There is an intriguing and welcome movement in EM/CA circles recommending that more be done by scholars to engage with social issues. Prime among these issues is racism, and I’m delighted that three early-career academics, Eleonora Sciubba, Natasha Shrikant and Francesca Williamson have agreed to report on their and their colleagues’ efforts to apply EM/CA perspectives on the issue.

The authors of this post [1] are members of a working group entitled, EMCA4RJ—or EMCA for Racial Justice—that was started in June 2020 [2] The purpose of this group is to foreground race and racism as central issues in the EMCA community. 

EMCA approaches are well-suited for addressing racial justice aims through deconstructing how race and racism are constituted in everyday interaction. Some scholars, for example, have analyzed ways that broader phenomena such as racism, whiteness, or anti-racism occur through specific interactional moves like categorization (Shrikant, 2020; Whitehead, 2020) or extreme case re-formulations (Robles, 2015). More generally, however, race, racism, and racial justice have been understudied in the EMCA community. This post provides examples of ways that can change.

Research Practices: Four suggestions

Since Sacks (1984), “unmotivated looking” has been the watchword of EM/CA. However, as philosophers (e.g., Chalmers, 2013) have argued, the practice of observation in scientific and social inquiry is tied to and shaped by researchers’ experiences, cultures, expectations, and academic training. In other words, who we (analysts) are and our experiences shape what we notice; what we can observe in social interaction. 

We suggest a motivated looking approach that leverages tools within (categorization) and outside (race/racism) of EMCA. This approach involves taking racism, a social fact, as a starting point for inquiry. We can begin with searching for instances when social actors do race, examine how racial categories are implicated in social actions, and consider the interactional and social consequences of these categorization practices. 

1. To do this, we must first build racially and ethnically diverse EMCA research teams that focus on race and racism-in-interaction studies. Analysts who experience racism in their everyday lives may meet the unique adequacy requirement (Garfinkel, 2002) and can thereby improve our ability to notice and describe racialization and racism.
2. Second, we should build collections focused on race and racism, as has been done with gender (e.g., Kitzinger & Frith, 1999; Speer & Stokoe, 2011), to examine instances when racialization is achieved in interaction. As Rawls and Duck (2020) suggested: “[r]acism does not usually take an obvious form that we can see and prevent; rather it masquerades as the most ordinary of daily actions: as unnoticed and ever-present as the air we breathe.” (p. 1). Thus, racialization and racism are likely designedly ambiguous or elusive. They need further interrogation.
3. Third, we argue for more use of Membership Categorization Analysis (MCA). Though some scholars have done so (e.g., Robles, 2015; Shrikant, 2020; Whitehead, 2020), more work is needed. For example, scholars can explore how category-bound activities or predicates are tied to racial categories, search for instances when race categories are positioned categories, or how particular membership categorization devices (MCDs) are produced in ways that may be marginalizing yet remain open to the ways that categorizations are produced and negotiated in interaction.
4. Finally, we should pursue new topics of inquiry through respecification projects as has been pursued for studies of social life in ethnomethodology (Garfinkel, 1991) and psychological constructs in discursive psychology (Potter, 2012), for example. In what settings have scholars documented racial inequities? What interactional materials might be available for EMCA studies in these settings?

Pedagogical practices

Conversation Analysis has a history of drawing teaching resources from audio and video data that are mostly anglophone, recorded either in the US or the UK, and feature White people, simply because they are already available and widely known within the discipline.

The problem with using “traditional EMCA data” for teaching is that it perpetuates a White, Anglocentric worldview that could make non-White students feel disconnected or excluded from the field. Moreover, it is difficult to draw connections between EMCA tools (e.g., adjacency pairs, categorization) and racism in these traditional data, as neither is readily visible as relevant, and the data are not taught or interrogated as examples of ‘Whiteness’. 

We propose teaching EMCA through using data:

• a) from linguistically and ethnically diverse people and
• b) where issues of race, racism, and intersecting inequalities appear as relevant.

Teachers can draw from data collected by scholars who work with diverse participants such as Rawls and Duck (2020) (African American), Shrikant (2018) (Asian American), or Whitehead (2020) (makes Whiteness visible in South African contexts). Teachers can also draw data from current events where race and racism appear relevant (we provide an example below). Equally, we encourage CA teachers to draw on and value the expertise of their diverse students. In line with practices of inclusive pedagogy, teachers should treat the differences among learners as a strength for analyzing data. Asking students to reflect on ways they arrived at a particular interpretation of data aligns with ethnomethodological approaches to research (Garfinkel, 1967). To this end, EMCA4RJ is developing practical resources—a syllabus, a data set including audio/video clips and transcriptions, and suggested lesson plans—and will share these resources to help put inclusive pedagogy into practice for EMCA teaching.

Community Building Practices: The EMCA Data Session

Data sessions bring EMCA together as a community of practice, or a community defined and maintained through participation in shared practices with shared goals (Eckert & McConnell-Ginet, 1992). Although data sessions are collaborative, they are not constituted by egalitarian relationships. Participants do boundary work about the kinds of contributions to a data session that are considered reasonable, appropriate, or within the bounds of EMCA analysis (e.g., Antaki et al, 2008). In some ways, clear boundaries and guidelines are useful, yet in other ways they are limiting. 

