Author Archives: charlesantaki

Guest Blog: Being Smart About Artificial Intelligence

There’s a lot going on at the interface of AI and speech – both recognition and production – and some of it draws on ideas from ethnomethodology and conversation analysis. But is it any good? Stuart Reeves runs the rule over some of the issues.

Stuart Reeves, Nottingham

Artificial Intelligence is a big deal now. We’re told that AI systems are reaching and even exceeding human performance at things like playing games, hearing and transcribing words (Xiong et al., 2017), translating between languages, or recognising faces and emotions (Lu and Tang, 2014). This means we are entering a world where it’s possible for people to have conversations with AI agents (a Google researcher recently claimed a chatbot as “sentient”), or get computers to understand what’s in a picture and even generate their own art when prompted.

The problem with this picture is that while it is technically accurate, it is also conceptually wrong.


It’s not that the AI systems built aren’t impressive. Voice transcription or language translation services—like many AI systems—are vastly more powerful than they were 10 years ago. This is because of significant hardware improvements around massively parallel processing (specifically, the use of Graphics Processing Units, or GPUs). This has made neural network techniques developed long ago now very tractable, and, coupled with huge data sources made available by the internet to ‘train’ these systems, it’s claimed AI can now readily ‘learn’ how to ‘recognise’ things. 

But there are two major self-deceptions going on here (hence the quotation marks in last paragraph). Firstly, it’s that, as Emily Bender says, people are confusing “the form of an artifact with its meaning”. Sure, an AI system can ingest text and produce news articles ‘automatically’, but that doesn’t make it a journalist or even what we’d think of as a ‘reader’. Secondly, when people talk about AI they tend to exclude all the human effort that is involved in designing, building and even performing its execution; and I say ‘performing’ because the running of AI is often very much the spectacle. (Nothing new here, just look at the hubbub around IBM’s Deep Blue chess playing AI from the 90s.)

This erasure of people subordinates the human to the machine. It offers a neat sidestep away from responsibility for all the potentially prejudicial and biased outputs that the huge data sets ingested by AI systems train them to generate, whether it’s reinforcing stereotypes or systematically excluding people from jobs. These problems are a feature of data sets because they are a feature of society—“stochastic parrots” as Bender et al. (2021) put it.

Ethnomethodology and CA’s long association with AI research

For ethnomethodologists and conversation analysts, however, the last decade’s resurgence of AI is increasingly demanding our attention because of AI’s spread into ever more mundane everyday circumstances, whether that’s voice-operated assistants like Apple’s Siri or self-driving cars. But AI is not new for EMCA.

It’s humbling to think that back in the 80s and 90s, when I was but a child, EM research from Lucy Suchman (Plans and Situated Actions, 1987/2006), and Graham Button and colleagues (Computers, Minds and Conduct, 1995), had already effectively pulled apart AI of the time. Suchman built a critique of the view that humans, as modelled by AI systems, mistook formal ‘plans’ as adequate descriptors of mundane interactions. Button et al. in turn deconstructed the notion that while AI systems might do things which appear human-like, it is a conceptual mistake to confuse them with human practical action. 

The problems they found have not gone away, no matter what anyone says about the ‘new AI’ which is sweeping the world. In fact the problems are bigger. It takes an army of people to train AI systems to ‘recognise’ anything, whether that thing is a sheep or that I’ve said the word ‘hello’. If EMCA researchers are going to pick apart human-AI ‘interactions’ (if we may even call them that), we need to look at the rest of this iceberg. Following Suchman, Mair et al. (2020) argue that EMCA should be “treating all the work that goes into and is done with AI, including descriptions of what a given system might be said to be or be doing, as being as much part of the ‘assemblage’ as the hardware and software”. 

Tread with care

Secondly, if EMCA wants to get stuck in with AI research(ers) en masse, we must also learn the hard lessons from EMCA’s prior engagements with technology-driven research, specifically in the field of human-computer interaction (HCI).

