The authors find that consumers prefer a bonus pack to a price discount for virtue foods but they prefer a price discount to a bonus pack for vice foods. Prior research has shown that, all else being equal, consumers prefer bonus packs to price discounts. The authors propose that this preference does not hold for vice food, because consumers cannot generate good justifications for buying such food when a bonus pack is offered because this would mean consuming more of the vice. However, a price discount on a vice food can be justified because it acts as a guilt-mitigating mechanism. For virtue foods, the absence of both anticipated postconsumption guilt and the resultant need to justify leads consumers to prefer a bonus pack to a price discount. The authors demonstrate the proposed effect and test its underlying process across five experiments. (print), 1547-7193 (electronic) 1961. Price discount: control (M = 4.10)

The authors would like to acknowledge the helpful comments made by Joseph Priester and Arul Mishra on earlier versions of the manuscript. They would also like to thank Baba Shiv and Irwin Levin for helpful comments on an earlier version of the manuscript. The authors would also like to acknowledge the guidance and helpful comments of the editor, the associate editor, and the three reviewers on earlier versions of the manuscript.

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Language provides an ever-present context for our cognitions and has the ability to shape them.Languages across the world can be gendered (language in which the form of noun, verb, or pronoun is presented as female or male) versus genderless. In an ongoing debate, one stream of research suggests that gendered languages are more likely to display gender prejudice than genderless languages. However, another stream of research suggests that language does not have the ability to shape gender prejudice. In this research, we contribute to the debate by using a Natural Language Processing (NLP) method which captures the meaning of a word from the context in which it occurs. Using text data from Wikipedia and the Common Crawl project (which contains text from billions of publicly facing websites) across 45 world languages, covering the majority of the world's population, we test for gender prejudice in gendered and genderless languages. We find that gender prejudice occurs more in gendered rather than genderless languages. Moreover, we examine whether genderedness of language influences the stereotypic dimensions of warmth and competence utilizing the same NLP method.