This study investigates workplace interactions where peer's linguistic backgrounds are topicalized. Analyzing video recordings of backstage interactions (Goffman, 1959), the research highlights different interactional consequences of topicalizing peers’ native languages and how it results in transformations in participation frameworks and thereby in the situated identities of participants. To address the main aim, the study uses an ethnomethodological conversation analytic approach to examine how participants respond to language-related inquiries, such as “How do you say X in your language?”, and how these inquiries serve as membership inference-rich devices. The findings reveal that topicalizing a peer's language (other than the main medium in the group) can trigger various activity types, including jocular interactions and informal learning. Moreover, the interaction may lead to the display of possible vulnerability, as unfolding talk can position individuals as marginal within the group and thus occasion stance-taking toward that positioning with resistance.

This study examines how smartphone-based use of Google Translate reconfigures turn-taking and interactional progressivity in multilingual workplace encounters. Drawing on ethnomethodological conversation analysis, it shows how three-turn sequences (initiation, response, and confirmation) are expanded through pre- and post-phase actions necessitated by digital mediation. These include GT processing delays, interface monitoring, and embodied conduct related to device handling and screen presentation. The analysis demonstrates how participants balance the need for sequential progressivity with the maintenance of intersubjectivity, even when interaction is prolonged by technological constraints. Rather than treating translation-induced pauses as disruptions, participants incorporate them as structurally embedded elements of extended turn construction. By analyzing shared-device (single smartphone) and dual-device (two smartphones) configurations, the study highlights how access, turn visibility, and participation rights are collaboratively managed. These findings contribute to understanding transmodal coordination in digitally mediated communication and offer new insights into the interactional consequences of translation technologies in workplace settings.

As large language models such as ChatGPT are increasingly used as live translation tools in multilingual workplaces, they reshape coordination while introducing new interactional demands. This article examines how ChatGPT, when used as an interpreter, reorganizes talk in real-time workplace interaction. Drawing on Ethnomethodological Conversation Analysis, the study analyzes two multilingual workplace encounters mediated by ChatGPT. The analysis identifies three adaptive practices: machine-directed turn construction, negotiation of AI output, and turn-allocation management, in which AI is positioned as an on-demand participant. These practices are accomplished through coordinated talk, gaze, gesture, and device handling. The findings demonstrate that translation emerges as an interactional achievement shaped by accountability, turn-taking, and human-AI