PhD course: (Un)making data
Exploring (auto)ethnographic epistemologies and ‘what counts?’ as relevant knowledge in a
Taught by: Professor Annette Markham and special Guest Professor Laura Ellingson, author of Engaging Crystallization as Qualitative Method, Voicing Survivorship, Embodiment in Qualitative Research
When: March 28-29, 2019
Aarhus University, Denmark
No fee for participants, coffee and lunches provided
Travel or lodging not provided
15 seats available
Register by March 15, 2019
The term ‘data’ refers to many things–the representation of traces of human and nonhuman behaviors and experiences, isolated and observed as discrete objects. While not the only way to describe data, this conceptualization has become prominent in the so-called digital age,
Computation of large datasets can reveal interesting patterns and yield novel insights about human behavior. Perhaps because data is so plentiful, minuscule, and detailed, researchers can sometimes forget that it is not meaningful in itself. This mistake sometimes takes the form of assuming the parts add up to the whole. Or conflating data with knowledge. Whatever the specific form of faulty reasoning, overvaluing the immediate meaning and truth value of data is a problem amplified by the size and number of datasets as well as the commonplace depiction of data as pre-existent and neutral.
For interpretive ethnographers, the term “data” has been problematized for decades because the word symbolically indicates an approach fundamentally opposed to inductive, immersive, and interpretive modes of inquiry. How should qualitative researchers respond to the recent tidal shifts toward datafication? How do we design studies when “data” becomes the predominant concept for giving shape or meaning to cultural materiality? We could simply refuse to use the term since it does not fit well with the qualitative enterprise. Or we could try to replace ‘data’ with other terms. Neither option confronts the actual problem, which is not data itself, or the growth of computation as a way of knowing, but the rise (and reprise) of positivist frameworks and procedures.
This course focuses on the concept of data alongside the concepts of embodiment, affect, and situated knowing to explore contradictions and possibilities for qualitative or mixed method social research. It begins with the premise that concepts are always
We also revive the autoethnographic focus on the researcher’s role in the process of making data. We situate autoethnography as a natural part of research as an embodied, lived practice. Understanding, focusing on, and valuing the role of the researcher in generating accounts of phenomena is a hallmark of contemporary interpretive traditions of ethnographic studies. Thus, the course also focuses on how autoethnographic sensibilities can be a strong counterpoint to data-centered orientations, a key element in building ethically sensitive, situated knowledge.
To apply Please send a single PDF containing one page CV, one-page motivation statement, and one-page discussion of your project, focusing on epistemological, ethical, or methodological concerns. Email to: firstname.lastname@example.org — Rolling admission begins immediately and proceeds until seats are filled. For best consideration, submit prior to March 15, 2019. Applications will be processed immediately on receipt. Once your acceptance is confirmed, we will send you to the webshop to register to reserve your seat. No fee for the workshop. Any reservation deposits will be returned unless the participant is a ‘no show’. Contact Annette Markham with questions or considerations.
Please contact course organizer for final literature list. Meanwhile, participants would be well prepared if they read or even browsed the following books and articles:
Adams, T., Holman Jones, S., & Ellis, C. (2014). Autoethnography. Understanding Qualitative Research. Oxford: Oxford University Press.
Cassell, J. (2002). Perturbing the system: “Soft science,” “hard science,” social science, the anxiety and madness of method. Human Organization, 61(2), 177-185.
Ellingson, L. L. (2017).
Ellingson, L. L. (2009). Engaging crystallization in qualitative research: An introduction. Thousand Oaks, CA: Sage.
Ellingson, L. L. (1998). “Then you know how I feel”: Empathy, identification, and reflexivity in fieldwork. Qualitative Inquiry, 4, 492-514.
Markham, A. N. (2017). Troubling the concept of data in digital qualitative research. In Flick, U. (Ed.). Handbook of Qualitative Data Collection (511-523). London: Sage.
Markham, A. N. (2013). Fieldwork in social media: What would Malinowski do? Qualitative Communication Research, 2(4), 434-446.
Markham, A. N. (2013). Undermining ‘data’: A critical examination of a core term in scientific inquiry. First Monday, 18(10).
Wolf, M. (1991). A
Target group/ Participants
Ph.D. students from any discipline. No prior knowledge is required, but experience in qualitative research will be useful in comprehending and situating the perspectives offered in this course.
VARIABLE: Students may wish to arrange with their supervisors to receive 2-3 ECTS for reading materials in advance and active participation at all sessions. If students wish to receive additional ECTS, they may arrange to submit a 25-30 page paper on the topic of the course, due 10 weeks after the course. They will receive feedback from both professors.
Laura Ellingson, Professor of Communication and Women’s & Gender Studies, Santa Clara University, United States.
Annette Markham, Professor MSO of Information Studies, Center for STS, Aarhus University, Denmark