This piece explains my rationale for choosing a novel autoethnographic method to extend one of my previous research projects, which used constructivist grounded theory method, to explore how early career researchers experience information for learning in complex transdisciplinary contexts. Over four years, as a doctoral candidate, I was immersed in the fascinating worlds and eclectic networks of fourteen researchers from across the natural sciences, social sciences and creative arts, in the first five years of their academic appointments. Each of these academics based at two Australian universities had continued to nurture connections established from their past lives working in industry, media, advocacy groups and government policy, while collaborating with a wide range of academics and practitioners from within and outside of their disciplines.
My study developed a theoretical model of early career researchers experiencing information as a transdisciplinary knowledge ecosystem. With constructivist grounded theory, my focus was on developing an understanding of a social phenomenon (and new conceptual models) based on commonalities and differences across various individual and personal, subjective meanings and experiences. The knowledge ecosystem model published in Journal of Documentation UK, featured as the journal’s most read paper in 2018-19 (Miller, 2015) and is cited in many projects academic and non-academic including the United Nations. The model was developed from qualitative data analysis, open and focused coding and constant comparison technique. Data analysis was focused on uncovering their emotions, thoughts, identities, practices and experiences in the relationships between the researchers and their support networks, and also their intersubjective relationships with myself as the researcher.
Since completing my doctorate five years ago, I have also developed both professionally and personally through postdoctoral research, teaching and life experience. Over the past twenty years I have had several careers across many different disciplines, sectors and geographical and sociocultural locations – many of them interrelated – as a scholarly researcher, author, filmmaker, musician, editor, research grants development manager and parliamentary social policy researcher. With this experience, I decided to apply the autoethnographic approach – with its emphasis on the researcher’s perspective on experiencing a phenomenon – to extending my knowledge ecosystem model by analyzing my own reflective journal entries, social media posts, publications, multimedia and observational notes produced throughout my doctorate until the present day. Autoethnography was considered the ideal approach to explore a new research question: How does a social change agent experience information while producing for impact across transdisciplinary spaces?
Autoethnography is “a reflexive means by which the researcher–practitioner consciously embeds himself or herself in theory and practice, and by way of intimate autobiographic account, explicates a phenomenon under investigation or intervention” (McIllveen, 2008). The participant-researcher is uniquely placed to analyse the data, enriching the findings with reflexive, embodied and affective insights that she has gained from over a decade of experience (Hokkanen, 2017; Ellis et al, 2010) as a change agent moving between different worlds such as academia, industries such as social media technology companies, journalism, and public policy development. An interest in peoples’ lived experiences may be described as a focus that “orients us holistically towards peoples informed existences, considering people and what informs them, within their wider environments in a manner which considers people and their world as inseparable”. (Bruce et al, 2014, p. 5). Data analysis was guided by six questions:
- How are cultures of a transdisciplinary nature observed?
- What is informing transdisciplinary social change?
- How are information and/or knowledge experienced in each context?
- What was the social problem jointly identified and worked on?
- What does the impact journey look like?
- How is this a complex adaptive system?
Each data source was collected and clustered into NVivo, under each of the cultural settings, for data analysis. The researcher, guided by the research questions, individually coded items line by line, while noting the relationships between emotions, information and the cultural settings (Ellis et al, 2010). Each case was written using memo development based on initial coding. From constantly comparing data and memos written from each case, patterns emerged from data analysis (Ellis et al, 2010), which identified transdisciplinary resonance as a way of experiencing information that empowers change agents working in liminal spaces between different groups. The following is an autoethnographic excerpt, which forms the basis of an upcoming scholarly book exploring methods of producing shared understanding for social innovation.
One the first innovative people I interviewed for my doctoral research was an early career ecologist in environmental science. Several years later her work has made a pioneering contribution to the conservation of a particular endangered species of wildlife. Even though she and I inhabited very different worlds, the interview flowed very harmoniously. She connected with me immediately and understood that I was a social scientist, studying humans and their behaviours, cultures and experiences and she acknowledged we were doing the same work but using different approaches, because humans are part of the same ecosystem as animals. As I interviewed more natural scientists such as ecology and biology researchers, and compared with them my observations of physicists and chemists, I observed that the ecologists are able to synthesise different disciplines working and learning together rather than working more narrowly. This was a memorable moment, for myself and for the people involved in my research, as it gave us common ground to co-create something that would otherwise never have been born. In a moment of intersubjectivity, or shared understanding, we were learning and knowing together even through our differences. The moment also signaled to me that the project itself was starting to produce resonance across disciplinary boundaries. In terms of creating impact, not only did the study have to follow standards of quality, trustworthiness and credibility in its data collection, analysis and theorizing, but the two evaluative notions of shared understanding and resonance were equally important, yet often skipped for lack of time in many qualitative studies. So I kept that in mind throughout my PhD and beyond. In using an autoethnographic approach, shared understanding is defined as the relationships between transdisciplinary information and resonance.
