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Mixed evidence for a richness-of-encoding account of animacy effects in memory from the generation-of-ideas paradigm

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Abstract

Animacy effects in memory correspond to the observation that animates (e.g., cow) are remembered better than inanimates (e.g., pencil). Although the ultimate explanation of these effects seems to be well-documented, clear evidence that would support one or other of the proximate explanations of animacy effects has proven difficult to obtain. Here, we focused on the richness-of-encoding account of animacy effects in memory, which assumes that animates are recalled better than inanimates because the former are encoded with many more distinct associations with other items (i.e., richer memory traces) than the latter. Our goal was to provide further evidence for this account by replicating and extending the analyses of Meinhardt, Bell, Buchner, and Röer (2020) showing that more ideas are generated in response to animate than inanimate words and, importantly, that this generation process mediates the better recall of animates over inanimates. In line with the richness-of-encoding account, we successfully replicated the finding that more ideas were produced in response to animates than inanimates. Even though there is some evidence that the generation of ideas mediates animacy effects in memory, we also report findings from reanalyses of previous studies (Bonin et al., Experimental Psychology, 62, 371–384, Bonin et al., 2015; Gelin et al., Memory, 25, 2–18, Gelin et al., 2017; Gelin et al., Memory, 27, 209–223, Gelin et al., 2019) which—although supporting mediation—show that the number of ideas generated in response to animate and inanimate words cannot reliably predict memory of these words when they are learned in different encoding contexts.

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Notes

  1. A common practice is to base the decision on p-values obtained in bilateral tests. When parameter estimations agree with unilateral hypotheses, the associated unilateral p-values are equal to bilateral ones divided by two. Reasoning on the basis of unilateral tests makes it possible to get more powerful tests.

  2. The number of ideas given by the participants was used as a proxy for the number of ideas per item.

  3. Testing this aspect is equivalent to testing an effect of the mediator when controlling for the two conditions of the independent variable. This is necessary in order to evaluate the validity of step 3 of the mediation procedure originally proposed by Judd et al. (2001) (see Montoya & Hayes, 2017).

  4. For the current experiment, the animacy effect was also significant at .05 in the by-items analysis (p = 0361; d = .84).

  5. To this end, we also explored another possibility through the information statistic H, which has been largely employed when measuring agreement between the names given to a specific picture of an object (e.g. Snodgrass & Vanderwart, 1980). However, the results obtained with the use of H generally outperformed those obtained with the variables described for the purpose of mediation (there were, however, no contradictions between them).

  6. As pointed out by an anonymous reviewer, it is possible that different encoding contexts (e.g., survival scenario, moving scenario) constrain the generation of ideas to different degrees—with animate words causing, on average, the production of more ideas than inanimate words—and that differences in the number of ideas generated in response to specific words may vary in different contexts. Apart from the observation that the interactions between animacy or tasks and the measures of generated ideas are never significant—which suggests that differences between animacy conditions and tasks are similar whatever the number of generated ideas—the current findings cannot be used directly to answer such a question. In the Gelin et al. (2017) studies, animacy effects did not differ across different encoding contexts (e.g., survival encoding, tour guide), suggesting that, perhaps, different contexts do not substantially modify the number of ideas produced in response to animate compared to inanimate words. However, this issue still has to be investigated in detail.

  7. Nevertheless, before ending our discussion of this issue, we would like to indicate the results of a complementary analysis in which we took the number of different associates given for words as an index of richness-of-encoding. The scores were taken from the Bonin et al. (2013), in which participants were instructed to name the first word that came to mind in response to any given word. (We had scores available for only 9 animates and 7 inanimates used in the present study.) We found that the correlations of the number of associates with recall rates were all significantly positive at .05, except in the intentional learning task (r = .41, p = .119), and that more associates were generated for animate words than for inanimate words, t(14) = 3.05, p = .0087. While the results were descriptively in line with those previously reported, that is to say direct effects of animacy lower than total effects and confidence intervals of indirect effects mostly positive, they were still too widely distributed.

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Data Availability Statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Univ. Bourgogne Franche-Comté, LEAD-CNRS UMR5022, Pôle AAFE - Esplanade Erasme, BP 26513, 21065, Dijon Cedex, France

    Patrick Bonin, Gaëtan Thiebaut & Aurélia Bugaiska

  2. Université Clermont-Auvergne, LAPSCO-CNRS UMR6024, Clermont-Ferrand, France

    Alain Méot

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  1. Patrick Bonin
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  2. Gaëtan Thiebaut
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  4. Alain Méot
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Correspondence to Patrick Bonin.

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The authors wish to thank Richard Ferraro and two anonymous reviewers for their constructive comments on a previous version of the ms.

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Bonin, P., Thiebaut, G., Bugaiska, A. et al. Mixed evidence for a richness-of-encoding account of animacy effects in memory from the generation-of-ideas paradigm. Curr Psychol 41, 1653–1662 (2022). https://doi.org/10.1007/s12144-021-02666-8

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