In Crisis, Europeans Support Radical Positions Climate Change and Social Welfare issues most salient. BertelsmannStiftung eupinions brief | May 2020

Europe finds itself in an unprecedented crisis which is pushing many of its citizens into existential uncertainty. Our EU-wide poll, conducted in March 2020, as the corona virus was spreading across the continent, shows Europeans embracing some radical positions

Embracing uncertainty: diplomacy and disruption

Authority hates uncertainty. Big business and government feel safest when life is predictable and stable. Change implies a risk that your grip on power will be weakened. And unexpected change is the worst kind of all. But if uncertainty is permanent, can systems adapt

Embracing uncertainty in multi-step inference

This dissertation focuses on embracing the uncertainty that is associated with multi-step inference. Typically, statistical analyses consist of multiple steps that build on each other and are executed sequentially. Common practice is that each consecutive step ignores the uncertainty of the preceding steps. Throughout this dissertation, it is shown that not embracing uncertainty leads to overconfidence and biased conclusions. Furthermore, I have demonstrated that this uncertainty can be accounted for by averaging across models or by performing the steps that involve uncertainty simultaneously in a single model. For example, instead of averaging the scores from repeated measurements and then analyzing the averages, it is better to directly analyze the unaggregated data. These situations occur with scores given to patients by different raters, as in Chapters 3 and 4, but also with repeated measures ANOVA, as illustrated in Chapters 9 and 10. The discussion suggests several ideas for making the adoption of methods that appropriately account for uncertainty more easily accessible and more standardized. Overall, my hope with this dissertation is that the practice of ignoring uncertainty by tying together several inferential steps becomes a relic of the past and that future studies embrace the uncertainty in the individual steps by adopting multi-model inference

The social, political and legal aspects of Text and Data Mining (TDM)

The ideas of textual or data mining (TDM) and subsequent analysis go back hundreds if not thousands of years. Originally carried out manually, textual and data analysis has long been a tool which has enabled new insights to be drawn from text corpora. However, for the potential benefits of TDM to be unlocked, a number of non-technological barriers need to be overcome. These include legal uncertainty resulting from complicated copyright, database rights and licensing, the fact that some publishers are not currently embracing the opportunities TDM offers the academic community, and a lack of awareness of TDM among many academics, alongside a skills gap