Shaping the register in crowdsourced crisis translation: an actor-network approach

This study investigated how the register of the crowdsourced translation COVID-19: From Basics to Clinical Practice was shaped by human and nonhuman actors in response to crisis-specific demands. Multidimensional analysis showed that the initial translation approximated the register profile prescribed by the source text. This alignment was enabled by a network combining institutional mechanisms with two dynamics that augmented translators’ genre competence. Horizontal negotiation addressed precision problems and tacit emulation ensured conformity to English conventions. During the two-stage revision, the network was reconfigured into vertical calibration. Peer revisers operationalized latent nonhuman actors into obligatory passage points and the Translator-in-Chief mediated among competing demands and constructed new norms. Genre competence evolved from norm enforcement to register flexibility and contextual coordination. These findings suggest that effective crisis translation hinges on a network’s capacity to build, recalibrate and even override its own textual norms, offering implications for process-oriented quality assurance in crisis translation.