HCI’s ultimate interests are driven towards the (re)design of technologies, just like much of AI’s is. For HCI, this design orientation quickly cast EMCA into a ‘service’ capacity, which it will have for AI research if it is only concerned with delivering “implications for design” (Dourish, 2006). Alternately, EM and CA work could be rethinking its hybridity with design, respecifying, or deflating conceptual confusions in / of AI. 

HCI research also tried to domesticate EMCA, to bring its concerns for the social organisation of technology use into line with conceptual orderings of the field. Suchman’s EM-informed critiques of AI became “situated action theory” (Vera and Simon, 1993). You may also find a catalogue of pretty odd descriptions of EM and CA in various HCI textbooks (naming no names!). If we are researching and publishing on AI I can see EMCA being domesticated again.

One last thing….

The last reminder is about EM in particular. EM’s work in HCI has sometimes relitigated its many arguments with sociology (and other disciplines); replaying these in HCI has derailed the ability of EM (less for CA) to explore what hybridity, conceptual respecification, etc. could mean to its fullest. Critique is important, but it’s also useful to remember whether your audience is as invested in an argument as you are. Baggage should probably be avoided in engagements with AI research.

Stuart has been practicing ethnomethodology and (to a lesser extent) conversation analysis within human-computer interaction (HCI) and collaborative computing (CSCW) research for most of his academic career. Read more on his thoughts about EM/CA and AI in his piece in Medium.

Guest blog: Should we share qualitative data?

Conversation analysts soon accumulate many hours of tapes and transcripts; usually these have been collected on the understanding that they are for the researcher’s own use, with permission only to publish extracts anonymously. But should such data be open to other researchers? Jack B. Joyce, Catrin S. Rhys, Bethan Benwell, Adrian Kerrison, Ruth Parry summarise here the arguments examined in a recent paper.

Jack B Joyce, Catrin S Hughes, Bethan Benwell, Adrian Kerrison and Ruth Parry

Data sharing has been central to the development of Conversation Analysis (CA) and is considered the bread-and-butter of the approach. Here we are talking about data sharing generally but we should point to Elliot Hoey and Chase Raymond’s Rolsi blog where they critically reflect on ‘Classic data’ and some of the pros/cons associated with drawing on a narrow range of data. CA has a fairly unique relationship with data sharing.  It is not an afterthought or a response to the Open Science movement; rather data sharing and ‘secondary’ analysis has been “baked in” to the CA approach from its inception. 

Harvey Sacks (often!) illustrates this point:

“It was not from any large interest in language or from some theoretical formulation of what should be studied that I started with tape-recorded conversations, but simply because I could get my hands on it and I could study it again and again, and also, consequentially, because others could look at what I had studied and make of it what they could, if, for example, they wanted to be able to disagree with me” 

(Sacks, 1984, p. 26, emphasis added). 

Ongoing debates

While the replication crisis or issues of data fabrication have not really touched the shores of qualitative research, the waves of the Open Science movement have brought these rumbling debates into sharp focus, and now many funders and publishers encourage or mandate data sharing. The arguments for reusing qualitative data include the checking of findings, fostering trust in science, enhancing researcher training, and importantly producing new findings which are cost-effective for researchers and avoid unnecessarily burdening participants (Kuula, 2011; DuBois et al., 2018). All-in-all, sharing data maximises the social value of publicly funded research.

Nonetheless, there are concerns about sharing qualitative data when it is highly sensitive. On-high mandates to share data can mean that we fail to protect our participants’ anonymity, or prevent subsequent researchers misinterpreting data which is highly contextual. Moreover, many of the policies and repositories (locally, nationally and internationally) are designed with quantitative research in mind. The extent to which repository specialists or ethics panels are prepared to advise qualitative researchers is varied; Mozersky and colleagues (2020) find that those groups felt responsibilities lay elsewhere.

Such is the difficulty of navigating the choppy waters of data sharing that many qualitative researchers understandably opt not to share their data. Can CA sail in and save the day? Not really; but CA can speak to some of these epistemological, ethical and practice issues and tilt the balance toward data sharing.

