Guest Blog: Writing “Ethnomethodological Conversation Analysis in Motion”

There’s an increasing demand for Conversation Analysis texts as the discipline becomes established, and new markets emerge among students and researchers. One of the most intriguing texts to come out soon is Ethnomethodological Conversation Analysis in Motion: Emerging Methods and New Technologies, edited by a group based at Oulu University. I’m delighted that the group have written a piece for the blog.

L to R: Antti Kamunen, Pentti Haddington, Tiina Eilittä, Tuire Oittinen,
Anna Vatanen, Laura Kohonen-Aho, Iira Rautiainen.

In 2020, during the first months of the pandemic, we had been working on a book proposal on the Complexity of Interaction (also forthcoming in 2023) and had sent it to a publisher. In their response, the publisher expressed an interest in some of the chapters and their focus on “the development of methodology and methods in EMCA” (their words) and suggested we put together a separate book on that theme. 

Intrigued by the idea, we formulated some guiding questions and sent them to colleagues who we knew were using innovative research approaches within EMCA. We wanted to capture what was going on as a live, developing stream of scholarship and methodology – hence the “in motion” of the title. 

What we asked potential contributors was along these lines:

  • What aspects of their research had guided them towards creative methodological thinking? 
  • What traditional and new solutions had they used, and to what ends? 

Luckily, it didn’t take too much begging and pleading to get those colleagues aa potential authors, and we soon began to receive abstracts. As a result, the following question began to emerge and unite the current book’s chapters: What can be treated as evidence for analytic claims in EMCA, and how can such evidence be analysed and represented? The new proposal began to take form. We submitted the book proposal in February 2021. 

How to write about CA’s claims, and the evidence for them?

The intellectual process – including the writing of the book proposal, the compiling of a thematically coherent volume with contribution to the EMCA field, and the writing of the introductory chapter – was both challenging and exciting. It was important throughout to keep in mind that we were trying to track what was new and exciting in the discipline. It entailed various stages and working methods: we read texts together, made mind maps, wrote parts of texts both together and individually, and had repeated – sometimes endless – discussions around theoretical and methodological matters. In other words, we did a lot of going back and forth, which was necessary for the development of our thinking and putting all the pieces together.

A crucial stage in the overall process was a cottage getaway in beautiful winter scenery in a place called Rokua in December 2021, where we spent two days working intensely on the volume. A couple of months earlier, we had received one reviewer’s feedback on the proposal. The feedback was critical but very helpful, and the getaway allowed us to brainstorm and reorganize our thoughts and ideas that were, at that point, still quite dispersed. For instance, how we perceived the relationship between EM and CA and positioned ourselves in the field remained a question to be answered. Along with having great fun as a group, we experienced a breakthrough regarding the book’s overall focus: how an analyst can access a member’s perspective in interaction. This really helped us to rethink the book’s structure and formulate a response to the reviewer’s comments.

 The editors (l to r: Tiina Eilittä, Iira Rautiainen, Pentti Haddington, Tuire Oittinen, Antti Kamunen and Anna Vatanen)  at a two-day book planning getaway in December 2021, a picture requested by the then very pregnant editor Laura Kohonen-Aho, who participated remotely.

Having seven editors is not typical for books, nor is it conventional that five out of the seven are early-career researchers (ECR; doctoral and postdoctoral researchers). For them, the book project gave insights into the editor’s perspective and the steps involved in publishing a book. Early-career researchers’ input can be very beneficial to these kinds of projects by bringing in fresh, new viewpoints.

As a result, what we hope to have achieved is to test the boundaries of the field, while also respecting the established practices of doing EMCA research. The discussions about the concepts, theory, and methodology were helpful to all, and we all learned from each other. Moreover, another significant thing we learned from the process was how to work together intensively in remote and hybrid modes. The practices for remote collaboration we developed during the process have benefitted us all after the pandemic began to ease off. 

Reflecting on conceptual and methodological trends

During the process, we did a lot of juggling with concepts, which forced us to rethink our understanding of the EMCA methodology. In its final form, the book presents three themes in the field:

  • members’ private actions – how are private actions relevant for the organisation of social order and how can they be studied?
  • the analyst’s access to a member’s perspective – what means can be used to examine the perspective of understudied participants (incl. non-sentient, non-human species)?
  • the emerging trends of the EMCA methodology – what other methods and technologies can be used during data collection, analysis, and representation?

