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  1. 1 Αυγ 2014 · This chapter introduces and explores views about manipulation’s nature and moral status. It begins by discussing manipulation’s current importance, given its relevance to everyday interpersonal interactions and public policy debates, its relative scholarly neglect, and our rapidly expanding power to effectively manipulate.

  2. 30 Μαρ 2018 · In the field of business ethics, much philosophical attention has been focused on the question of whether advertising is manipulative. The economist John Kenneth Galbraith famously called advertising “the manipulation of consumer desire” and compared being the target of advertising with being

  3. 3 Σεπ 2022 · Some of these characteristics, typical economic and social–political realities of many developing countries, render the study of manipulative behavior quite relevant to modern times. 6.1 (i) Humanistic psychology perspective: The mission of manipulating and influencing others may not always succeed. Often manipulative tricks in social ...

  4. 25 Μαΐ 2017 · The economic and psychological forces that perpetuate inequality continue to be studied, and in this theoretical review, we examine the role of daily experiences of economic inequality—the communication of social class signals between interaction partners—in this process.

  5. Consider a politician intentionally spreading false information in order to improve her chances of winning an election – perhaps malicious rumours about opposition candidates, fabricated statistics supporting the incumbents’ policy agenda, or claims of electoral fraud to discredit election results.

  6. We consider a social learning model where agents learn about an underlying state of the world from individual observations as well as from exchanging information with each other. A principal (e.g. a firm or a government) interferes with the learning process in order to manipulate the beliefs of the agents.

  7. 28 Φεβ 2018 · When the responses to these questions were factor analysed, Easterbrook and colleagues found three factors that were common to the two datasets: SES-based identities (e.g., income), basic-demographic identities (e.g., age), and identities based on sociocultural orientation (e.g., ethnic background).

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