Practices of sharing CA data

Conversation analysts have, for the longest time, been sharing their data. You can see three distinct categories of sharing: making a whole corpus available to authorised scholars (as do Jepsen et al (2017) with their ‘one-in-a-million’ corpus of primary care interaction); sharing among a small number of fellow-researchers working on the same project (as often happens in close-knit groups of colleagues); and, most publicly but much more selectively, making selected extracts available in published articles.

For conversation analysts, the chief drivers for sharing data have been to add a level of rigour to the analytic findings and to give others the ability to check the analysis. Seeing the evidence means that “others could look at what I had studied and make of it what they could, if, for example, they wanted to be able to disagree with me” (Sacks, 1984, p. 26, emphasis added).

Primary/Secondary distinction of data

What can CA add to these ongoing debates about sharing qualitative data

In a new publication we argue that the data CA draws on is inherently sensitive even if not formally, legally protected. A person’s openly available actions during a meal may typically be regulated quite differently from their private medical records, but CA researchers quickly learn how prized and intimate mundane interactions can become when we request access to them. Although the ethical concerns associated with handling interactional data are not uniquely experienced by CA researchers, we argue that our experiences in needing to share sensitive data means we have much to contribute to ethical discussions around participant consent regarding data access and practices for maintaining anonymity even in widely-available recordings and transcripts.

An anonymised image of the kind typically used in a journal article

On epistemology, the highly contextual nature of qualitative data and thus the question of whether that data can ever be reinterpreted in secondary analyses has dictated the direction of data sharing discussions. We argue that CA’s endogenous conception of ‘context’ (in brief: that CA does not entertain or assume contextual explanations of phenomena, which was debated at length by Billig, Schegloff and Wetherell in the late 90s) means that data is always constituted for the first time at the point of analysis. Therefore, the distinction between ‘primary’ and ‘secondary’ data which directs the debates on whether to share qualitative data does not exist in CA. In fact, a more significant concern for CA researchers should be the relationship between researcher and data at each analysis (where data are “constituted for the first time” in each project) because of the way that we draw on our own memberships to recognise practices despite the CA appeal to ‘unmotivated looking’. (As an example , see the Twitter thread on this point and related concerns about “the whiteness in the erasure of the researcher” by Edward Reynolds.)

There is a strong practical legacy too: CA’s baked-in approach to sharing data during and after a research project should widen the existing debates around qualitative data sharing and can inform how other approaches might share their data.


CA is unique in its conception of ‘context’ and the real emphasis that is placed on data sharing as part of a rigorous approach. Our rich history (some of which we might now critically reflect on) means that we have experience and knowledge which can usefully inform these debates and shape others’ thinking on how and why data sharing can be at the bow of research design. 

So, should we share qualitative data? Well, you’ll have to read the article to find out… 

Joyce, J.B., Douglass, T., Benwell, B., Rhys, C. S., Parry, R., Simmons, R. & Kerrison, A. (2022). Should we share qualitative data? International Journal of Social Research Methodology


DuBois, J. M., Strait, M., & Walsh, H. (2018). Is It Time to Share Qualitative Research Data? Qualitative Psychology, 5(3), 380-393. doi: 10.1037/qup0000076

Jepson, M., Salisbury, C., Ridd, M. J., Metcalfe, C., Garside, L. & Barnes, R. (2017). The ‘One in a Million’ study: creating a database of UK primary consultations. British Journal of General Practice, 67(658), e345-e351.

Kuula, A. (2011). Methodological and Ethical Dilemmas of Archiving Qualitative Data. IASSIST Quarterly, 34(3-4), 12-17. 

Mozersky, J. Walsh, H. Parsons, M. McIntosh, T. Baldwin, K. and DuBois, J.M. (2020a). Are we ready to share qualitative research data? Knowledge and preparedness among qualitative researchers, IRB Members, and data repository curators. The International Association for Social Science Information Service            and Technology Quarterly, 8(43), 1-26. doi:10.29173/iq952.