In the end, those themes informed 12 chapters, with headings like ‘Transcribing human-robot interaction: Methodological implications of participating machines’, ‘EMCA informed experimentation as a way of investigating (also) “non-accountable” interactional phenomena’, and ‘A satellite view of spatial points in conversation.’ We hope that this book acts as a conversation opener and inspires discussion on the development of the EMCA methodology! This is key reading for researchers and advanced students on a range of courses on conversation analysis, language in interaction, discourse studies, multimodality and more.

The cover of the book.

We use the title Ethnomethodological Conversation Analysis (EMCA) and are aware of the problems connected with the label, but we use it deliberately to emphasize the importance of the ethnomethodological roots for doing conversation analysis.

Together, they are considered to form an analytic mentality and approach for studying the construction of action, activities, and social order.

Guest Blog: Promoting EM/CA in China

There is a growing interest in EM/CA in China, and I’m delighted that Enhua Guo, from the Ocean University of China, has written us a lively and informative account of new developments. In celebrating the 100th HDS (“Happy Data Session”) in China, he reflects on its evolution over the past three years, highlighting local practices, and sharing key takeaways with the international EMCA (Ethnomethodology and Conversation Analysis) community.

Enhua Guo

Data sessions are a crucial component of EMCA research and serve as one of the most fundamental means of conducting EMCA studies. On the foundational and pioneering work done by K.K. Luke (陆镜光), EMCA in China in the past two decades has seen remarkable development and growth, thanks to the unwavering efforts of some leading Chinese conversation analysts as Guodong Yu (于国栋), Yaxin Wu (吴亚欣), Wei Zhang (张惟), along with Ni-Eng Lim (林尔嵘) from Singapore.

Despite the significant contributions made by these experts, the field of CA in China is still in its early stages, with only a few universities and research institutes regularly conducting CA data sessions. These include Ocean University of China, Shanxi University, Shandong University, Shanghai University of Finance and Economics, among others.

  • Beginnings: the Ocean University CA research team, Covid-19, and a new era of Chinese CA research

On January 18, 2020, just days before the Covid-19 outbreak in China, I began my position as a lecturer at Ocean University of China (OUC) after completing my Ph.D. at Tongji University. I was thrilled to learn that two leading Chinese CA experts, Guodong Yu and Yaxin Wu, had very recently joined OUC too as distinguished professors. As someone who had been introduced to the fascinating world of CA by Prof. Yu, I felt incredibly lucky and privileged to join OUC, which has rapidly developed into a new CA hub in China. Shortly after my arrival, the Ocean University of China established the CA research team (OUCCA), which is led by Prof. Guodong Yu and directly funded by OUC at the university level. However, the Covid-19 pandemic forced OUC to close its campus throughout the spring 2020 semester, delaying OUCCA’s first in-person data session until the Fall.

Guodong Yu

Despite these challenges, Chinese CA scholars remained passionate about data sessions. Thus, the idea for the “Happy Data Sessions” (HDS) was born as a response to the need for virtual data sessions. On April 23, 2020, the first HDS webinar was launched by Guodong Yu (leading host) and me (Enhua Guo, as executive co-host) as part of the OUCCA Team. Over the past three years since its inception, HDS has established itself as the leading online platform for Chinese-speaking CA researchers around the globe. It provides a space for researchers to showcase their findings and benefit from in-depth data analysis.

  • The Happy Data Sessions – its goals and its platforms for achieving them

HDS is dedicated to achieving three key goals: (1) expanding the community of Chinese CA scholars, (2) applying CA insights and methods to both mundane and institutional Chinese data, and (3) investigating the features of Chinese talk-and-body-in-interaction. The HDS sessions are conducted through the platform of Tencent Meetings (known as VOOV Meetings outside China). The first 70 sessions were conducted every Wednesday between 18:00-21:00. Since the 71st session, the timing has been changed to every alternate Wednesday between 19:00-21:00. In each HDS webinar, we have at least one experienced CA expert attending, including Yaxin Wu,Guodong Yu, Ni-Eng Lim, Wei Zhang, etc. Through their own data analysis, experienced CA experts can demonstrate to CA novices how to look at data from the participant’sperspective. 

