The roles of independent and correlated properties in real world object concepts were explored. Property norms were collected for 190 natural kinds and artifacts. The norms were used to design behavioral experiments and computational models of concept similarity. Property intercorrelations influenced performance in property verification. Concept similarity, as measured by overlap of independent properties, predicted similarity ratings, speeded same/different category decision latency, and short interval priming latency. Concept similarity, as measured by overlap of correlated properties, predicted same/different category decision latency and short interval priming for natural kinds. It was concluded that people encode knowledge about independent and correlated properties of real-world objects. The influence of property intercorrelations is stronger for natural kinds because natural kinds contain a higher proportion of correlated properties. In the investigation of short interval semantic priming, results suggested that semantic relatedness can be defined in terms of property overlap between concepts.

This thesis examines property generalization among concepts. Its primary objective is to investigate the hypothesis that the more central a feature for a concept, the higher its generalizability to other concepts that share a similar structure (features and dependencies). Its secondary objectives are to examine the relative contributions of feature centrality and feature variability in property induction, whether centrality offers a domain-general or a domain-specific constraint, and whether centrality can operate under conditions of vagueness. Experiments 1 and 2 addressed the centrality hypothesis with centrality measured, whereas Experiments 3 to 14 and 17 with centrality manipulated. Relative feature centrality was manipulated as follows: from a single-dependency chain (Experiments 3 to 7), from the number of properties that depended upon a feature (Experiments 8 to 11 and 17), and from the centrality of the properties that depended upon the critical features (Experiments 12 to 14). The results support the centrality hypothesis. Experiments 12 to 16 addressed the relative contributions of centrality and variability in property induction. Experiments 12 to 14 pitted a central and variable property against a less central and less variable property in judgments of frequency and inductive strength. The results suggest that property induction depends on centrality rather than frequency information, and that centrality can bias the perception of frequency (although the latter results were not clear-cut). Experiments 15 and 16 pitted centrality against variability in information seeking. The results show that centrality information is sought more often than variability information to make an inference, especially amongst dissimilar concepts. Experiments 1 to 16 used animal categories. Experiment 17 examined the centrality hypothesis with artifact categories. The results show centrality effects. Taken together, the Experiments suggest that centrality offers a domain-general constraint. Experiments 5, 8 to 11, and 17 left the properties that depended upon a candidate feature unspecified. A centrality effect was still obtained. The results suggest that centrality can operate under conditions of vagueness. The results are discussed in terms of theories of conceptual structure and models of category-based inference. A model to capture the present findings is also sketched.

Thesis (M.A.)--York University, 2006. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves 73-78). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR19739

Thesis (M. S. in Psychology)--Vanderbilt University, Dec. 2008. / Title from title screen. Includes bibliographical references.

Thesis (Ph. D.)--UCLA, 2007. / Vita. Includes bibliographical references (leaves 88-97).

Thesis (Ph. D.)--Lehigh University, 1999. / Includes vita. Includes bibliographical references (leaves 147-149).

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (M. Phil.)--University of Hong Kong, 2000. / Includes bibliographical references (leaves 60-72).

Thesis (Ph. D.) -- University of Alberta, 2010. / "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Department of Psychology, University of Alberta." Title from pdf file main screen (viewed on November 23, 2009). Includes bibliographical references.

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