Results 251 to 260 of about 19,140 (303)
Journal of Linguistic Anthropology, Volume 36, Issue 1, May 2026.Abstract This paper asks how LLM‐based systems can produce text that is taken as contextually appropriate by humans without having seen text in its broader context. To understand how this is possible, context and co‐text have to be distinguished. Co‐text is input to LLMs during training and at inference as well as the primary resource of sense‐making ...
Ole Pütz
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Nonhuman situational enmeshments—How participants build temporal infrastructures for ChatGPT
Journal of Linguistic Anthropology, Volume 36, Issue 1, May 2026.Abstract This paper investigates how participants recruit Large Language Models (LLMs) like ChatGPT as interactional co‐participants depending on their temporal enmeshment within an interactional flow. Using Charles Goodwin's co‐operative action framework, we analyze video data of human–AI interaction to trace the temporal structures established by ...
Nils Klowait, Maria Erofeeva
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Things at Work: How Things Contribute to Performing Work
Journal of Management Studies, Volume 63, Issue 3, Page 1155-1191, May 2026.Abstract A crucial question for organizations is what constitutes work performance. While the importance of human competence and motivation to work performance has been established, less well understood is how ‘things’ – such as algorithms, tools, instruments, and raw materials – contribute to work performance.
Jörgen Sandberg +2 more
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Diagnostic and Prognostic Values of Bile Biomarkers for Malignant Biliary Stenosis
Liver International, Volume 46, Issue 5, May 2026.ABSTRACT Introduction Differentiating between malignant and benign biliary strictures remains a clinical challenge because current diagnostic tools have limited sensitivity. The detection of tumour‐related biomarkers directly in bile, which is in close contact with the lesion, may enhance diagnostic accuracy.
E. Gigante +9 more
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Medical Education, Volume 60, Issue 5, Page 492-504, May 2026.Abstract With the increasing adoption of artificial intelligence (AI), health care systems and medical education are undergoing significant changes. This review examines how medical students and faculty members perceive the opportunities and challenges of AI integration in both health care practice and medical curricula.
See Chai Carol Chan +2 more
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