Introduction to Benjamin Wright and His Contributions to Measurement Science

Chapter
Part of the Springer Series in Measurement Science and Technology book series (SSMST)

Abstract

In this chapter we briefly describe the facts of Ben Wright’s professional career as a physicist and psychologist. We also make some perspective-setting remarks on the strengths and range of his accomplishments, on the nature of his engaging and sometimes-challenging personality, as well as on his perspicacity and forward-looking view on the roles of measurement in the scientific world. In doing so, we ask some questions about his career and work that we hope (and expect) are illuminated by the succeeding chapters of the volume. Of particular interest are the ways in which Wright drew from his deep experiences in physics, mathematics, computers, and psychoanalysis to set the stage for new advances in qualitative theory and quantitative precision in measurement science, advances that are proving to span a wide range of fields not limited to psychology and the social sciences. We also give some details of the original Conference that was the generator of many of the chapters in the Volume.

References

  1. Andrich, D. (1988). Sage University Paper Series on quantitative applications in the social sciences. Vol. series no. 07–068: Rasch models for measurement. Beverly Hills, California: Sage Publications.Google Scholar
  2. Andrich, D. (2015). Ben Wright: “Idiosyncrasies of Autobiography and Personality” in taking up the Rasch measurement paradigm. Rasch Measurement Transactions, 29(3), 1539–1542.Google Scholar
  3. Andrich, D. (2017). A law of ordinal random error: The Rasch measurement model and random error distributions of ordinal assessments. Journal of Physics Conference Series. in press.Google Scholar
  4. Black, M. (1962). Models and metaphors. Ithaca, New York: Cornell University Press.Google Scholar
  5. Black, M. (1993). More about metaphor. In A. Ortony (Ed.), Metaphor and thought (pp. 19–43). Cambridge: Cambridge University Press. (Reprinted from Black, M. (1977). More about metaphor. Dialectica, 31(3–4), 431–457).CrossRefGoogle Scholar
  6. Boumans, M. (1993). Paul Ehrenfest and Jan Tinbergen: A case of limited physics transfer. In N. De Marchi (Ed.), Non-natural social science: Reflecting on the enterprise of “More Heat than Light” (pp. 131–156). Durham, NC: Duke University Press.Google Scholar
  7. Boumans, M. (2005). How economists model the world into numbers. New York: Routledge.CrossRefGoogle Scholar
  8. Cheng, Y. T., & Cheng, C. M. (2004). Scaling, dimensional analysis, and indentation measurements. Materials Science and Engineering: R: Reports, 44(4), 91–149.CrossRefGoogle Scholar
  9. Cipriani, D., Fox, C., Khuder, S., & Boudreau, N. (2005). Comparing Rasch analyses probability estimates to sensitivity, specificity and likelihood ratios when examining the utility of medical diagnostic tests. Journal of Applied Measurement, 6(2), 180–201.PubMedGoogle Scholar
  10. Finkelstein, L. (2009). Widely-defined measurement: An analysis of challenges. Measurement, 42(9), 1270–1277.CrossRefGoogle Scholar
  11. Finkelstein, L. (2010). Measurement and instrumentation science and technology-the educational challenges. Journal of Physics Conference Series, 238, 012001.CrossRefGoogle Scholar
  12. Fisher, W. P., Jr. (1988). Truth, method, and measurement: the hermeneutic of instrumentation and the Rasch model, diss. Dissertation Abstracts International 49, 0778A. Dept. of Education, Division of the Social Sciences: University of Chicago. 376 pages, 23 figures, 31 tables.Google Scholar
  13. Fisher, W. P., Jr. (2008). Notes on IMEKO symposium. Rasch Measurement Transactions, 22(1), 1147.Google Scholar
  14. Fisher, W. P., Jr. (2010a). Rasch, Maxwell’s method of analogy, and the Chicago tradition. Paper presented at the conference, Celebrating 50 years since the publication of Rasch’s Probabilistic Models, University of Copenhagen School of Business, FUHU Conference Centre, Copenhagen, Denmark.Google Scholar
  15. Fisher, W. P., Jr. (2010b). The standard model in the history of the natural sciences, econometrics, and the social sciences. Journal of Physics Conference Series, 238(1), 012016.CrossRefGoogle Scholar
  16. Fisher, W. P., Jr. (2017). A practical approach to modeling complex adaptive flows in psychology and social science. Procedia Computer Science, 114, 165–174.Google Scholar
