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Wittgenstein’s Revenge: How Semantic Algorithms Can Help Survey Research Escape Smedslund’s Labyrinth

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Respect for Thought

Part of the book series: Theory and History in the Human and Social Sciences ((THHSS))

Abstract

Empirical research has shown how semantic algorithms can often predict the statistics of survey data a priori, particularly in topics like “leadership” and “motivation.” In those cases, the survey data reflect the language usages of respondents, not the attitudes toward the topics in question. While this fact seems to bewilder researchers, it opens a computational tool for exploring our semantic construction of psychological reality. Using Dennett’s concept “competence without comprehension,” this article discusses how humans are trapped in a semantic network that we ourselves struggle to understand. Since Smedslund’s work and the language algorithms have common roots in formal logics, the computational algorithms may help us explore the cognitively challenging area of a priori assumptions in psychological research. There may be a computational way to test and explore Smedslund’s ideas of “pseudo-empiricality,” helping science explore the complex area among empirical, logical, and psychological phenomena.

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References

  • American Educational Research Association, American Psychological Association, Joint Committee on Standards for Educational, Psychological Testing (US), & National Council on Measurement in Education. (2014). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.

    Google Scholar 

  • American Psychological Association, American Educational Research Association, & National Council on Measurement in Education. (1954). Technical recommendations for psychological tests and diagnostic techniques. Psychological Bulletin, 51, 1–38.

    Google Scholar 

  • Arnulf, J. K., & Larsen, K. R. (2015). Overlapping semantics of leadership and heroism: Expectations of omnipotence, identification with ideal leaders and disappointment in real managers. Scandinavian Psychologist, 2(e3). https://doi.org/10.15714/scandpsychol.2.e3.

  • Arnulf, J. K., Larsen, K. R., Martinsen, O. L., & Bong, C. H. (2014). Predicting survey responses: how and why semantics shape survey statistics on organizational behaviour. PLoS One, 9(9), e106361. https://doi.org/10.1371/journal.pone.0106361.

    Article  PubMed  PubMed Central  Google Scholar 

  • Arnulf, J. K., Larsen, K. R., & Dysvik, A. (2018a). Measuring semantic components in training and motivation: A methodological introduction to the semantic theory of survey response. Human Resource Development Quarterly, 30(1), 17–38.

    Google Scholar 

  • Arnulf, J. K., Larsen, K. R., & Martinsen, Ø. L. (2018b). Respondent robotics: Simulating responses to likert-scale survey items. SAGE Open, 8(1), 1–18. https://doi.org/10.1177/2158244018764803.

    Article  Google Scholar 

  • Arnulf, J. K., Larsen, K. R., Martinsen, O. L., & Egeland, T. (2018c). The failing measurement of attitudes: How semantic determinants of individual survey responses come to replace measures of attitude strength. Behavior Research Methods, 1–21. https://doi.org/10.3758/s13428-017-0999-y.

  • Arnulf, J. K., Larsen, K. R. (2020). Culture blind leadership research: How semantically determined survey data may fail to detect cultural differences. Frontiers in Psychology 11(176).

    Google Scholar 

  • Avolio, B. J., Bass, B. M., & Jung, D. I. (1995). Multifactor leadership questionnaire technical report. Redwood City, CA: Mind Garden.

    Google Scholar 

  • Bagozzi, R. P. (2011). Measurement and meaning in information systems and organizational research: Methodological and philosophical foundations. MIS Quarterly, 35(2), 261–292. https://doi.org/10.2307/23044044.

    Article  Google Scholar 

  • Beeson, M. J. (2004). The mechanization of mathematics. In C. Teuscher (Ed.), Alan turing: Life and legacy of a great thinker (pp. 1–54). Berlin: Springer Verlag.

    Google Scholar 

  • Blanchette, P. A. (2012). Frege’s conception of logic. New York: Oxford University Press.

    Google Scholar 

  • Boole, G. (1847). The mathematical analysis of logic, being an essay towards a calculus of deductive reasoning. London, England: Macmillan, Barclay, & Macmillan.

    Google Scholar 

  • Boring, E. G. (1945). The use of operational definitions in science. Psychological Review, 52(5), 243–245. https://doi.org/10.1037/h0054934.

    Article  Google Scholar 

  • Bridgman, P. W. (1927). The logic of modern physics. New York: Macmillan.

    Google Scholar 

  • Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281–302. https://doi.org/10.1037/h0040957.

    Article  PubMed  Google Scholar 

  • Dennett, D. (2012). A perfect and beautiful machine’: What darwin’s theory of evolution reveals about artificial intelligence. The Atlantic.

    Google Scholar 

  • Dennis, S., Landauer, T. K., Kintsch, W., & Quesada, J. (2013). Introduction to latent semantic analysis. Denver, CO: University of Colorado.

