Framing Climate Uncertainty: Frame Choices Reveal and Influence Climate Change Beliefs

The public debate around climate change is increasingly polarized. At the same time, the scientific consensus about the causes and consequences of climate change is strong. This inconsistency poses challenges for mitigation and adaptation efforts. The translation of uncertain numerical climate projections into simpler but ambiguous verbal frames may contribute to this polarization. In two experimental studies, we investigated 1) how “communicators” verbally frame a confidence interval regarding projected change in winter precipitation due to climate change (N = 512) and 2) how “listeners” interpret these verbal frames (N = 385). Both studies were preregistered at the Open Science Framework. Communicators who perceived the change as more severe chose a concerned rather than an unconcerned verbal frame. Furthermore, communicators’ verbal frames were associated with their more general beliefs, like political affiliation and environmental values. Listeners exposed to the concerned frame perceived climate change–induced precipitation change to be more severe than those receiving the unconcerned frame. These results are in line with two pilot studies (N = 298 and N = 393, respectively). Underlying general beliefs about climate and the environment likely shape public communication about climate in subtle ways, and thus verbal framing by the media, policymakers, and peers may contribute to public polarization on climate change

The four weeks before lockdown during the COVID-19 pandemic in Germany: A weekly serial cross-sectional survey on risk perceptions, knowledge, public trust and behaviour, 3 to 25 March 2020

Background: During the COVID-19 pandemic, public perceptions and behaviours have had to adapt rapidly to new risk scenarios and radical behavioural restrictions. Aim: To identify major drivers of acceptance of protective behaviours during the 4-week transition from virtually no COVID-19 cases to the nationwide lockdown in Germany (3–25 March 2020). Methods: A serial cross-sectional online survey was administered weekly to ca 1,000 unique individuals for four data collection rounds in March 2020 using non-probability quota samples, representative of the German adult population between 18 and 74 years in terms of age × sex and federal state (n = 3,910). Acceptance of restrictions was regressed on sociodemographic variables, time and psychological variables, e.g. trust, risk perceptions, self-efficacy. Extraction of homogenous clusters was based on knowledge and behaviour. Results: Acceptance of restrictive policies increased with participants’ age and employment in the healthcare sector; cognitive and particularly affective risk perceptions were further significant predictors. Acceptance increased over time, as trust in institutions became more relevant and trust in media became less relevant. The cluster analysis further indicated that having a higher education increased the gap between knowledge and behaviour. Trust in institutions was related to conversion of knowledge into action. Conclusion: Identifying relevant principles that increase acceptance will remain crucial to the development of strategies that help adjust behaviour to control the pandemic, possibly for years to come. Based on our findings, we provide operational recommendations for health authorities regarding data collection, health communication and outreach

Collective Animal Behavior from Bayesian Estimation and Probability Matching

Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is based on empirical fits to observations and we lack first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching.
In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability given by the Bayesian estimation that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior

Reasoning with heuristics

Which rules should guide our reasoning? Human reasoners often use reasoning shortcuts, called heuristics, which function well in some contexts but lack the universality of reasoning rules like deductive implication or inference to the best explanation. Does it follow that human reasoning is hopelessly irrational? I argue: no. Heuristic reasoning often represents human reasoners reaching a local rational maximum, reasoning more accurately than if they try to implement more “ideal” rules of reasoning. I argue this is a genuine rational achievement. Our ideal rational advisors would advise us to reason with heuristic rules, not more complicated ideal rules. I argue we do not need a radical new account of epistemic norms to make sense of the success of heuristic reasoning

CP Violation in Tau Slepton Pair Production at Muon Colliders

We discuss in detail signals for CP violation in the Higgs boson and tau-slepton sectors through the production processes $\mu^+\mu^- \to \tilde{\tau}_i^- \tilde{\tau}_j^+$, where $i,j=1,2$ label the two $\tau$ slepton mass eigenstates in the minimal supersymmetric standard model. We assume that the soft breaking parameters of third generation sfermions contain CP violating phases, which induce CP violation in the Higgs sector through quantum corrections. We classify all the observables for probing CP violation in the Higgs boson and $\tau$ slepton sectors. These observables depend on the initial muon beam polarization, where we include transverse polarization states. If the heavy Higgs bosons can decay into tau slepton pairs, a complete determination of the CP properties of the neutral Higgs boson and $\tau$--slepton systems is possible. The interference between the Higgs boson and gauge boson contributions could also provide a powerful method for probing CP violation, if transversely polarized muon beams are available. We show in detail how to directly measure CP violation in the tau slepton system, under the assumption that the neutral Higgs mixing angles are determined through the on--shell production of the neutral Higgs bosons.Comment: 38 pages, 9 figures Including 7 eps ones. A figure to show the dependence on tan(beta) and the mass parameters of the sfermion sectors and a reference added. To appear in Phys. Rev.