Apart from its webinar, HDS has another interactive platform: its own WeChat group, which has 197 registered members and is still expanding. Since all potential HDS meeting participants are members of this WeChat group, it is used to give updates for upcoming HDS webinars and share post-session thoughts and files. Additionally, it also serves as a forum for members to discuss any questions or thoughts related to CA. As many well-known Chinese CA experts are also members of this group, it provides an excellent platform for members to benefit from thought-provoking discussions and stimulating exchanges.

  • Invisible mode of HDS

Every HDS webinar has an average of 30 participants. One of its notable characteristics, as distinguished from many other international CA webinars, is that all participants prefer to remain invisible during the meetings. This means that participants can only see each other’s avatars (with identified names below) and their microphone status (mute or unmute), but not their faces or other embodied features. 

While it remains to be explored whether unwillingness to show their faces during HDS meeting is related to the implicit, withdrawn ethos in Chinese culture, the lack of mutual visibility could sometimes make it difficult for participants to organize their turn-takingusing nonverbal cues such as eye gaze and other physical gestures. Furthermore, Tencent Meeting’s technological sensitivity to the “one speaker at a time” rule, as well as the potential for multiple participants to simultaneously respond to a prior speaker’s turn, can create challenges in managing overlaps and silence during data discussions. 

A screen grab of a typical HDS meeting

Fortunately, Tencent Meeting later introduced the “HAND UP” feature, similar to Zoom’s, to compensate for the lack of embodiment characteristic of in-person data sessions. Apart from the advances in technological affordances offered by the Tencent Meeting platform, HDS has also developed practical methods to facilitate smooth turn-taking among participants. For example, if prolonged gaps occur, the host will intervene and allocate turns to ensure the progressivity of the discussion. Of course, the next speaker can always anticipate the end of the current speaker’s ongoing turn and unmute themselves immediately before their turn arrives to minimize any gaps caused by the unmuting operation itself.

  • When HDS meets DMC (DIG Mandarin Conversations)

One of the Ocean University CA research group’s main objectives is to promote the development of CA (as well as interactional linguistics) in China. To achieve this aim, OUCCA has been dedicated to building an open-access Chinese conversation corpus known as DMC (DIG Mandarin Conversations); DMC is the very first daily telephone call corpus collected in mainland China, transcribed with Jeffersonian system and accessible to all possible users (See more on Guodong Yu, Yaxin Wu, Chase Wesley Raymond, forthcoming). Meanwhile, for over three semesters, HDS has also been constructing an insider-access corpus of Chinese conversations only within the HDS WeChat group on voluntary basis. Recently, we have made the decision to open access to this corpus and integrate it into DMC, provided that written consent forms be obtained from participants being recorded in the data.

  • Celebrating 100th HDS: a talk given by Prof. Wei Zhang
Wei Zhang

To celebrate the 100th Happy Data Session (HDS), Professor Guodong Yu invited Professor Wei Zhang, a renowned expert in Chinese Conversation Analysis from Tongji University, to deliver a two-hour online talk entitled “Data Session & Conversation Analysis-Celebrating the 100th Happy Data Session”. The lecture attracted more than 100 active participants from both China and other countries. Prof. Zhang provided a thorough and systematic overview of the significant role of data sessions in CA research, covering its origins, purposes, approaches, and principles. Using two concrete examples of interactions, she demonstrated how CA practitioners conduct data sessions. This talk has been very enlightening and beneficial, especially for researchers outside EMCA community who share an interest in research on language and social interaction.

The future of the Happy Data Sessions in China

The Ocean University CA team remains fully committed to advancing the progress of EMCA in China through two major initiatives.

First and foremost, we will continue to organize HDS data sessions every other Wednesday from 7:00-9:00 p.m. We plan to enhance our HDS data sessions by diversifying the types of data presented, featuring not only traditional interactions, but also technology-mediated interactions, such as CMC, human-machine interactions, Metaverse interactions, etc. By incorporating more video-recorded data, we strive to ensure that HDS sessions provide ample space and opportunities for multimodal conversation analysis. Also, we seek to foster a more inclusive participant base by welcoming participants from a range of disciplines, including sociology, psychology, communication studies, and others aside from linguistics. We will remain dedicated to supporting young scholars who are new to EMCA, and hope to inspire their active participation.

