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The Paradox of Abstraction: Precision Versus Concreteness

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Abstract

We introduce a novel measure of abstractness based on the amount of information of a concept computed from its position in a semantic taxonomy. We refer to this measure as precision. We propose two alternative ways to measure precision, one based on the path length from a concept to the root of the taxonomic tree, and another one based on the number of direct and indirect descendants. Since more information implies greater processing load, we hypothesize that nouns higher in precision will have a processing disadvantage in a lexical decision task. We contrast precision to concreteness, a common measure of abstractness based on the proportion of sensory-based information associated with a concept. Since concreteness facilitates cognitive processing, we predict that while both concreteness and precision are measures of abstractness, they will have opposite effects on performance. In two studies we found empirical support for our hypothesis. Precision and concreteness had opposite effects on latency and accuracy in a lexical decision task, and these opposite effects were observable while controlling for word length, word frequency, affective content and semantic diversity. Our results support the view that concepts organization includes amodal semantic structures which are independent of sensory information. They also suggest that we should distinguish between sensory-based and amount-of-information-based abstractness.

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Notes

  1. We chose the term precision rather than the terms inclusiveness, generality or specificity because it more closely reflects the notion of amount of information in a hierarchical system.

  2. It is also important to note that precision is not limited to category structure and is relevant to any variable defined in terms of inclusiveness. As reviewed in Burgoon et al. (2013); Vallacher and Wegner (1987) defined abstraction in terms of comprehensiveness, Semin and Fiedler (1991) in terms of enduring qualities, and Watkins et al. (2008) in terms of essential gists and invariance. In this sense, precision can also refer to spatio-temporal inclusiveness, but we do not address this aspect here.

  3. Each additional level of precision can be seen as adding new sub-partitions to a set, and it is easy to show that the amount of information gained from knowing to which sub-partition an element belongs, increases with the number of sub-partitions (cf. Meilă 2007).

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Acknowledgements

We are grateful to Doug Medin, Scott Atran, David Balota, Victor Kuperman, Bryor Snefjella, Dermot Lynott, Anastasia Smirnova, and Nadiya Kostyuk for helpful comments and suggestions. This work was supported by Air Force Office of Scientific Research Grant FA9550-10-1-0373.

Author’s contribution RI and RA developed the theoretical framework. RI assembled the database and conducted the statistical analyses. RI and RA interpreted the results and prepared the manuscript. Both authors approved the final version of the manuscript for submission.

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  1. Rumen Iliev

    Present address: Stanford University, Stanford, CA, USA

Authors and Affiliations

  1. Gerald R. Ford School of Public Policy, University Of Michigan, Ann Arbor, MI, USA

    Rumen Iliev & Robert Axelrod

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  1. Rumen Iliev
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Correspondence to Rumen Iliev.

Appendix

Appendix

See Table 3.

Table 3 Zero-order correlations of all variables from Studies 1 and 2
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Iliev, R., Axelrod, R. The Paradox of Abstraction: Precision Versus Concreteness. J Psycholinguist Res 46, 715–729 (2017). https://doi.org/10.1007/s10936-016-9459-6

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