  17. Fisher, W. P., Jr., Bernstein, L. H., Qamar, A., Babb, J., Rypka, E. W., & Yasick, D. (2002). At the bedside: Measuring patient outcomes. Advance for Administrators of the Laboratory, 11(2), 8. 10.Google Scholar
  18. Fisher, W. P., Jr., & Burton, E. (2010). Embedding measurement within existing computerized data systems: Scaling clinical laboratory and medical records heart failure data to predict ICU admission. Journal of Applied Measurement, 11(2), 271–287.PubMedGoogle Scholar
  19. Fisher, W. P., Jr., & Stenner, A. J. (2013). On the potential for improved measurement in the human and social sciences. In Q. Zhang & H. Yang (Eds.), Pacific Rim Objective Measurement Symposium 2012 Conference Proceedings. Berlin, Germany: Springer-Verlag.Google Scholar
  20. Fisher, W. P., Jr., & Stenner, A. J. (2016). Theory-based metrological traceability in education: A reading measurement network. Measurement, 92, 489–496.CrossRefPubMedPubMedCentralGoogle Scholar
  21. Hambleton, R., Wright, B. D., Crocker, L., Masters, G., & van der Linden, W. (1992). Hambleton’s 9 theses. Rasch Measurement Transactions, 6(2), 215.Google Scholar
  22. Mari, L., & Wilson, M. (2014). An introduction to the Rasch measurement approach for metrologists. Measurement, 51, 315–327.CrossRefGoogle Scholar
  23. Nersessian, N. J. (2002). Maxwell and “the method of physical analogy:” Model-based reasoning, generic abstraction, and conceptual change. In D. Malament (Ed.), Reading natural philosophy: Essays in the history and philosophy of science and mathematics (pp. 129–166). Lasalle, Illinois: Open Court.Google Scholar
  24. Pelton, T., & Bunderson, V. (2003). The recovery of the density scale using a stochastic quasi-realization of additive conjoint measurement. Journal of Applied Measurement, 4(3), 269–281.PubMedGoogle Scholar
  25. Pendrill, L. (2014). Man as a measurement instrument [Special Feature]. NCSLi Measure: The Journal of Measurement Science, 9(4), 22–33.CrossRefGoogle Scholar
  26. Pendrill, L., & Fisher, W. P., Jr. (2015). Counting and quantification: Comparing psychometric and metrological perspectives on visual perceptions of number. Measurement, 71, 46–55.CrossRefGoogle Scholar
  27. Powers, M., Fisher, W. P., Jr. & Massof, R. W. (2016). Modeling visual symptoms and visual skills to measure functional binocular vision. Journal of Physics Conference Series, 772(1), 012045.Google Scholar
  28. Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen, Denmark: Nielsen and Lydiche. [Republished, 1980, University of Chicago Press.]Google Scholar
  29. Rasch, G. (1988/1972). Review of the cooperation of Professor B. D. Wright, University of Chicago, and Professor G. Rasch, University of Copenhagen; letter of June 18, 1972. Rasch Measurement Transactions, 2(2), 19.Google Scholar
  30. Ricoeur, P. (1991). Narrative identity. In D. Wood (Ed.), On Paul Ricoeur: Narrative and interpretation (pp. 188–199). New York, New York: Routledge.Google Scholar
  31. Royal, K. (Ed.). (2015). A tribute to Benjamin D. Wright [Special issue]. Rasch Measurement Transactions, 29(3), 1528–1546.Google Scholar
  32. Stephanou, A., & Fisher, W. P., Jr. (2013). From concrete to abstract in the measurement of length. Journal of Physics Conference Series, 459, 012026.CrossRefGoogle Scholar
  33. Stone, M. H., & Stenner, A. J. (2014). From ordinality to quantity. Rasch Measurement Transactions, 27(4), 1439–1440.Google Scholar
  34. Wilson, M. R. (2013). Using the concept of a measurement system to characterize measurement models used in psychometrics. Measurement, 46, 3766–3774.CrossRefGoogle Scholar
  35. Wilson, M., Mari, L., Maul, A., & Torres Irribarra, D. (2015). A comparison of measurement concepts across physical science and social science domains: Instrument design, calibration, and measurement. Journal of Physics Conference Series, 588, 012034.CrossRefGoogle Scholar
  36. Wright, B. D. (1960). Should children teach? The Elementary School Journal, 60, 353–369.CrossRefGoogle Scholar
  37. Wright, B. D. (1968). The sabbath lecture: Love and order. In A. R. Nielsen et al. (Eds.), Lust for learning. Thy, Denmark: New Experimental College Press.Google Scholar
  38. Wright, B. D. (1997). A history of social science measurement. Educational Measurement: Issues and Practice, 16(4), 33–45, 52.CrossRefGoogle Scholar
  39. Wright, B. D. (2000). Rasch regression: My recipe. Rasch Measurement Transactions, 14(3), 758–759.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Graduate School of EducationUniversity of California, BerkeleyBerkeleyUSA

Personalised recommendations