more and more studies engage in the new contract between science and society. However are the role and power relations of different actors within a system deeply contextual, and so far the knowledge of such studies did not saturate yet into a more general understanding on how such study setting can be approached. While blueprints already exists and there is a growing understanding of such concepts as social learning, actor participation is still something that did not find its way into a broad diversity of textbooks, and available approaches are more different then unified. Most of normals sciences actually dispute whether the recognition of actor knowledge is actually contributing to scientific progress, and instead keep judging the difference between applied science and their science. What is more, actor participation is approached from all sorts of disciplinary background, which is adding diversity in terms of methods, but adds to a more general confusion because the different approaches rooted in diverse disciplines are often pitched as being either superior or inferior to each other. While it is clear that different methods have different value in a specific context, comparison between different methods to allow for actor participation is widely lacking to date, yet only fair comparisons of diverse approaches may allow for a claim of which methodological approach has a higher validity in a respective context.

Sustainable consumption

The question how we shift our consumption towards being more sustainable is another thriving debate within sustainability science and beyond. While there is research focussing on global trade and its inequalities, there is equally research focussing on the individual behaviour and the motivations of consumers. Understanding and even more challenging driving behaviour change in terms of sustainable consumption is to date a diverse field, again being methodologically rooted in psychology, social science and many other domains. On the other hand are global supply chains and trade arrangements part of totally different fields in sciences and these two scales are hardly matched. Instead there is a clear gap between research focussing on supply and research focussing on demand. From a methodological standpoint, integrating global and the individual and supply and demand already poses a very complex challenge, showcasing how a link between these diverse line of thinking will preoccupy research for the foreseeable future. Atomising challenges into smaller chunks that represent parts of the picture follows a long tradition in science, yet integrating these diverse approaches will be vital in order to take the whole depth and width of the challenges into account.

Three pathways of methodological innovation

We can thus concluded that urgency, wickedness, normativity, context, scale integration and many other challenges are currently recognised in the community of sustainability science researchers, and deserve more focus in order to generate solutions. This no-exhaustive list of problems already showcases that this is easier proposed than done. Within sustainability sincere and beyond, there is an almost obsession to question the status quo, and to proclaim what methods should do. While it sounds so appealing to "dance with the system" -a sentence borrowed from Donella Meadows, I always asked myself what that actually means. How do we take the normative burden of all the proposals for transformation and take a first step as individual researchers? Here, I propose three perspectives on how innovation in terms of scientific methods could be more concretely approached.

1) Invention of new methods Inventing new methods sounds surely exiting, there is a whole world of knowledge that awaits us, and new methods might be potentially able to unlock this new knowledge. Despite the spirit that motivates many researchers to this end, I would like to highlight that in the past the invention of new methods often came out of a clear recognition of a lack of method in order to solve a specific problems. The proposal of interviews as s scientific method, or grounded theory, were rooted in the recognition of a lack of a suitable methodological approach for a specific problem. Take open interviews as an example, which allowed for an inductive recognition of the perceptions of individuals. This type of knowledge did not exists before as such, and the proposal of these new methods allowed for a gap to be closed. In order to close this gap, I believe that this gap needed to be realised, and this was rooted in the recognition of clear knowledge and experience with methods that were already there. Take Fischers Analysis of Variance as another example, which basically took the implementation of systematic experimentation onto a completely new level. Fischer saw existing research at the agricultural research center he was working at as a statistician, and he saw a clear lack of a systematic method that allowed to generate knowledge in terms of pattern recognition based on the testing of a predominated hypothesis. Fischer knew the state of the art, and he recognised a clear gap in the canon of existing methods. What is more, he had experience in the already existing methods, which were preconditions for his formulation of the analysis of variance. The invention of new methods is thus quite often a gradual process that is rooted in a continuous development, yet history of science often reduces it to one point in time. To this end, I propose to recognise more of a continuum that such new methods are being proposed in, and such innovative settings build typically on experience regarding existing methods, and through this a recognition of a gap within the already existing methods, or better, the knowledge these methods can produce.

