Oct 2026· Energy Research & Social Science· 51 references
Sustainability and Climate Change Governance
Abstract
Promotional language in scientific and institutional documents is usually dismissed as individual failing or passing fashion. Using Bourdieu's field theory, the Sociology of Expectations and Bacchi's problem representation, we argue instead that it reflects scientific documents' structural position and institutional documents' functional mandate in governance. First, an expert-calibrated Large Language Model scores eight promotional dimensions across 268 natural hydrogen documents (1987-mid-2025). Hype, defined as evidential disproportion rather than forward-looking language, occupies the top two of five levels, whereas the models cover the full scale. Two metrics computed on each document's references translate Bourdieu's field theory into network terms, and both behave as it expects. Low out-closeness centrality, the strongest correlate, places those references at the margins of the field. A high hub score shows reliance on canonical authorities, whose symbolic capital the document borrows. Others are high novelty, absent direct measurements, hydrocarbon-system analogies, lower-prestige journals and a techno-economic or environmental focus, together explaining a third of the variance. The register rises as newcomers enter peripheral positions. Second, discourse analysis of 22 institutional documents (2021–2026) shows that register follows mandate. Enactors amplify expectations and Selectors temper them, as in the Sociology of Expectations. Hybrids, the role added here, write expectations into legal categories, funding calls and research agendas with a moderate register. Written into rules, unverified expectations act through procedure, not persuasion. Amplifying texts recur and push caveats to the margins, while tempering texts appear once. This imbalance in information, a constitutive element of procedural energy justice, precedes any participatory process.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
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A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.