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: Cambridge University Press. 

Paul ten Have, 1937 – 2022

Paul ten Have’s son Frans has shared the sad news of Paul’s passing. Paul ten Have died on Tuesday May 10, 2022 in a nursing home in Alkmaar (The Netherlands), two years after he lost his life partner Immelien Kramer.  

Paul ten Have

In 2002, Paul ten Have retired as an Associate Professor in the Department of Sociology and Anthropology, Faculty of Social  and Behavioural Sciences, University of Amsterdam. At that time, he was also a staff member of the Dutch Graduate School in Science & Technology Studies: Science, Technology and Modern Culture. 

From 1992 on, and from 1996 on the world-wide web, Paul’s ETHNO/CA-NEWS has been an important resource for publications and activities in conversation analysis and ethnomethodology ( Since 2014, this work is continued on the EM/CA wiki site ( In a biographical note on the pages of Ethno/CA-News, Paul described his own research interests as follows: 

“My research interests can be indicated by the concepts of ethnomethodology, conversation analysis, medical interaction, technology and research practices. I have a long-standing interest in qualitative research methods, as evident in most of my teaching, a number of publications, and some of my research. My general orientation has been shaped mostly by ethnomethodology, which I most often apply in the form of Conversation Analysis. Since the late 1970’s, I have done research on doctor-patient interaction in the context of the general practice consultation, i.e. in general medicine. (…) For the last 15 years or so, I have also developed an interest in the study of local practices involving various kinds of technology, such as ICT as in word processing or web page design.” 

Paul ten Have was a member of the small group of first generation talk-in-interaction scholars in the Netherlands around the end of the seventies (together with Hanneke Houtkoop-Steenstra, Martha Komter, Dorothea Franck, Marca Schasfoort and Dick Springorum). In 1979, this group had several meetings with Emanuel Schegloff during his stay in the Netherlands, and from 1983 on, there were regular data sessions with Gail Jefferson. In 1991 Paul organized one of the first international conferences on Ethnomethodology and Conversation Analysis in Amsterdam (together with Hanneke Houtkoop-Steenstra and Harrie Mazeland).

Paul was influential as a teacher of ethnomethodology, conversation analysis and qualitative methodology. His handbooks Doing Conversation Analysis (1999, second edition 2007) and Understanding Qualitative Research and Ethnomethodology (2004) offer accessible introductions. They reached a broad readership and are often quoted. Not only was the connection between conversation analysis and ethnomethodology a serious concern for Paul, he was also open to research in related and overlapping paradigms such as interactional linguistics, discursive psychology, membership categorization analysis, or related interaction studies such as Goffman and micro-ethnography.

Some publications

Have, Paul ten (1989) ‘The consultation as a genre’. In: B. Torode, ed. Text and Talk as Social Practice. Dordrecht / Providence, R.I.: Foris Publications: 115- 35

Have, Paul ten (1991) ‘Talk and institution: a reconsideration of the ‘asymmetry’ of doctor-patient interaction’. In: D. Boden, D.H. Zimmerman, eds. Talk and social structure: studies in ethnomethodology and conversation analysis. Cambridge: Polity Press: 138- 63 

Have, Paul ten; George Psathas, eds. (1995) Situated order: Studies in the social organization of talk and embodied activities. Washington, D.C.: University Press of America

Have, Paul ten (1999) Doing conversation analysis: a practical guide. London etc: Sage 

Have, Paul ten (2004) Understanding qualitative research and ethnomethodology. London etc.: Sage

Have, Paul ten (2005) ‘The Notion of Member is the Heart of the Matter: On the Role of Membership Knowledge in Ethnomethodological Inquiry’, Historical Social Research / Historische Sozialforschung 30: 28-53 

Have, Paul ten (2013) ‘Identifying birds by their song’. In: Peter Tolmie, Mark Rouncefield, eds. Ethnomethodology at Play. Farnham, Surrey, U.K.: Ashgate

Harrie Mazeland, May 10, 2022

Guest Blog: The EMCA Doctoral Network Meetings restart, November 2021

Among the many formal and informal networks that support postgraduates and early-career researchers in CA and ethnomethodology, the EMCA is perhaps the most venerable and global. I’m delighted that two active members, Felicity Slocombe and Andrea Bruun have sent a report on the most recent meeting, November 2021.

