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priming |
any experiences or procedures that bring a particular concept to mind |
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Classical view |
concepts may be defined by a set of necessary and sufficient attributes; ex: one may be considered a student only if they have all of the attributes and anyone who has all of them is a student |
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problems with the classical view |
1) difficulty in specifying defining features (not all games have a winner but this is a major aspect of a game-should it be a defining feature?)
2) members vary in their typicality: some members are better examples of the concept than others (a robin is a better example of a bird than an emu)
3) unclear cases: e.g. is a blackboard furniture? |
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Probabilistic view |
a category can be described by a list of features that are typical of it, yet do not define it (ex: birds typically fly but a chicken qualifies as a bird even though it doesn’t) |
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family resemblance |
family members can share various features but they do not all have to have them to be a member of the family; and some show them more than others |
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2 different ways of conceptualizing categories within the probabilistic view |
prototype view, exemplar view |
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prototype view |
people possess summary representations of categories, called prototypes (an abstracted list of features that are typical of category members). To determine whether something is a member of a category, one compares it to this prototype |
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exemplar view |
categories are represented as sets of examples that one has encountered; category of a bird is represented as a wren, a pigeon, a chicken, etc. To determine whether something is a member of a category, one compares it to the other members |
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Representativeness heuristic |
we categorize objects based on their similarity to the group; ex: if Susan seems similar to our stereotype of a democrat, we’ll classify her as a democrat |
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Ignoring Prior Probabilities of Outcomes (Base Rates) |
classifying something as belonging to a group based on its similar traits to the group but ignoring the probability of that outcome; ex: assuming that Bob is a classics scholar rather than a farmer because he loves poetry and museums, when farmers are much more common than classics scholars so he is more likely to be a farmer |
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Covariation model of attribution |
provides guidelines for what caused an effect; we should take 3 things into account: 1) distinctiveness: does the effect occur only in the presence of any one possible cause? 2)consistency: does the effect occur repeatedly in the presence of the possible cause? 3) consensus: does everyone respond in the same way to this possible cause? |
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Stereotypes as Base-Rates |
like the common belief that men are more assertive than women; people use these stereotypes as base-rates the same way they use actual base-rates: use them to make judgments about a person when they have no info about the person but ignore them when they have even a little info on the person |
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The Dilution Effect |
refers to when you get more info on the individual you will rely less on the stereotypes, even if it’s irrelevant info |
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Ignoring sample size |
small samples are far more likely to stray from the overall pop. mean than are large samples but we ignore this |
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Belief in the Hot Hand |
belief that someone does better after they have just had a success |
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Conjunction fallacy |
failure to recognize that the probability of a conjunction of 2 events is less likely than the probability of one event occurring (ex: the probability that Linda is a bank teller is more likely than the probability that she is a bank teller and a feminist) |
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Availability heuristic |
we base our idea of how frequently something occurs on how readily we can recall examples of it occurring |
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Salience |
prominence; how much one stands out (the only black person in a room or the person we are facing); focusing our attention on a given individual will lead us to notice and recall more of their contributions and thus view them as being more influential |
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Egocentric biases |
the tendency to assume that one has contributed more than their fair share to joint endeavors |
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Ignoring biases in accessible cognitions |
even if the total pool of examples that we have at our disposal is unbiased, the availability heuristic could still lead us to bias if we temporarily bring to mind only a biased subset of the total pool…several factors lead us to do so |
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One-sided questions |
increasing the availability of a biased set of one’s self-knowledge through one-sided questions can affect their self-conception; for example, asking someone about their shyness will cause them to bring only instances of times they acted shy to mind, and not instances of times they acted shy and times they acted outgoing to mind which would be the full sample |
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