Looking to the future: our open-access DMC corpus expansion efforts will continue by working hand-in-hand with the 200 registered HDS members. At the start of every semester, we will launch a recruiting drive to seek volunteers willing to contribute to the publicly-accessible data pool (including the finely-grained transcripts of the data), as part of our ongoing commitment to expanding the size and scope of DMC corpus.

Guest Blog: The Conversation Analyst as an Expert Witness in the Courtroom

Some court cases rely on the interpretation of verbal exchanges – recorded conversations, interviews, police interrogations. The expert may be asked to say whether something is evidence of a bribe, a threat, a confession, and so on. Gary C. David PhD CCS is one of the very few conversation analysts who have been called on to help the court. His report makes for fascinating reading.

Gary C David, Bentley University

When is an interrogation and interview, or an interview an interrogation? How much does it matter how such encounters are characterized versus what they look like? How can we tell the difference between the two? These are questions that I had to address as I was asked to examine a police encounter with a person suspected of murder. My expert opinion could make a difference in whether evidence is admitted or excluded, and whether the suspect goes to trial or goes free.

For the past approximately seven years, I have been working on legal cases in which police interviews and interrogations have been called into question. I originally started this work with retired Detective Jim Trainum, a nationally recognized expert on false confessions. I got to know of Jim’s work through hearing him on an episode of This American Life, where he was discussing his role in unknowingly producing a false confession. After reviewing the video recording of the police interrogation, he was able to identify how he and his partner generated a false confession. As he retold this story, I immediately saw the potential for conversation analysis to contribute to this work. After contacting him and introducing myself, he agreed, and we have been working together ever since.

Coercion and contamination

Typically, I work on cases in which the police/suspect encounter is called into question, focusing on whether coercion and/or contamination produced a false confession. Coercion would involve law enforcement creating duress for the purposes of getting a confession, such as promising (or even strongly implying) a reduced sentence in exchange for a confession. Contamination involves law enforcement providing details of the crime to such an extent that it can’t be known whether the suspect was really there, or just repeating what they were told.

When working on these cases, I position CA under the category of forensic linguistics, which broadly includes approaches focusing on the nature and impact of oral and written communication/language occurring in legal contexts. Conversation analysis has been identified as part of that field, especially for the purposes of research and scholarship. However, I don’t believe CA has been introduced as a scientific area of analysis in criminal proceedings. Until now.

A typical US police interrogation scene (Source: Youtube)

An example case: interview, or interrogation?

For one particular case, I was asked by defense counsel to evaluate a police encounter with a suspect to determine whether it was a non-custodial interview or a custodial interrogation. This determination is important because it determines whether or not the suspect’s Miranda rights need be given. I was asked to use my training as a conversation analyst, my participation in police interrogation training programs, and my previous work on other cases to render an expert judgment on whether the encounter was an interview, interrogation, or both. To do so, I reviewed the following materials:

  • The police encounter with the suspect, both audio recording and official transcript
  • Transcripts from pre-trial hearings
    • Police reports from the investigation

In the United States, the primary method of interrogation is known as an accusatorial approach, meaning that the goal of the encounter is to get the suspect to confess to the crime. This can be compared to the information-seeking interview where the investigators are looking for information regarding the crime. Each is identifiable by the conversation structures present, as well as the tactics used. Thus, determination of interrogation or interview is not a matter of opinion, but a matter of examining the structures and practices

Working with the court

In my role as expert, I had the opportunity to be part of a pre-trial motion hearing where I shared my analysis with the judge, the prosecutor, and the defense counsel (with whom I was working). Part of that process included trying to explain what conversation analysis is and how it was applicable to this case. In doing so, I was able to establish that forensic linguistics and conversation analysis are scientific methods that can be used for the examination of police encounters with suspects. As a result, the court deemed that CA is an appropriate tool for rendering judgments on the nature and structure of these interactions.

A number of CA’s features were important as part of testifying.

First, that we rely on analysis and description rather than interpretation and assessment of mental states which can raise objections in courts in terms of admissibility.

Second, the ability to go “back to the data” in the form of the transcript as forms of evidence to support our analysis. It is not my opinion that this is happening; I can point out where and how it is happening in the transcript and recordings.

Third, focus on audio (or video) recordings to explore parts of the encounters that are not rendered on the official transcript. This focus on listening also is important in terms of checking the accuracy of the official transcript. Fourth, the corpus of conversation analytic work and concepts that have come before which can be used in the examination of police/suspect encounters.

