Extreme opponents of genetically modified foods know the least but think they know the most.

There is widespread agreement among scientists that genetically modified foods are safe to consume and have the potential to provide substantial benefits to humankind. However, many people still harbour concerns about them or oppose their use. In a nationally representative sample of US adults, we find that as extremity of opposition to and concern about genetically modified foods increases, objective knowledge about science and genetics decreases, but perceived understanding of genetically modified foods increases.

An Overview of Attitudes Toward Genetically Engineered Food.

Genetically engineered food has had its DNA, RNA, or proteins manipulated by intentional human intervention. We provide an overview of the importance and regulation of genetically engineered food and lay attitudes toward it. We first discuss the pronaturalness context in the United States and Europe that preceded the appearance of genetically engineered food.

Evidence for Absolute Moral Opposition to Genetically Modified Food in the United States.

Public opposition to genetic modification (GM) technology in the food domain is widespread (Frewer et al., 2013). In a survey of U.

Asymmetrical social mach bands: exaggeration of social identities on the more esteemed side of group borders.

Perceptual processes generally enhance borders, because of their high information value. Mach bands are an example in vision. In the social world, borders are also of special significance; one side of a border is generally more esteemed or valued than the other.

Psychological strategies for winning a geopolitical forecasting tournament.

Five university-based research groups competed to recruit forecasters, elicit their predictions, and aggregate those predictions to assign the most accurate probabilities to events in a 2-year geopolitical forecasting tournament. Our group tested and found support for three psychological drivers of accuracy: training, teaming, and tracking. Probability training corrected cognitive biases, encouraged forecasters to use reference classes, and provided forecasters with heuristics, such as averaging when multiple estimates were available.