    Google Scholar 

  • Elster, J. (2011). Hard and soft obscurantism in the humanities and social sciences. Diogenes, 58(1–2), 159. https://doi.org/10.1177/0392192112444984.

    Article  Google Scholar 

  • Feng, Y. (2015). A short history of Chinese philosophy. Beijing: Foreign Language Teaching and Research Press.

    Google Scholar 

  • Frege, G. (1884). Die Grundlagen der Arithmetik: eine logisch-mathematische Untersuchung über den Begriff der Zahl. Breslau: W. Koebner.

    Google Scholar 

  • Frege, G. (1918). Der Gedanke. Eine logische Untersuchung Beiträge zur Philosophie des deutschen Idealismus I (pp. 58–77).

    Google Scholar 

  • Gebotys, R. J., & Claxton-Oldfield, S. P. (1989). Errors in the quantification of uncertainty—A product of heuristics or minimal probability knowledge base. Applied Cognitive Psychology, 3(3), 237–250.

    Google Scholar 

  • Gefen, D., Endicott, J. E., Miller, J., Fresneda, J. E., & Larsen, K. R. (2017). A guide to text analysis with latent semantic analysis in R with annotated code: Studying online reviews and the stack exchange community. Communications of the Association for Information Systems, 41(11), 450–496.

    Google Scholar 

  • Gefen, D., & Larsen, K. (2017). Controlling for lexical closeness in survey research: A demonstration on the technology acceptance model. Journal of the Association for Information Systems, 18(10), 727–757. https://doi.org/10.17705/1jais.00469.

    Article  Google Scholar 

  • Graham, D. W. (2015). Heraclitus. In E. N. Zalta (Ed.), The Stanford Encyclopedia of philosophy (Fall 2015 Edition ed.).

    Google Scholar 

  • Harari, Y. N. (2015). Sapiens: A brief history of humankind. New York: Harper Collins.

    Google Scholar 

  • Harbsmeier, C. (2007). Globalisation and conceptual biodiversity. Paper presented at the Union Académique Internationale, Oslo.

    Google Scholar 

  • Jöreskog, K. G. (1993). Testing structural equation models. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 294–316). Newbury Park: Sage.

    Google Scholar 

  • Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.

    Google Scholar 

  • Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80(4), 237–251.

    Google Scholar 

  • Kelley, T. L. (1927). Interpretation of educational measurements. New York, NY: World Book.

    Google Scholar 

  • Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: Guilford Press.

    Google Scholar 

  • Kowalski, R., Jackson, M. A., Rogers, M. J., Shepherdson, J. C., Sannella, D., & Lehman, M. M. (1984). The relation between logic programming and logic specification [and Discussion]. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 312(1522), 345–361. https://doi.org/10.1098/rsta.1984.0064.

    Article  Google Scholar 

  • Kuvaas, B. (2006). Performance appraisal satisfaction and employee outcomes: mediating and moderating roles of work motivation. International Journal of Human Resource Management, 17(3), 504–522. https://doi.org/10.1080/09585190500521581.

    Article  Google Scholar 

  • Lamiell, J. T. (2013). Statisticism in personality psychologists’ use of trait constructs: What is it? How was it contracted? Is there a cure? New Ideas in Psychology, 31(1), 65–71. https://doi.org/10.1016/j.newideapsych.2011.02.009.

    Article  Google Scholar 

  • Landauer, T. K. (2007). LSA as a theory of meaning. In T. K. Landauer, D. S. McNamara, S. Dennis, & W. Kintsh (Eds.), Handbook of latent semantic analysis (pp. 3–34). Mahwah, NJ: Larence Erlbaum Associates, Publishers.

    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. https://doi.org/10.1037//0033-295x.104.2.211.

    Article  Google Scholar 

  • Larsen, K. R., & Bong, C. H. (2016). A tool for addressing construct identity in literature reviews and meta-analyses. MIS Quarterly, 40(3), 529. https://doi.org/10.25300/Misq/2016/40.3.01.

    Article  Google Scholar 

  • Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 140, 1–55.

    Google Scholar 

  • Lovasz, N., & Slaney, K. L. (2013). What makes a hypothetical construct “hypothetical”? Tracing the origins and uses of the ‘hypothetical construct’ concept in psychological science. New Ideas in Psychology, 31(1), 22–31. https://doi.org/10.1016/j.newideapsych.2011.02.005.

    Article  Google Scholar 

  • MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011). Construct measurement and validation procedures in mis and behavioral research: Integrating new and existing techniques. MIS Quarterly, 35(2), 293–334.

    Google Scholar 

  • March, J. G., & Simon, H. A. (1958). Organizations. New York: Wiley.