My judgement to the court

I was able to come to a firm conclusion for the court. My assessment was that the encounter was, in fact, an interrogation: it had the conversational structures and interrogation tactics associated with an interrogation. This wasn’t my expert opinion, but rather my expert analysis.

While I don’t currently know the outcome of my testimony, I do know that the three hours that I spent testifying allowed me to highlight the importance of conversation analysis in the examination of police/suspect encounters. Defense counsel admitted that he was skeptical of what I could contribute going in, but then realized the importance of CA in the examination of such encounters. As more CA work is done as expert testimony, we can expect more people to see the value that CA can contribute to legal cases and courtroom proceedings.

Gary David is a Professor of Sociology and Experience Design at Bentley University (Waltham, MA). You can read more about his work and thoughts at  You also can learn more about his professional and consulting work at

Guest Blog: Doing CA on hospital wards with front-line healthcare professionals

Conversation analysis offers a great deal to those trying to improve how to communicate with people with disorders of language. It’s not always easy, and practical obstacles keep getting in the way: Isabel Windeatt from Nottingham University gives us a lively account of what it’s like to collect and analyse data on a ward for older people .

Isabel Windeatt

I’ve been working closely with front-line healthcare professionals in my role on the VOICE2 study, a conversation analytic study of communication between staff and people living with dementia who are in hospital. I want to share the benefits of collecting data and sharing preliminary CA analyses with healthcare professionals, as well as some of the challenges, in the hope that others will find solutions to collecting data in challenging environments, and be encouraged to involve healthcare staff during the analysis.

The healthcare professionals I refer to are ward-based staff who are unfamiliar with CA and don’t undertake research. I also work with clinical academics who are familiar with CA and recognise its value in healthcare research – they’re the reason I have a job.

Recruiting healthcare professionals on acute hospital wards

The data I’ve been collecting involve naturally occurring interactions on UK acute hospital wards between healthcare professionals and patients living with dementia who were prone to distress, recorded at times when distress was anticipated to occur or had previously occurred.

First, I had to get familiar with the scene. This required a traditional ethnographic immersion in the data collection process. From March to September 2022, myself and 3 other researchers spent 6 months on acute older persons’ hospital wards to collect almost 10 hours of video and audio data.

You have to become familiar with the everyday realities of the scene

Much of that time was spent finding patients for the study and recruiting willing healthcare professionals from amongst the healthcare assistants, doctors, nurses and therapists working on the wards. I had to try to build the trust of staff by talking with them, getting to understand their roles, and generally becoming a bit of a ward fixture so that staff could get to know the person behind the camera. Staff were always busy. I was careful to introduce myself to as many staff as possible and explain what we were doing on the ward – it’s a bit intimidating having someone unfamiliar turning up at your workplace with a large folder and recording equipment, watching and taking notes on what you’re doing!

Start at local manager level. Initially, we presented at a Ward Managers’ team meeting so that those running the wards knew who we were and what we were doing on their ward. We would also approach Ward Managers when first arriving on a ward, recruiting them to take part in the study as this set an example for other ward staff, encouraging them to sign up as well. The Ward Managers recommended staff who might be comfortable in front of the camera. We also presented at Medics’ team meetings and attended board round meetings on the wards. This networking offered our first recruits on each ward and, having broken the ice, recruitment would snowball as talk about the study passed between healthcare professionals.

Recruiting people on the fly

That’s not to say we didn’t have to do our fair share of ‘cold recruitment’. Many healthcare professionals who signed up were those we had to pitch the study to from scratch. For this, having a polished ‘elevator pitch’ was useful, and helped with any nerves about distracting a healthcare professional at work, especially as reading a 10 page long study information sheet didn’t make signing up all that appealing. This pitch would often get interrupted by staff having to dash off to attend to a patient, or a patient might instead stop me – either thinking I was their relative, falling asleep on me, or just wanting to chat. I’d find the healthcare professional later, if possible, to resume our talk when there was a brief moment of calm between patient-focussed tasks, such as when they were watching over their assigned bay.