The EMCA (Ethnomethodology and Conversation Analysis) Doctoral event ran every six months, pre-pandemic, with universities taking it in turn to host the event.

The event allows doctoral researchers to meet and engage with others using similar methodologies within their research and provides a vibrant context for building contacts and developing presentation skills within a friendly environment. Due to coronavirus restrictions, it had been two years since the last event. So we’re glad to report that the Network’s life has restarted: the event started up again, in person, on the 8-9th November 2021 at Loughborough University.

In this blog we will hear from two doctoral researchers who attended the event. Firstly, we will hear from Andrea Bruun from UCL whose research uses conversation analysis to examine prognostic decision-making within specialist palliative care multidisciplinary teams. We will also hear from Felicity Slocombe who was one of the doctoral researchers who helped organise the event. Felicity is from Loughborough University and her research uses conversation analysis to look at how we can maintain identity of people living with dementia.

What it was like as a participant: Andrea Bruun

It seemed unbelievable that this year’s EMCA doctoral network meeting would go through and actually be an in-person event. After having participated in virtual conferences and online data sessions in what feels like forever (since spring 2020), it was absolutely brilliant to meet people in real life and feel like you were at an actual conference again. You remembered how it felt like to small talk with people in 3D by the coffee table, actually raising your hand if you had a question, participating in actual applauses, and feeling the vibrant atmosphere that only comes with being in the same physical room together. 

As if meeting people at an in-person conference was not fulfilling enough, imagine that these people are also PhD students like yourself. Imagine the room of support and experiences being shared because everyone is on the same journey. Then imagine that every single one of these PhD students are working within the same field as you. Now you are frosting the support and the experience with a heavy layer of community, sprinkled with passion. If you are from a university or department with none or only a few people doing EMCA, then it felt like coming “home” – you felt understood. No matter who you turned to, they were on the same page as you, you did not have to defend your method or explain every little detail. This made it so easy and such a pleasure to network and make friends during the days.

This home we built on only two days housed the most diverse community within the EMCA tradition. People were working on data from many different settings; all the way from GP consultations to museums, even criminal trials, to grassroot group meetings. The presentations and data sessions involved all sort of topics such as transcription of laughter, analyses of specific words or question formats to how technology is used in interaction. It was so inspiring to see how diverse EMCA research is, and you got the feeling as if only the sky is the limit.

Having two days only focusing on EMCA was like falling in love with a partner all over again. Sometimes you can get stuck in your methods and (pessimistic and critical) ways and you might have a feeling of EMCA research not being enough – something is missing, and the grass might seem greener on the other side. But digging into all the exciting data, meeting such wonderful people, and having really interesting discussions made it clear why EMCA is important and why we are doing it – and then a lovely hotel stay and a delicious conference dinner for free do indeed help with making you fall head over heels.

Loughborough University

What it was like as an organiser: Felicity Slocombe

The EMCA doctoral event was a great event to be involved in organising. The organising committee consisted of academic staff and doctoral researchers: Prof. Alison Pilnick from the University of Nottingham, Dr. Marco Pino, and Dr. Jessica Robles, both from Loughborough University, Rachael Drewery from the University of Nottingham and Chloe Waterman from the University of Birmingham, who is in the write up year of her PhD and is now a Research Associate at King’s College London. We worked together to organise different parts of the event, such as the room booking, catering, and programme. It was a real team effort and especially lovely to work with Rachael and Chloe who are ahead of me in their PhD paths. 

