The term physics envy is used to criticize modern writing and research of academics working in areas such as "softer sciences", liberal arts, business administration education, humanities, and social sciences.[1][2][3] The term argues that writing and working practices in these disciplines have overused confusing jargon and complicated mathematics to seem more 'rigorous' and like heavily mathematics-based natural science subjects like physics.[4][5]

Background

The success of physics in "mathematicizing" itself, particularly since Isaac Newton's Principia Mathematica, is generally considered remarkable and often disproportionate compared to other areas of inquiry.[6] "Physics envy" refers to the envy (perceived or real) of scholars in other disciplines for the mathematical precision of fundamental concepts obtained by physicists. It is an accusation raised against disciplines (typically against social sciences and liberal arts such as literature, philosophy, economics, and psychology) when these academic areas try to express their fundamental concepts in terms of mathematics, which is seen as an unwarranted push for reductionism.

Evolutionary biologist Ernst Mayr discusses the issue of the inability to reduce biology to its mathematical basis in his book What Makes Biology Unique?.[7] Noam Chomsky discusses the ability and desirability of reduction to its mathematical basis in his article "Mysteries of Nature: How Deeply Hidden."[8] Chomsky contributed extensively to the development of the field of theoretical linguistics, a formal science.

Examples

Social science has been accused of inferiority complex, which has been associated with physics envy. For instance, positivist scientists accept a mistaken image of natural science so it can be applied to the social sciences.[9] The phenomenon also exists in business strategy research as demonstrated by historian Alfred Chandler Jr.'s strategy structure model. This framework holds that a firm must evaluate the environment in order to set up its structure that will implement strategies.[10] Chandler also maintained that there is close connection "between mathematics, physics, and engineering graduates and the systemizing of the business strategy paradigm".[10]

In the field of artificial intelligence (AI), physics envy arises in cases of projects that lack interaction with each other, using only one idea due to the manner by which new hypotheses are tested and discarded in the pursuit of one true intelligence.[11]

See also

Notes

  1. Clarke, Kevin; Primo, David (31 March 2012). "Overcoming 'Physics Envy'". New York Times. Retrieved 10 August 2016.
  2. Sokal, Alan. "Physics envy in psychology: A cautionary tale" (PDF). New York University. Retrieved 10 August 2016.
  3. Bennis, Warren; O'Toole, James (May 2005). "How Business Schools Lost Their Way". Harvard Business Review. Retrieved 10 August 2016.
  4. Robin Dunbar (7 April 2011). The Trouble with Science. Faber & Faber. pp. 214–231. ISBN 978-0-571-26519-0.
  5. Smith, Noah (12 December 2015). "Academic B.S. as artificial barriers to entry". Economics, neologisms, and distraction. Retrieved 10 August 2016.
  6. For example, Eugene Wigner remarked "The miracle of the appropriateness of the language of mathematics for the formulation of the laws of physics is a wonderful gift which we neither understand nor deserve.", while Richard Feynman said "To those who do not know mathematics it is difficult to get across a real feeling as to the beauty, the deepest beauty, of nature ... If you want to learn about nature, to appreciate nature, it is necessary to understand the language that she speaks in."
  7. Mayr (2004)
  8. Chomsky (2009)
  9. Yoshida, Kei (2014). Rationality and Cultural Interpretivism: A Critical Assessment of Failed Solutions. Lanham, MD: Lexington Books. p. 126. ISBN 9780739173992.
  10. 1 2 Neergaard, Helle; Ulhøi, John P. (2007). Handbook of Qualitative Research Methods in Entrepreneurship. Cheltenham, UK: Edward Elgar Publishing. pp. 37–38. ISBN 9781843768357.
  11. Goertzel, Ben; Pennachin, Cassio (2007). Artificial General Intelligence. Berlin: Springer Science & Business Media. pp. 2007. ISBN 9783540237334.

References


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