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Manifest functions are the consequences that people see, observe or even expect. It is explicitly stated and understood by the participants in the relevant action. The manifest function of a rain dance, according to Merton in his 1957 Social Theory and Social Structure, is to produce rain, and this outcome is intended and desired by people participating in the ritual.
His example from his 1949 piece, "Manifest and Latent Functions", was an analysis of political machines. Manifest and latent functions were devised to prelude the inadvertent confusion between conscious motivations for social behavior and its objective consequences. [ 27 ]
He is best recognised for his work on gambling and game addiction where, for example, he explores how people from different ages are drawn to gambling. For example, he has reported that demo versions and online "skill schools" where players gamble with points rather than money appeal more to teenagers than adults. [ 9 ]
The task was originally presented simply as the Gambling Task, or the "OGT". Later, it has been referred to as the Iowa gambling task and, less frequently, as Bechara's Gambling Task. [4] The Iowa gambling task is widely used in research of cognition and emotion. A recent review listed more than 400 papers that made use of this paradigm. [5]
Most theoretical analyses of risky choices depict each option as a gamble that can yield various outcomes with different probabilities. [2] Widely accepted risk-aversion theories, including Expected Utility Theory (EUT) and Prospect Theory (PT), arrive at risk aversion only indirectly, as a side effect of how outcomes are valued or how probabilities are judged. [3]
Many observable variables can be aggregated in a model to represent an underlying concept, making it easier to understand the data. In this sense, they serve a function similar to that of scientific theories. At the same time, latent variables link observable "sub-symbolic" data in the real world to symbolic data in the modeled world.
A latent variable model is a statistical model that relates a set of observable variables (also called manifest variables or indicators) [1] to a set of latent variables. Latent variable models are applied across a wide range of fields such as biology, computer science, and social science. [ 2 ]
Example of the optimal Kelly betting fraction, versus expected return of other fractional bets. In probability theory, the Kelly criterion (or Kelly strategy or Kelly bet) is a formula for sizing a sequence of bets by maximizing the long-term expected value of the logarithm of wealth, which is equivalent to maximizing the long-term expected geometric growth rate.