Dave Kinkead

A stable democracy requires a shared identity and political culture. Its citizens need to identify as one common demos lest it fracture and balkanise into separate political communities. This in turn necessitates some common communication network for political messages to be transmitted, understood and evaluated by citizens. Hence, what demarcates one demos from another are the means of communication connecting the citizens of those demoi, allowing them to debate and persuade each other on the proper conduct of government and on issues of common interest. For the ancient Athenians, their public sphere was the agora (marketplace); for the Federalists in the American colonies, the newspaper; for us today, it is the Internet. Until now, the physical nature of these communication networks has resulted in a trade-off between the reach of political messages (the numeric and geographic composition of the demos who receive political messages and may participate in the public sphere) and the ability to target the content of a message on that network towards individual citizens. One-to-one interpersonal conversation in the agora was highly targeted but could reach only as far as a voice could carry. The speakers and audience were well known to each other through personal interaction. As the printing press and later television allowed for greater and greater reach, the content of these messages became more generic as the speakers became more distant from their audience. The wider the audience grew, the less a message could be targeted at a particular audience segment without alienating others.

The principle of the common cause demands that every pair of causally independent but statistically correlated events should be the effect of a common cause. This demand is often supplemented with the requirement that said cause should screen-off the two events from each other. This paper introduces a new probabilistic model for common causes, which generalises this requirement to include sets of distinct but non-disjoint causes. It is demonstrated that the model hereby proposed satisfies the explanatory function generally attributed to common causes and an existential proof is offered. Finally, the model is compared to other known structures intended to perform a similar function, such as Reichenbachian Common Cause Systems and Bayesian Networks.

Reasons.js is an open-source, loosely-coupled, web-based argument mapping library that can be integrated into a range of online coursewares and websites. The javascript library can be embedded into any HTML page and allows users to create, edit, share, and export argument maps . The API is designed to permit the integration of the three stages of informal logical analysis — identification of truth claims within arguments, the analysis of logical structure, and synthesis of logical structure into written form

Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively neutralize the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking.