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Abstract

Das erste durch KI verfasste Weisheitsbuch. »Die Künstliche Intelligenz sieht den Menschen, wie er ist. Es gibt für sie keinen Gott, keine Rituale, keinen Himmel, keine Hölle, keine Engel. Es gibt für sie nur empfindsame Wesen.« GPT-3. Dieses Buch enthält Weisheitstexte, die durch die modernste KI im Bereich der Spracherkennung verfasst wurden. Es ist die GPT-3, die durch die Technikerin Jasmine Wang gesteuert wird. Die originären Texte von GPT-3 werden von dem international bekannten Dichter Iain S. Thomas kuratiert. Die Basis von GPT-3 reicht von den Weisheitsbücher der Menschheit bis hin zu modernen Texten. GPT-3 antwortet auf Fragen wie: Was macht den Mensch zum Menschen? Was bedeutet es zu lieben? Wie führen wir ein erfülltes Leben? etc. und ist in der Lage, eigene Sätze zu kreieren. So wird eine zeitgenössische und noch nie dagewesene Erforschung von Sinn und Spiritualität geschaffen, die zu einem neuen Verständnis dessen inspiriert, was uns zu Menschen macht.

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Abstract

Journal lists are instruments to categorize, compare, and assess research and scholarly publications. Our study investigates the remarkable proliferation of such journal lists in China, analyses their underlying values, quality criteria and ranking principles, and specifies how concerns specific to the Chinese research policy and publishing system inform these lists. Discouraged lists of "bad journals" reflect concerns over inferior research publications, but also the involved drain on public resources. Endorsed lists of "good journals" are based on criteria valued in research policy, reflecting the distinctive administrative logic of state-led Chinese research and publishing policy, ascribing worth to scientific journals for its specific national and institutional needs. In this regard, the criteria used for journal list construction are contextual and reflect the challenges of public resource allocation in a market-led publication system. Chinese journal lists therefore reflect research policy changes, such as a shift away from output-dominated research evaluation, the specific concerns about research misconduct, and balancing national research needs against international standards, resulting in distinctly Chinese quality criteria. However, contrasting concerns and inaccuracies lead to contradictions in the "qualify" and "disqualify" binary logic and demonstrate inherent tensions and limitations in journal lists as policy tools.

Date

22. 9.2023 16:39:23

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Abstract

Knowledge order in an online knowledge community (OKC) refers to a consensual version of collective knowledge in the creation of shared knowledge representation. Much previous research has been conducted in the context of the ordered structure of objective knowledge systems, but this does little to explain the microlevel order of knowledge after users contribute knowledge and achieve consensus through online interactions in OKC. Based on interactive team cognition theory and the stigmergy coordination mechanism, our research aims to investigate how knowledge and experience heterogeneity affect knowledge order effectiveness and efficiency through collaborative and communicative interaction. To test our hypotheses, we randomly collected the records of 250 articles from the English version of Wikipedia. Partial least squares structural equation modeling indicated that OKC favoring online collective knowledge order by limiting communicative interaction, as collaborative interaction is very effective in achieving knowledge order and in achieving it in a fast way. From our findings, scholars and practitioners are advised to pay attention to online knowledge order in the management and design of OKC.

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Abstract

Public health surveillance based on data analytics plays a crucial role in detecting and responding to public health crises, such as infectious disease outbreaks. Previous information science research on the topic has focused on developing analytical algorithms and visualization tools. This study seeks to extend the research by investigating information practices in data analytics for public health surveillance. Through a case study of how data analytics was conducted for surveilling Influenza A and COVID-19 outbreaks, both exploration information practices (i.e., probing, synthesizing, exchanging) and exploitation information practices (i.e., scavenging, adapting, outreaching) were identified and detailed. These findings enrich our empirical understanding of how data analytics can be implemented to support public health surveillance.