The Ups and Downs of Black and White: Do Sensorimotor Metaphors Reflect an Evolved Perceptual Interface?

References

• Asch, S. E. (1955). On the use of metaphor in the description of persons. In H. Werner (Ed.), On expressive language (pp. 29–38). Worcester: Clark University Press.
   Google Scholar
• Asch, S. E. (1958). The metaphor: A psychological inquiry. In R. Tagiuri & L. Petrullo (Eds.), Person perception and interpersonal behavior (pp. 324–333). Stanford: Stanford University Press.
   Google Scholar
• Bao, H. W. S. (2023). PsychWordVec: Word embedding research framework for psychological science (version 2023.9) [Computer Software]. https://CRAN.R-project.org/package=PsychWordVec
   Google Scholar
• Bao, H. W. S., Wang, Z. X., Cheng, X., Su, Z., Yang, Y. … Cai, H. (2023). Using word embeddings to investigate human psychology: Methods and applications. Advances in Psychological Science, 31(6), 887–904. doi:10.3724/SP.J.1042.2023.00887
   Google Scholar
• Bates, D., Mächler, M., Bolker, B., & Walker, S. (2014). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1). doi:10.18637/jss.v067.i01
   Web of Science ®Google Scholar
• Berke, M. D., Walter‐Terrill, R., Jara‐Ettinger, J., & Scholl, B. J. (2022). Flexible goals require that inflexible perceptual systems produce veridical representations: Implications for realism as revealed by evolutionary simulations. Cognitive Science, 46(10), e13195. doi:10.1111/cogs.13195
   PubMed Web of Science ®Google Scholar
• Berne, E. (1959). The mythology of dark and fair: Psychiatric use of folklore. The Journal of American Folklore, 72(283), 1–13. doi:10.2307/538382
   Web of Science ®Google Scholar
• Black, M. (1955). XII.—Metaphor. Proceedings of the Aristotelian Society, 55(1), 273–294. doi:10.1093/aristotelian/55.1.273
   Google Scholar
• Black, M. (1977). More about metaphor. Dialectica, 31(3–4), 431–457. https://www.jstor.org/stable/42969757
   Google Scholar
• Bowdle, B. F., & Gentner, D. (2005). The career of metaphor. Psychological Review, 112(1), 193–216 . doi:10.1037/0033-295X.112.1.193
   PubMed Web of Science ®Google Scholar
• Clark, A. (2009). Being there. Cambridge, MA: MIT Press.
   Google Scholar
• Clark, H. H. (1973). Space, time, semantics, and the child. In T. Moore (Ed.), Cognitive development and acquisition of language (pp. 27–63). New York: Academic Press.
   Google Scholar
• Crawford, E. L., Margolies, S. M., Drake, J. T., & Murphy, M. E. (2006). Affect biases memory of location: Evidence for the spatial representation of affect. Cognition and Emotion, 20(8), 1153–1169. doi:10.1080/02699930500347794
   Web of Science ®Google Scholar
• De Houwer, J. (2001). A structural and process analysis of the implicit association test. Journal of Experimental Social Psychology, 37(6), 443–451. doi:10.1006/jesp.2000.1464
   Web of Science ®Google Scholar
• Dudschig, C., de la Vega, I., & Kaup, B. (2015). What’s up? emotion-specific activation of vertical space during language processing. Acta Psychologica, 156, 143–155. doi:10.1016/j.actpsy.2014.09.015
   PubMed Web of Science ®Google Scholar
• Durgin, F. H., & Li, Z. (2017). Why do hills look so steep? In A. Shapiro & D. Todorovic (Eds.), Oxford compendium of visual illusions (pp. 190–197). New York, NY: Oxford University Press.