Similarly, as I interviewed social scientists and humanities researchers working in fields of communications, filmmaking, marketing and psychology, they enthusiastically offered the terms social ecology and complex adaptive systems. In those moments, the social-ecological metaphor became a major common framework and mindset for many disciplinary and epistemological perspectives to hang onto, making the often chaotic experience of working collaboratively in transdisciplinary projects and environments a little smoother. It also suggested that the projects they were working on together had long-term global and local significance in sustainable development – for the environment, both natural and artificial or digital, the economy and the people and societies. The repeated use of the term ecology indicated to me that the disciplinary boundaries informally known as silos were starting to crumble and that researchers themselves were changing in their approaches, especially natural scientists whose work is traditionally more firmly entrenched in present day and historically undisputed empirical observable fact as opposed to a work’s future implications in a changing and evolving environment.
A transdisciplinary project is one of collaborative problem solving where a social or digital problem is formulated and knowledge gaps identified by a team or network of academics and non-academics from different disciplines and sectors on equal status. Each team member is changed throughout the project, regardless of orientation. While there is much published about how to facilitate transdisciplinary processes, teamwork and the transcultural nature of such projects (Stokols, 2018), very few studies explore the sociocultural, experiential and interpersonal aspects of transdisciplinary groundwork (Miller, 2016). Much of the transdisciplinary culture remains ‘invisible work’ and deeper insights and understanding can only be gained through a synthesis of the individual, collaborative and cross-boundary contextual factors and experiences. As yet, there have been no studies which attempt to analyze data collected from people involved in transdisciplinary projects, tracking their impacts, perceptions and experiences over a number of years.
In the urgency of finding solutions to many social and environmental problems, a re-calibration was occurring. And that is why the social-ecological mindset rose to the forefront of my knowledge ecosystem theory, and that what truly informed innovators and change makers while learning and growing was the ecosystem itself, particularly waves of creative intelligence and ingenuity. We need to look at new ways to facilitate these resources. My study was not meant to be an activist push for change or advocacy. The changes and shifts were observed as unfolding slowly; like a natural scientist, I was observing, collecting and analysing empirical data gathered from humans in their natural environment – a university ecosystem.
The autoethnographic approach using reflexive data analysis extends findings from a grounded theory study, by revealing some of the researcher’s personal story behind the making of the knowledge ecosystem model, while relating and integrating further insights into important issues currently being discussed in higher education and the wider society.
Bruce, C., Davis, K., Hughes, H., Partridge, H. & Stoodley, I. (2014). Information experience: contemporary perspectives. In C. Bruce, K. Davis, H. Hughes, H. Partridge & I. Stoodley (Eds.), Information experience: approaches to theory and practice (pp. 3-15). Bingley, UK: Emerald. (Library and Information Science, 9.)
Ellis, C., Adams, T. E. & Bochner, A. P. (2010). Autoethnography: An Overview. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 12(1), Art. 10, Available at: http://nbn-resolving.de/urn:nbn:de:0114-fqs1101108
Hokkanen, S. (2017). Analyzing personal embodied experiences: Autoethnography, feelings, and fieldwork. Translation & Interpreting, 9(1), 24-35.
McIlveen, P. (2008). Autoethnography as a method for reflexive research and practice in vocational psychology. Australian Journal of Career Development, 17(2), 13-20.
Miller, C. Z. (2016). Towards transdisciplinarity: Liminality and transitions inherent in pluridisciplinary collaborative work. Journal of Business Anthropology, 2, 35-57.
Miller, F. Q. (2015). Experiencing information use for early career academics’ learning: A knowledge ecosystem model, Journal of Documentation, 71(6), 1228-1249.
Stokols, D. (2018). Social ecology in the digital age. Cambridge, Massachusetts: Academic Press.