My favourite part of the event echoes Andrea’s: of being in the same physical space as others. It felt like a friendly environment in which everyone felt comfortable to contribute their thoughts and experiences. It was great to have a meal together on the evening of the first day, everyone seemed in high spirits having not been able to meet like this with others throughout the course of my PhD so far, it was so refreshing and inspiring. The presentations, data sessions and papers-in-progress were so diverse and equally fascinating. I had the opportunity to present my data on the second day and the observations made have really helped me in beginning my analysis. 

Keynotes. Additionally, a big draw to the event were the keynote talks given at the end of each day: one by Prof. Charles Antaki, and one by Dr Jessica Robles. Charles spoke about ‘Asymmetries in interactions between people with learning disabilities and those who support them’. This was a stimulating talk which examined how staff members support people with learning disabilities in attempting a task. Charles contrasted two different approaches that staff members have taken: one in which a staff member uses directives and imperatives, where a distinct asymmetry between the staff member and the person with learning disabilities is evident from the interaction, in the other example the staff member tries to reduce the asymmetry between themselves and the person with learning disabilities. It was interesting to see how the two strategies work.

Jessica’s keynote discussed ‘Forms of allegedly non-racist race talk as possible instances of racism’. Jessica’s talk was thought-provoking and recognisable in conversations had with extended family members of claims of non-racist racist talk. Jessica discussed the practices that feature in the phenomenon of ‘non-racist’ race talk, which is an under-explored area in EMCA research. The two questions Jessica discussed were: (1) what counts analytically, for participants, as ‘racism denial’ or talk about race produced as ‘not racist’? and (2) how might racism denial be analysed as accomplishing racism? These questions were explored using examples from naturalistic interactions as to how racism denials are produced in their context, and how these cases can be analysed as possible instances of racism.

A big thank you to all those who attended, presented, and especially to the keynote speakers. I hope that more events like this become more possible in the future and return to their bi-annual appearance!  

Guest Blog: SPAC, an online space for doing CA in Spanish

CA is well established in a number of Spanish-speaking countries, but there is always room for more initiatives, and for ways for sometimes isolated researchers to meet together. I’m delighted that Luis Manuel Olguín has sent in a report on the Seminario Permanente de Análisis de la Conversación, a lively and inclusive forum for Spanish-speaking CA researchers.

Luis Manuel Olguín, UCLA

Although CA is well-known across Spanish-speaking academia, resources for learning and teaching CA in Spanish are still significantly scant, especially if compared to other approaches to language use and social interaction with established traditions in Spain and Latin America. Similarly, the Spanish-speaking CA community is still relatively small and largely scattered across countries, making it difficult for CA to take root in Language and Social Science programs and departments. 

Luckily, this situation is starting to change thanks to SPAC, an international collaboration that brings together language and social interaction scholars and students around the globe to do CA in Spanish. 

SPAC’s logo

Seminario Permanente de Análisis de la Conversación (SPAC) is an online space for collaboratively learning what CA is all about. The idea of a “seminar” responds to SPAC’s efforts promoting CA practice at different levels of expertise as well as designing and making freely available resources for learning and teaching CA in Spanish. 

SPAC’s activities include monthly talks and workshops, as well as weekly (yes, weekly!) data sessions. Since our launch in January this year, we have organized 11 events, ranging from talks on classroom interaction in Chile and summons practices of deaf communities in Mexico, to workshops on transcription, ELAN, and multimodal analysis. All our events are recorded and uploaded to our YouTube channel.

Chase Raymond (UC Boulder) gives a talk on exploring Spanish morphology in interaction in May 2021

Data sessions–or observatorios de datos, as we call them in Spanish, highlighting CA’s characteristic approach to data analysis–are SPAC’s most cherished and defining activity. SPAC’s data sessions take place every Tuesday at 18:00 UTC and run year-round. We primarily focus on ordinary conversation, working on a single episode over the course of several weeks and, recently, on assembling specimen collections. We encourage participants to bring their own data too, so they can benefit from others’ observations. You can read more about SPAC’s data sessions in this ISCA report written by Verónica González Temer (UMCE, Chile) and Katherina Walper (UAC, Chile) earlier this year. 