2) Relocation of existing methods Methodological innovation often build on existing methods, if these are use din a different setting or context. For instance were interview in the world value survey applied at a globals scale, allowing for a global comparison of peoples values based on tens of thousands of interviews. The method of structured interviews existed long beef that, and one could argue that such larger surveys even predated the 1960 proclamation of Strauss and Glaser regarding interviews. However, allowing for a global comparison was clearly unique. Another example is how the Analysis of Variance was once widely reserved for deductive experiments, yet with the rise of data science and the availability of more data though the internet and other sources led to the application of the Analysis of Variance in purely inductive settings.Another example would be the diverse applications of text analysis, which were once postulated for very specific setting, but are today applied in all sort of branches of science. The relocation of a method basically thus utilises an existing method in a different setting of context than it was original intended to be used. Again, this does not only imply that experience with the existing method is a necessary precondition, but the real innovation potential comes out of the recognition of a gap, and that the relocation of the existing method may close this gap by creating new knowledge.

3) Recombination of existing methods Another possibility of creating innovation in methodologies is possible though the recombination of existing methods. To this end, with the rise of data becoming available through surveys, statistics allowed fro the utilisation of diverse methods to analyse data coming out of surveys, and later also from structured interviews. Such innovations are rather gradual, and are less recognised by the community. Another example would be the utilisation of statistical methods for coded items from a grounded theory approach. While originally this approach was focussing on qualitative research, there are now examples how coded information was compiled in a table, and this table was thus statistically analysed. Such innovation is often a violation of the original rules or norms that were proclaimed with a method, and thus have also attracted controversy and criticism in the past. Recombining diverse methods build nevertheless on a deep understanding and even experience of a respective method, showcasing yet again how researchers created new knowledge by building on already established methodological approaches.

The here proposed possibilities of methodological innovation bare clearly building on design thinking, as the development of methodological applications can be understood as a design problem. Creating a methodological design is necessarily a commitment that may be criticised as static or even downright dogmatic by some researchers, yet the here proposed criteria for innovation are more proposed as a starting point, and should not be seen as a new dogma. Instead I propose a counterpoint to a hype for methodological innovation that may be appealing to many, yet makes is in my experience very hard for researchers to start with their specific research. There is a tendency in sustainability science to reject all methodological dogma in order to be unbiased and more creative. While this sounds appealing in theory, I would counteragrue in the spirit of critical realism that some observable realities can be accessed by existing methods, and some new activated knowledge that we try to unravel may demand methodological innovation. All this implies that -following Roy Baskhar- we should clearly reject any claim of any knowledge being perfect, independent if it is based on old or new methodologies, knowledge can and most certainly will change. The urge for novel methodologies is however right now so strong, that experience in existing methodologies is rejected altogether. I consider this to be a dangerous new dogma, and kindly ask future researchers to consider experience in empirical methodologies as an important basis for innovation. As I have clearly shown above, there4 can be more than just theoretical considerations why methodological innovation can build in experience in existing methodologies. Such experience should always include a recognition of its limitations, and in the long run there might be a greater recognition of new design criteria that shall drive methodological innovation. While thus the interconnectedness of different forms of knowledge, reflexivity of researchers and other actors, the recognition of complexity in systems, and the necessity of power relations in knowledge production are prominent examples of current challenges that methodologies as of yet have not solved, we are probably still far away from the creation of a solidified canon of knowledge to solve these riddles. One could argue that we will never solve these methodological problems altogether, but that the joined action and interaction while working on these problems will be the actual solution, and a real solution as with past methods of normal sincere shall never be reached. This is unclear to date, yet we need to become aware that when we question the status quo of knowledge production and methodologies that we may not be looking for goals, but more for a path. There are several examples in sustainability science that follow this path, such as transdisciplinarity and system thinking. However, according to critical realism is may be good to solidify innovative and novel methodologies to a point that enables as to take meaningful actions based on the knowledge we create.