Category-based induction.

Abstract

An argument is categorical if its premises and conclusion are of the form All members ofC have property F, where C is a natural category like FALCON or BIRD, and P remains the same across premises and conclusion. An example is Grizzly bears love onions. Therefore, all bears love onions. Such an argument is psychologically strong to the extent that belief in its premises engenders belief in its conclusion. A subclass of categorical arguments is examined, and the following hypothesis is advanced: The strength of a categorical argument increases with (a) the degree to which the premise categories are similar to the conclusion category and (b) the degree to which the premise categories are similar to members of the lowest level category that includes both the premise and the conclusion categories. A model based on this hypothesis accounts for 13 qualitative phenomena and the quantitative results of several experiments.

Fear Generalization in Humans: Systematic Review and Implications for Anxiety Disorder Research

“…Another area of insight into the complexity of human fear and anxiety is category-based induction (Osherson, Smith, Wilkie, Lopez, & Shafir, 1990), which investigates factors that promote the generalizability of information at the category level. Examples include arguments of the nature mice have sesamoid bones [premise] therefore horses have sesamoid bones [conclusion].…”

“…representative (or atypical) of their category (Osherson et al, 1990). The example argument concerning mice and horses, for instance, would be considered strong because the premise exemplar is typical of its category (e.g., mammal).…”

“…For example, the argument bats have sesamoid bones therefore mice have sesamoid bones is considered weaker than the argument mice have sesamoid bones therefore bats have sesamoid bones, even though the premise and conclusion exemplars are from the same category (mammals). This effect is referred to as premise-conclusion asymmetry, and provides evidence that typical exemplars provide better sources of generalization than atypical exemplars (Osherson, et al, 1990;Rips, 1975). Dunsmoor and Murphy (2014) adopted the framework of category-based induction to investigate whether typicality effects apply to generalization of conditioned SCRs in humans.…”

Statistical judgments are influenced by the implied likelihood that samples represent the same population

“…For example, infants' inferences are affected by whether samples are shown to be randomly or nonrandomly selected (Xu & Denison, 2009), and they can detect that samples are unrepresentative of a known population, even when sampling method is hidden (Kushnir, Xu & Wellman, 2010). Furthermore, children are more likely to generalize attributes from samples to general populations when given diverse samples that are (presumably) more representative of a general population rather than homogeneous samples, which could represent a particular subpopulation (Rhodes, Brickman & Gelman, 2008; see also Osherson, Smith, Wilkie, Lopez & Shafir, 1990).…”

Induction and knowledge-what

“…In contrast to the sentential approach to induction in philosophy, there exist in psychology an active research programme dealing with 'category-based induction' (Osherson et al 1990;Hayes et al 2010;Fisher et al 2015). Within this programme, the stimuli almost exclusively consist of generic sentences that, according to our classification, express knowledge-what.…”