   Google Scholar
• Gagnon, S., Brunye, T., Robin, C., Mahoney, C., & Taylor, H. A. (2011). High and mighty: Implicit associations between space and social status. Frontiers in Psychology, 2, 259. doi:10.3389/fpsyg.2011.00259
   PubMed Web of Science ®Google Scholar
• Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7(2), 155–170. doi:10.1016/S0364-0213(83)80009-3
   Web of Science ®Google Scholar
• Gentner, D. (1988). Metaphor as structure mapping: The relational shift. Child Development, 59(1), 47–59. doi:10.2307/1130388
   Web of Science ®Google Scholar
• Gentner, D., & Grudin, J. (1985). The evolution of mental metaphors in psychology: A 90-year retrospective. American Psychologist, 40(2), 181–192. doi:10.1037/0003-066X.40.2.181
   Web of Science ®Google Scholar
• Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74(6), 1464–1480. doi:10.1037/0022-3514.74.6.1464
   PubMed Web of Science ®Google Scholar
• Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the implicit association test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85(2), 197–216. doi:10.1037/0022-3514.85.2.197
   PubMed Web of Science ®Google Scholar
• Günther, F., Dudschig, C., & Kaup, B. (2015). Lsafun-an R package for computations based on latent semantic analysis. Behavior Research Methods, 47(4), 930–944. doi:10.3758/s13428-014-0529-0
   PubMed Web of Science ®Google Scholar
• Günther, F., Rinaldi, L., & Marelli, M. (2019). Vector-space models of semantic representation from a cognitive perspective: A discussion of common misconceptions. Perspectives on Psychological Science, 14(6), 1006–1033. doi:10.1177/1745691619861372
   Web of Science ®Google Scholar
• Hoffman, D. D. (2018). The interface theory of perception. Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience, 2, 1–24. doi:10.1002/9781119170174.epcn216
   Google Scholar
• Hoffman, D. D., Singh, M., & Prakash, C. (2015). The interface theory of perception. Psychonomic Bulletin & Review, 22(6), 1480–1506. doi:10.3758/s13423-015-0890-8
   PubMed Web of Science ®Google Scholar
• Jackson, R. E., & Cormack, L. K. (2007). Evolved navigation theory and the descent illusion. Perception & Psychophysics, 69(3), 353–362. doi:10.3758/BF03193756
   PubMed Web of Science ®Google Scholar
• Keysar, B., & Bly, B. (1995). Intuitions of the transparency of idioms: Can one keep a secret by spilling the beans? Journal of Memory and Language, 34(1), 89–109. doi:10.1006/jmla.1995.1005
   Web of Science ®Google Scholar
• Keysar, B., & Bly, B. M. (1999). Swimming against the current: Do idioms reflect conceptual structure? Journal of Pragmatics, 31(12), 1559–1578. doi:10.1016/S0378-2166(99)00004-1
   Web of Science ®Google Scholar
• Kintsch, W. (2000). Metaphor comprehension: A computational theory. Psychonomic Bulletin & Review, 7(2), 257–266. doi:10.3758/BF03212981
   PubMed Web of Science ®Google Scholar
• Kintsch, W. (2008). How the mind computes the meaning of metaphor: A simulation based on LSA. In R. W. Gibbs Jr. (Ed.), The Cambridge handbook of metaphor and thought (pp. 129–142). New York: Cambridge University Press.
   Google Scholar
• Kittay, E., & Lehrer, A. (1981). Semantic fields and the structure of metaphor. Studies in Language, 5(1), 31–63. doi:10.1075/sl.5.1.03kit
   Google Scholar
• Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017). lmerTest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1–26. doi:10.18637/jss.v082.i1.
   Web of Science ®Google Scholar
• Lakoff, G., & Johnson, M. (1980a). The metaphorical structure of the human conceptual system. Cognitive Science, 4(2), 195–208. doi:10.1016/S0364-0213(80)80017-6
   Web of Science ®Google Scholar
• Lakoff, G., & Johnson, M. (1980b). Metaphors we live by. Chicago: University of Chicago press.
   Google Scholar
• Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104(2), 211–240. doi:10.1037/0033-295X.104.2.211
   Web of Science ®Google Scholar
• Landauer, T. K., Foltz, P. W., & Laham, D. (1998). An introduction to latent semantic analysis. Discourse Processes, 25(2–3), 259–284. doi:10.1080/01638539809545028
   Web of Science ®Google Scholar
• Landau, M. J., Meier, B. P., & Keefer, L. A. (2010). A metaphor-enriched social cognition. Psychological Bulletin, 136(6), 1045–1067. doi:10.1037/a0020970
   PubMed Web of Science ®Google Scholar
• Litman, L., Robinson, J., & Abberbock, T. (2017). TurkPrime.com: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior Research Methods, 49(2), 433–442. doi:10.3758/s13428-016-0727-z
   PubMed Web of Science ®Google Scholar
• Luke, S. G. (2017). Evaluating significance in linear mixed-effects models in R. Behavior Research Methods, 49(4), 1494–1502. doi:10.3758/s13428-016-0809-y
   PubMed Web of Science ®Google Scholar
• Meier, B. P., & Robinson, M. D. (2004). Why the sunny side is up: Associations between affect and vertical position. Psychological Science, 15(4), 243–247. doi:https://doi.org/10.1111/j.0956-7976.2004.00659.x
   PubMed Web of Science ®Google Scholar
• Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. Preprint at arXiv: Computation and Language. 10.48550/arXiv.1301.3781
   Google Scholar
• Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013). Distributed representations of words and phrases and their compositionality, Preprint. at arXiv: Computation and Language. 10.48550/arXiv.1310.4546.
