Advisor(s)

John D. Coley

Contributor(s)

Nancy S. Kim, Neal J. Pearlmutter, Adam J. Reeves

Date of Award

2011

Date Accepted

2011

Degree Grantor

Northeastern University

Degree Level

Ph.D.

Degree Name

Doctor of Philosophy

Department or Academic Unit

College of Science. Department of Psychology.

Keywords

explanation, hypothesis generation, inductive inference, inductive selectivity, knowledge retrieval, property effects

Disciplines

Cognitive Psychology | Psychology

Abstract

This project examined how people generate inductive inferences – probabilistic hypotheses rendered plausible by the given evidence but not guaranteed by it. The hypotheses people generate are often fine-tuned to specific features of the problem. For example, when one is asked to project a property from a known case to unknown – e.g., given that ducks have gene X, what else is likely to share the gene? – the nature of the projected property can have a profound effect on the generated hypotheses. Intrinsic properties, such as having a gene, tend to be projected to members of the same class – sparrows, other birds. Contextual, or environmentally-transmitted properties, such as having a parasite – tend to be projected to entities that interact or co-occur with the known case – otters, other aquatic animals; predators of ducks. Such changes in inductive inferences based on the projected property – “property effects” - are ubiquitous in induction, but the theoretical accounts of induction capable of addressing the underlying psychological mechanism are lacking.

To address this gap, I proposed a simple two-component model of inductive inference, consisting of retrieval of knowledge about the premise category (duck) and property (gene), and generation of an inductive hypothesis. I hypothesized that property effects stem from selective retrieval of knowledge about premise categories in the context of different properties. One set of results suggested that the knowledge about premise category and property is combined interactively in order to form an inductive hypothesis: the relationship between participants’ knowledge about animals and the inferences they generated about these animals varied depending on the property. For example, salient ecological knowledge about animals promoted ecological inferences about them (projections of property to ecologically related species), but only when participants were reasoning about a contextual property. Likewise, salient categorical knowledge about animals suppressed ecological inferences, but only when participants were reasoning about intrinsic properties. However, a study examining the time course of early knowledge activation in the context of inductive inference found no evidence for interactive retrieval: despite systematic differences in the use of knowledge in inferences, the activation of knowledge about the premise category was not affected by the property.

These results suggest that premise category and property knowledge are combined interactively, but not during retrieval. Because these results were not compatible with the proposed retrieval-based model of property effects, they required a revision of the model. The revised proposal introduced explanation of the evidence to the model. On this account, inference generation involves first, explaining the evidence provided by the premise (the combination of premise category and the property) by identifying a larger regularity that it belongs to, and second, formulating a guess about other entities that might share the property by virtue of belonging to same regularity. Within this account, different properties can affect inferences by triggering different types of explanations – formal, based on category membership, or causal, based on a sequence of enabling events, or teleological, based on ends and goals. Different explanations, or identifying an observation as a part of different types of regularities can in turn lead to different generalization hypotheses. Preliminary examination of explanations for premise information that participants spontaneously generated during the inference-generation task showed that the dominant type of explanation indeed varied with the property participants were reasoning about, providing the first support for the explanation-based account of property effects.

In sum, this project was the first to examine the processing details of property-sensitive induction. It contributed towards understanding the mechanism of property effects in induction in two ways. First, it suggested how property effects do not work, by demonstrating that property does not influence retrieval of knowledge about premise categories. Second, it introduced property-driven explanations as a possible source of property effects and provided preliminary evidence for this proposal, opening up a new promising line of research.

Document Type

Dissertation

Rights Holder

Nadezda Vasilyeva


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