    Google Scholar 

  • Mari, L., Maul, A., Irribarra, D. T., & Wilson, M. (2017). Quantities, quantification, and the necessary and sufficient conditions for measurement. Measurement, 100, 115–121. https://doi.org/10.1016/j.measurement.2016.12.050.

    Article  Google Scholar 

  • Markie, P. (2017, Fall). Rationalism vs. empiricism. In E. N. Zalta (Ed.), The Stanford Encyclopedia of philosophy (2017 ed.). Stanford, CA: Stanford University.

    Google Scholar 

  • Maul, A. (2017). Rethinking traditional methods of survey validation. Measurement-Interdisciplinary Research and Perspectives, 15(2), 51–69. https://doi.org/10.1080/15366367.2017.1348108.

    Article  Google Scholar 

  • Michell, J. (1994). Measuring dimensions of belief by unidimensional unfolding. Journal of Mathematical Psychology, 38(2), 244–273. https://doi.org/10.1006/jmps.1994.1016.

    Article  Google Scholar 

  • Michell, J. (2013). Constructs, inferences, and mental measurement. New Ideas in Psychology, 31(1), 13–21. https://doi.org/10.1016/j.newideapsych.2011.02.004.

    Article  Google Scholar 

  • Mihalcea, R., Corley, C., & Strapparava, C. (2006). Corpus-based and knowledge-based measures of text semantic similarity. AAAI, 6, 775–780.

    Google Scholar 

  • Miller, G. A. (1995). Wordnet—A lexical database for English. Communications of the ACM, 38(11), 39–41. https://doi.org/10.1145/219717.219748.

    Article  Google Scholar 

  • Nimon, K., Shuck, B., & Zigarmi, D. (2015). Construct overlap between employee engagement and job satisfaction: A function of semantic equivalence? Journal of Happiness Studies, 17(3), 1149–1171. https://doi.org/10.1007/s10902-015-9636-6.

    Article  Google Scholar 

  • Nisbett, R. E., Peng, K., Choi, I., & Norenzayan, A. (2001). Culture and systems of thought: holistic versus analytic cognition. Psychological Review, 108(2), 291–310.

    PubMed  Google Scholar 

  • Norenzayan, A., Smith, E. E., Kim, B. J., & Nisbett, R. E. (2002). Cultural preferences for formal versus intuitive reasoning. Cognitive Science, 26(5), 653–684. https://doi.org/10.1207/s15516709cog2605_4.

    Article  Google Scholar 

  • Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. In S. T. Fiske, D. L. Schacter, & S. E. Taylor (Eds.), Annual review of psychology (Vol. 63, pp. 539–569). Palo Alto: Annual Reviews.

    Google Scholar 

  • Poli, R., Healy, M., & Kameas, A. (2010). WordNet. In C. Fellbaum (Ed.), Theory and applications of ontology: Computer applications (pp. 231–243). New York: Springer.

    Google Scholar 

  • Rogers, H. (1963). An example in mathematical logic. American Mathematical Monthly, 70(9), 929. https://doi.org/10.2307/2313050.

    Article  Google Scholar 

  • Rojas, R., Göktekin, C., Friedland, G., Krüger, M., Langmack, O., & Kuniss, D. (2000). Plankalkül: The first high-level programming language and its implementation. Retrieved from Berlin.

    Google Scholar 

  • Russell, B. (1922). An introduction to the tractatus logico-philosophicus. In L. Wittgenstein (Ed.), Tractatus logico-philosophicus. London: Kegan Paul.

    Google Scholar 

  • Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals, and understanding: An inquiry into human knowledge structures. New York: Routledge.

    Google Scholar 

  • Semin, G. (1989). The contributon of linguistic factors to attribute inference and semantic similarity judgements. European Journal of Social Psychology, 19, 85–100.

    Google Scholar 

  • Senge, P. (Producer). (2000). The leadership of profound change. SPC INK. Retrieved from http://66.102.9.104/search?q=cache:elAoLNjJDcgJ:www.spcpress.com/ink_pdfs/Senge.pdf+SPC+INK,+2000,+%231.&hl=en&ct=clnk&cd=1&gl=no

  • Simon, H. A. (1957). Models of man, social and rational: Mathematical essays on rational human behavior in a social setting. New York: Wiley.

    Google Scholar 

  • Slaney, K. L. (2017). Validating psychological constructs: Historical, philosophical, and practical dimensions. London: Palgrave Macmillan.

    Google Scholar 

  • Slaney, K. L., & Racine, T. P. (2013). Constructing an understanding of constructs. New Ideas in Psychology, 31(1), 1–3. https://doi.org/10.1016/j.newideapsych.2011.02.010.

    Article  Google Scholar 

  • Sluga, H. (1987). Frege against the Booleans. Notre Dame Journal of Formal Logic, 28(1), 89–98.