   Google Scholar
• Murphy, G. L. (1996). On metaphoric representation. Cognition, 60(2), 173–204. doi:10.1016/0010-0277(96)00711-1
   PubMed Web of Science ®Google Scholar
• Murphy, G. L. (1997). Reasons to doubt the present evidence for metaphoric representation. Cognition, 62(1), 99–108. doi:10.1016/S0010-0277(96)00725-1
   PubMed Web of Science ®Google Scholar
• Nagy, W. (1974). Figurative Patterns and Redundancy in the Lexicon. Ph.D. dissertation, University of California at San Diego.
   Google Scholar
• Nick Reid, J., & Katz, A. N. (2018). Vector space applications in metaphor comprehension. Metaphor and Symbol, 33(4), 280–294 . doi:10.1080/10926488.2018.1549840
   Web of Science ®Google Scholar
• Nosek, B. A., Greenwald, A. G., & Banaji, M. R. (2005). Understanding and using the implicit association test: II. Method variables and construct validity. Personality and Social Psychology Bulletin, 31(2), 166–180. doi:10.1177/0146167204271418
   PubMed Web of Science ®Google Scholar
• Nosek, B. A., Greenwald, A. G., & Banaji, M. R. (2007). The implicit association test at age 7: A methodological and conceptual review. In J. A. Bargh (Ed.), Automatic processes in social thinking and behavior (pp. 265–292). New York: Psychology Press.
   Google Scholar
• Osgood, C. (1952). The nature and measurement of meaning. Psychological Bulletin, 49(3), 172–237. doi:10.1037/h0055737
   Web of Science ®Google Scholar
• Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957). The measurement of meaning. Urbana: University of Illinois Press.
   Google Scholar
• Pennington, J., Socher, R., & Manning, C. (2014). GloVe: Global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (pp. 1532–1543). 10.3115/v1/D14-1162
   Google Scholar
• Proffitt, D. R., Bhalla, M., Gossweiler, R., & Midgett, J. (1995). Perceiving geographical slant. Psychonomic Bulletin & Review, 2(4), 409–428. doi:10.3758/BF03210980
   PubMed Web of Science ®Google Scholar
• R Core Team. (2019). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
   Google Scholar
• Schimmack, U. (2021). The implicit association test: A method in search of a construct. Perspectives on Psychological Science, 16(2), 396–414. doi:10.1177/1745691619863798
   Web of Science ®Google Scholar
• Sherman, G. D., & Clore, G. L. (2009). The color of sin: White and black are perceptual symbols of moral purity and pollution. Psychological Science, 20(8), 1019–1025. doi:10.1111/j.1467-9280.2009.02403.x
   PubMed Web of Science ®Google Scholar
• Smith-McLallen, A., Johnson, B. T., Dovidio, J. F., & Pearson, A. R. (2006). Black and white: The role of color bias in implicit race bias. Social Cognition, 24(1), 46–73. doi:10.1521/soco.2006.24.1.46
   Web of Science ®Google Scholar
• Stoet, G. (2010). PsyToolkit: A software package for programming psychological experiments using linux. Behavior Research Methods, 42(4), 1096–1104. doi:10.3758/BRM.42.4.1096
   PubMed Web of Science ®Google Scholar
• Stoet, G. (2017). A novel web-based method for running online questionnaires and reaction-time experiments. Teaching of Psychology, 44(1), 24–31. doi:10.1177/0098628316677643
   Web of Science ®Google Scholar
• Thibodeau, P. H., Boroditsky, L. (2011). Metaphors we think with: The role of metaphor in reasoning. PloS One, 6(2), e16782. doi:10.1371/journal.pone.0016782
   PubMed Web of Science ®Google Scholar
• Thibodeau, P., & Durgin, F. H. (2008). Productive figurative communication: Conventional metaphors facilitate the comprehension of related novel metaphors. Journal of Memory and Language, 58(2), 521–540. doi:10.1016/j.jml.2007.05.001
   Web of Science ®Google Scholar
• Tourangeau, R., & Rips, L. (1991). Interpreting and evaluating metaphors. Journal of Memory and Language, 30(4), 452–472. doi:10.1016/0749-596X(91)90016-D
   Web of Science ®Google Scholar
• Tourangeau, R., & Sternberg, R. J. (1982). Understanding and appreciating metaphors. Cognition, 11(3), 203–244. doi:10.1016/0010-0277(82)90016-6
   PubMed Web of Science ®Google Scholar
• Williams, J. E., & Morland, J. K. (1976). Race, color, and the young child. Chapel Hill, NC: UNC Press Books.
   Google Scholar