Not everyone wanted to be part of the study. Many healthcare professionals didn’t feel comfortable being filmed and I even received one unmitigated ‘no’ without any delay or account. Fascinating interactionally, but also mildly disheartening. However, I found many staff were still happy to chat about patients who might be suitable for the study, giving me valuable information on distress patterns of patients I was going to speak to. They would also share their own experiences of dealing with patient distress, and cajole other healthcare professionals to take part.

Blending in

We were careful to emphasise that staff did not have to take part, that they could stop at any time, or say ‘not today’ to us. For those that did take part, our two stage consent process, in which we took consent for future use of video material after they had viewed the recording, meant that they could decide after the recording how they would like it to be used and who would see it. 96 staff allowed us to take up their already limited time by agreeing to take part, a testament to their interest in improving care and demonstrating a selfless nature.

Getting immersed in data collection

A lot of the time, the patient being filmed would wander about the ward, or staff would shifting positions to do their work. So I had to navigate around the scene, trying to keep the interaction on screen, but also keeping in mind patient dignity by covering the camera lens if the situation demanded it.

Seeing how staff handle difficult moments

It was very illuminating collecting data in this way. I got to see first-hand what life on the wards was really like for staff. In my first week, a patient I was assessing the capacity of, switched from being quiet and calmly spoken, to yelling at me that he wanted to murder someone. Staff suggested that it was best just to ignore this behaviour and I had many pleasant chats with this patient after this occurrence. In the few months I was there, I’ve witnessed patients throwing walkers and anything else to hand at staff, fighting each other, and trying break the ward doors open to escape. One of my most memorable occurrences of distress, was a patient who, at the time of his distress, believed staff on the ward were a gang who had taken his young children. This gentleman had taken another patient’s shoes thinking they were his, then used them to hit a ward window, resulting in a resounding crack and broken window. Staff were amazing in all of these circumstances, responding calmly, and with understanding, to patients who couldn’t always help their disinhibited behaviour.

The biggest benefit of being so immersed in the data collection, was that I was able to
learn about the context of the interactions that I would otherwise have missed out on. As the focus of our research – distress – could be fleeting, being on the ward for long periods allowed us to collect field notes to be used alongside the recorded data, something not always done with CA (Mondada, 2012:33; ten Have, 2007:88). Much of our data is better understood in the light of the context of the patients’ prior distressed episodes which these field notes provide.

Hit and miss with data collection

Data collection was time consuming: on some days no data collected, and others more time was spent standing around observing, or waiting for a healthcare professional to undertake a task with a recruited patient. On these long days I was very grateful to the wards that had sofas in their bays.

It was a tiring but valuable process, and being on the wards for these extended periods allowed me to learn some of the healthcare jargon and contextual information that I lacked as non-clinical analyst. It’s also given me a better appreciation of healthcare professions’ concerns, an understanding of their roles, and of what our research is being done in support of.

Sharing analyses with other healthcare professionals

I’ve since shared some work-in-progress with other healthcare professionals at monthly project management group meetings and with a community based team in another NHS Trust. Online meetings make doing this sort of dissemination much easier. The analysis I presented wasn’t finished (is it ever?), and I didn’t have any concrete findings to show them. They understood that and didn’t push me for any. What they did do, was offer their own perspective on the data as healthcare professionals. Presenting here offered valuable insights on the analyses and new perspectives into the data that I otherwise may have missed. It reminded me to take a step back from the data and consider why we are doing this research.

Final thoughts (for the moment). A commendable goal of any research is to have the findings from it put into practice and travel beyond academia. The point of research is to learn, not just for the sake of learning (which is still a valuable endeavour), but to also apply that learning to the real world. Working and sharing work at each stage with healthcare professionals is an essential part of the research process to ensure that we have a practical impact with our findings. Building a network of relationships with front-line healthcare professionals and having ongoing discussions with them helps to ensure that our work is relevant and applicable and we should strive to ensure this becomes an essential part of the research process whenever possible. Personally, I’ve found it by turns exciting, frustrating, and occasionally emotionally challenging – and utterly fascinating throughout.


Mondada, L. (2012). The Conversation Analytic Approach to Data Collection. In The Handbook of Conversation Analysis (eds J. Sidnell and T. Stivers). 

ten, H. P. (2007). Doing conversation analysis. SAGE Publications, Limited.

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.

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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
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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.

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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. 

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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.

This image has an empty alt attribute; its file name is screenshot-2020-12-21-at-11.23.30.png
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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