SPAC data session

SPAC is coordinated by an international team of CA practitioners and enthusiasts. For 2021, they are Verónica González Temer (UMCE, Chile), Alexa Bolaños Carpio (UC, Costa Rica), Ariel Vázquez Carranza (UG, Mexico), Elizabeth Manrique (UCL, Argentina/England), Carmen Del Río Villanueva (PUCP, Peru), and Luis Manuel Olguín (UCLA, Peru/USA). 

Other SPAC projects

Aside from organizing SPAC’s monthly events and weekly data sessions, the team is putting together a bibliography of CA publications on Spanish talk in interaction as well as those written inSpanish, such as textbooks and specialized work that might help colleagues at Spanish-speaking institutions introduce CA to students. The team also runs a GoogleGroup with more than 200 subscribers from Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Mexico, Peru, Spain, the U.S., among other countries in Europe and the Americas. The listserv is used to disseminate information about recent publications and upcoming events of interest to the community.

SPAC is a chapter of Conversanalista, a larger vision to foster interactional research methods in Spanish-speaking academia and to progressively consolidate a network of language and social interaction scholars across Ibero-America. 

Si estás interesado/a en saber más sobre las activades de SPAC, suscríbete a nuestra lista de distribución enviando un correo electrónico a conversanalista+subscribe (arroba) lists (punto) ucla (punto) edu. 

The author

Luis Manuel Olguín is a PhD Candidate in Sociology at UCLA. His research explores how everyday language practices reflexively shape exchange behavior and economic action, with a particular empirical focus on Spanish talk in interaction. 

Guest Blog: Promoting CA in Brazil

As Conversation Analysis is increasingly taken up by researchers across the world, we are seeing efforts to bring the approach to their wider local communities. There are several initiatives in Brazil, and I’m delighted that Fabio Ferraz de Almeida, currently working in Finland, has sent in this report of an inaugural workshop in Sao Paulo.

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Fabio Ferraz de Almeida

The idea of organising an introductory CA workshop in Brazil began to take shape last year, while I was talking to a colleague, Bruna Gisi, professor of Sociology at the University of São Paulo (USP). Bruna was developing a postgraduate course on EM and Goffman and invited me to participate in one of the lectures. According to her, several sociologists in Brazil often talk about ethnomethodology but they rarely show how to put  it to use. Her suggestion was that we  discuss a particular EM concept and show how to ‘apply’ it in empirical research. 

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Guest Blog: Using inclusive language when transcribing French data

Every language poses it own problems when transcribing from the spoken to the written word. In this guest blog, I’m delighted that Dennis Dressel, Wifek Bouaziz and Marie Klatt, all at the University of Freiburg, take us through the dilemma of transcribing French, with its convention of treating plurals as masculine, while also trying to respect inclusivity. How does the transcriber acknowledge references to females when the language conventionally refers to them as male?

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Guest Blog:  Building an EMCA community at CADSS

Groups of EM/CA analysts have sprung up all over the world to share expertise, pore over data together, bounce ideas off each other and provide a sense of shared community. Here Simon Stewart gives an enthusiastic account of recent developments of the group based on the south coast of England.

Simon Stewart, Southampton

This post is intended to share with the CA community some of the resources and learning that have come from our group, CA Data Sessions South (CADSS), in its first 18 months.

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Guest Blog: In memory of Jack Bilmes

All of us at ROLSI were sorry to hear of the death, in May of this year, of Jack Bilmes, one of ethnomethodology’s most original and independent voices, and a warm, generous and caring man. I’m very grateful to Professor Gabi Kasper, an old friend and teaching colleague of Jack’s, for allowing us to reproduce here the obituary that was read out at this year’s IPrA conference. The paper that Jack was to have presented a paper there will, happily, be published in Discourse Studies (1).

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