Traditional conversation analysis data sessions do not address questions about race and racism. Many of us in EMCA4RJ have had the experience of attempting to make claims about racism in a data session only to be told that racism has ‘not been made relevant’ by the participants. Ignoring race, denying its relevance, or simply the inability to see race and racism in interaction are indicative of a White worldview (Bonilla-Silva, 2006). In EMCA4RJ, we challenge this worldview through conducting data sessions that leverage the tools from CA to deconstruct the ways that race and racism are made relevant in everyday interaction. During our data sessions, we help scholars support their noticings of race and racism through using EMCA tools instead of dismissing these noticings as outside of EMCA frameworks. As part of EMCA4RJ, we are developing a document of guidelines for inclusive data sessions to share widely in hopes of encouraging other data session groups to operate in a more inclusive fashion. Below is an example of an EMCA4RJ data session from February 5, 2021 where we analyzed racist discourse in an interview between Gayle King and Miya Ponsetto [3].

The clip can be accessed here.

Overall, we argue that the suggested research, teaching, and community-building practices will help transform the EMCA community to include more diverse scholars and more research on topics like race, racism, and Whiteness. It is in these ways that we can highlight ways that EMCA approaches can serve racial justice aims.  

References

Antaki, C., Biazzi, M., Nissen, A. & Wagner, J. (2008). Accounting for moral judgments in academic talk: The case of a conversation analysis data session. Text & Talk, 28(1), 1–30. doi: 10.1515/TEXT.2008.001

Bonilla-Silva, E. (2006). Racism without racists: Color-blind racism and the persistence of racial inequality in the United States. Rowman & Littlefield Publishers.

Chalmers, A. F. (2013). What is this thing called science (4th ed.). Hackett Publishing Company

Crenshaw, K., Gotanda, N., Peller, G., & Thomas, K. (Eds.) (1995). Critical race theory: The key writings that formed the movement. New York: The New Press.

Eckert, P., & McConnell-Ginet, S. (1992). Think practically and look locally: Language and gender as community-based practice. Annual review of anthropology, 21(1), 461-488.

Garfinkel, H. (1967). Studies in ethnomethodology. Englewood Cliffs, NJ: Prentice-Hall.

Garfinkel, H. (1991). Respecifcation: Evidence for locally produced, naturally accountable phenomena of order*, logic, reason, meaning, method, etc. in and as of the essential haecceity of immortal ordinary society, (I) – an announcement of studies. In G. Button (Ed.) Ethnomethodology and the human sciences (pp. 10-19). Cambridge University Press. 

Garfinkel, H. (2002). Ethnomethodology’s program: Working out Durkheim’s aphorism. Rowman & Littlefield. 

Kitzinger, C., & Frith, H. (1999). Just say no? The use of conversation analysis in developing a feminist perspective on sexual refusal. Discourse & Society, 10(3), 293-316. Retrieved from http://www.jstor.org/stable/42888261

Potter, J. (2012). Discourse analysis and discursive psychology. In Cooper, H. (Ed.), APA handbook of research methods in psychology: Vol. 2. Quantitative, qualitative, neuropsychological, and biological (pp. 111-130).Washington, DC: American Psychological Association Press

Rawls, A. W., & Duck, W. (2020). Tacit racism. The University of Chicago Press.

Robles, J. S. (2015). Extreme case (re) formulation as a practice for making hearably racist talk repairable. Journal of Language and Social Psychology, 34(4), 390-409.

Sacks, H. (1984). Notes on methodology. In J. M. Atkinson & J. Heritage (Eds.) Structures of social action: Studies in conversation analysis (pp. 21-27). Cambridge University Press.

Shrikant, N. (2018). “There’s no such thing as Asian”: A membership categorization analysis of cross-cultural adaptation in an Asian American business community. Journal of International and Intercultural Communication, 11(4), 286-303. doi: 10.1080/17513057.2018.1478986

Shrikant, N. (2020). Membership Categorization Analysis of Racism in an Online Discussion among Neighbors. Language in Society. doi: 10.1017/S0047404520000846

Speer, S. A., & Stokoe, E. (2011). Conversation and gender. Cambridge University Press.

Whitehead, K. A. (2020). The problem of context in the analysis of social action: The case of implicit whiteness in post-apartheid South Africa. Social Psychology Quarterly, 83(3), 294-313.

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[1] This piece was a collaborative product, where all authors made equally significant contributions. We also would like to thank Jessica Robles for her thoughtful feedback on an earlier draft. Last, we drew many ideas from our participation in EMCA4RJ and from the following thread https://twitter.com/Nat_Shri/status/1298640326488395777?s=20.   

[2]  http://emca4rj.conversationanalysis.org/; contact Natasha Shrikant (natasha.shrikant@colorado.edu) if interested in joining or learning more.

[3] See Video Clips, Transcript, and Excerpt of Data Session here: https://drive.google.com/drive/folders/145rI1ZI3lQF43DOxKTNJ-5cDK1f631OS?usp=sharing