In the midst of a pandemic, the efficacy of official measures to mitigate the COVID-19 crisis largely depends on public attitudes towards them, where conspiracy beliefs represent potential threats to the efficacy of measures such as vaccination. Here, we present predictors and outcomes associated with a COVID-19 vaccination conspiracy belief. In a representative survey of Germany, sociodemographic predictors of this belief were found to include age, federal state, migration background and school leaving qualification. The study revealed correlations with trust in scientific and governmental information sources, respondents’ self-assessment of being informed about science, general conspiracy mindedness, the frequency of using Twitter and messaging apps, as well as willingness to voluntarily take the COVID-19 vaccine. Our results cohere with and build on the general literature on conspiracy mindedness and related factors. The findings provide an evidence base for more effective health and crisis communication in Germany and beyond.
Igneous sheet intrusions such as sills, dikes, and laccoliths are abundant in volcanic basins. Mafic intrusions are characterized by high P-wave seismic velocities in the range from 5.0 to 7.0 km/s. Velocity aureoles with a thickness comparable to the sill intrusion are commonly identified on sonic log data above and below the intrusions. Sills as thin as 10 m may be detected by conventional seismic reflection data, whereas sills with a thickness above about 40 m are resolvable. Offset-dependent tuning of sill reflections is expected due to the high velocity of the intrusions. Deep sills are difficult to image by reflection methods but can be identified from wide-angle seismic data. Sill reflections are interpreted based on characteristic features such as their high amplitudes and saucer-shaped geometries. Sill complexes are further well-suited for 3D visualization techniques. Potential field and electromagnetic data may improve the reliability of the igneous intrusion interpretation; however such data have poor resolution if sills are buried below more than a few kilometers of sediments. Andesitic and felsic intrusions and laccoliths are less abundant than sills in volcanic basins, and few well-documented geophysical interpretation studies of such intrusions or dykes are published.
A 3D CSEM survey was acquired in a frontier deepwater area in SE-Asia to provide input for portfolio ranking and risk mitigation. The interpretation process of the 3D data set was heavily driven by 3D inversion. Various 3D inversion approaches were tested and the results demonstrated the importance of including anisotropy. Interpretations based on the isotropic 3D inversion differ from the interpretation of the anisotropic result, the latter coinciding with the pre-survey geomodel. The final interpretation of the CSEM data suggested significant hydrocarbon charge to be restricted to only one-third of the original prospect area, off the crest of the structure, reducing the potential of the prospect significantly.
Contents of this paper were reviewed by the Technical Committee of the 13 th International Congress of the Brazilian Geophysical Society and do not necessarily represent any position of the SBGf, its officers or members. Electronic reproduction or storage of any part of this paper for commercial purposes without the written consent of the Brazilian Geophysical Society is prohibited.
The European Commission-funded RRING (Responsible Research and Innovation Networked Globally) Horizon 2020 project aimed to deliver activities that promoted a global understanding of Socially Responsible Research and Innovation (RRI). A necessary first step in this process was to understand how researchers (working across Global North and Global South contexts) implicitly understand and operationalise ideas relating to social responsibility within their day-to-day work. Here, we describe an empirical dataset that was gathered as part of the RRING project to investigate this topic. This Data Note explains the design and implementation of 113 structured qualitative interviews with a geographically diverse set of researchers (across 17 countries) focusing on their perspectives and experiences. Sample selection was aimed at maximising diversity. As well as spanning all five UNESCO world regions, these interview participants were drawn from a range of research fields (including energy; waste management; ICT/digital; bioeconomy) and institutional contexts (including research performing organisations; research funding organisations; industry and business; civil society organisations; policy bodies). This Data Note also indicates how and why a qualitative content analysis was implemented with this interview dataset, resulting in category counts available with the anonymised interview transcripts for public access.
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