    Google Scholar 

  • Smedslund, J. (1978). Banduras theory of self-efficacy—Set of common-sense theorems. Scandinavian Journal of Psychology, 19(1), 1–14. https://doi.org/10.1111/j.1467-9450.1978.tb00299.x.

    Article  Google Scholar 

  • Smedslund, J. (1987). The epistemic status of inter-item correlations in Eysenck’s Personality Questionnaire: The a priori versus the empirical in psychological data. Scandinavian Journal of Psychology, 28, 42–55. https://doi.org/10.1111/j.1467-9450.1987.tb00904.x.

    Article  Google Scholar 

  • Smedslund, J. (1988). What is measured by a psychological measure. Scandinavian Journal of Psychology, 29(3-4), 148–151. https://doi.org/10.1111/j.1467-9450.1988.tb00785.x.

    Article  Google Scholar 

  • Smedslund, J. (1994). Nonempirical and empirical components in the hypotheses of 5 social-psychological experiments. Scandinavian Journal of Psychology, 35(1), 1–15. https://doi.org/10.1111/j.1467-9450.1994.tb00928.x.

    Article  Google Scholar 

  • Smedslund, J. (1995). Psychologic: Commonsense and the pseudoempirical. In J. Smith, R. Harre, & L. Van Langenhove (Eds.), Rethinking psychology (pp. 196–206). London: Sage.

    Google Scholar 

  • Smedslund, J. (2002). From hypothesis-testing psychology to procedure-testing psychologic. Review of General Psychology, 6, 51–72.

    Google Scholar 

  • Smedslund, J. (2012). Psycho-logic: Some thoughts and after-thoughts. Scandinavian Journal of Psychology, 55, 295–302.

    Google Scholar 

  • Smedslund, J. (2015). The value of experiments in psychology. In The Wiley handbook of theoretical and philosophical psychology (pp. 359–373). New Jersey: John Wiley & Sons, Ltd..

    Google Scholar 

  • Smedslund, J. (2016). Why psychology cannot be an empirical science. Integrative Psychological & Behavioral Science, 50(2), 185–195. https://doi.org/10.1007/s12124-015-9339-x.

    Article  Google Scholar 

  • Soros, G. (2006). The age of fallibility: The consequences of the war on terror. London: Weidenfeld & Nicolson.

    Google Scholar 

  • Stogdill, R. M. (1963). Manual for the leader behavior description questionnaire, form XII. Columbus, OH: Bureau of Business Research, Ohio State University.

    Google Scholar 

  • Thorndike, E. (1904). An introduction to the theory of mental and social measurements. New York: Columbia University: Teachers College.

    Google Scholar 

  • Todd, P. M., & Gigerenzer, G. (2003). Bounding rationality to the world. Journal of Economic Psychology, 24(2), 143–165. https://doi.org/10.1016/S0167-4870(02)00200-3.

    Article  Google Scholar 

  • Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131. https://doi.org/10.1126/science.185.4157.1124.

    Article  PubMed  Google Scholar 

  • Tversky, B., & Kessell, A. (2014). Thinking in action. Pragmatics & Cognition, 22(2), 206–223. https://doi.org/10.1075/pc.22.2.03tve.

    Article  Google Scholar 

  • van Knippenberg, D., & Sitkin, S. B. (2013). A critical assessment of charismatic—Transformational leadership research: Back to the drawing board? The Academy of Management Annals, 7(1), 1–60. https://doi.org/10.1080/19416520.2013.759433.

    Article  Google Scholar 

  • van Schuur, W. H., & Kiers, H. A. L. (1994). Why factor analysis often is the incorrect model for analyzing bipolar concepts, and what models to use instead. Applied Psychological Measurement, 18(2), 97–110.

    Google Scholar 

  • Wiener, N. (1948). Cybernetics. New York: Wiley.

    Google Scholar 

  • Wittgenstein, L. (1922). Tractatus logico-philosophicus. London: Kegan Paul.

    Google Scholar 

  • Yukl, G. (2012). Leadership in organizations (8th ed.). Harlow: Pearson Education.

    Google Scholar 

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  1. BI Norwegian Business School, Oslo, Norway

    Jan Ketil Arnulf

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  1. Jan Ketil Arnulf
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  1. Asker, Norway

    Tobias G. Lindstad

  2. Department of Psychology, University of Oslo, Oslo, Norway

    Erik Stänicke

  3. Department of Communication and Psychology, Aalborg University, Aalborg, Denmark

    Jaan Valsiner

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Arnulf, J.K. (2020). Wittgenstein’s Revenge: How Semantic Algorithms Can Help Survey Research Escape Smedslund’s Labyrinth. In: Lindstad, T., Stänicke, E., Valsiner, J. (eds) Respect for Thought. Theory and History in the Human and Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-43066-5_17

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