Normalization of Deviation: Quotation Error in Human Factors

Hum Factors. 2018 May;60(3):293-304. doi: 10.1177/0018720817752253. Epub 2018 Jan 12.

Abstract

Objective The objective of this paper is to examine quotation error in human factors. Background Science progresses through building on the work of previous research. This requires accurate quotation. Quotation error has a number of adverse consequences: loss of credibility, loss of confidence in the journal, and a flawed basis for academic debate and scientific progress. Quotation error has been observed in a number of domains, including marine biology and medicine, but there has been little or no previous study of this form of error in human factors, a domain that specializes in the causes and management of error. Methods A study was conducted examining quotation accuracy of 187 extracts from 118 published articles that cited a control article (Vaughan's 1996 book: The Challenger Launch Decision: Risky Technology, Culture, and Deviance at NASA). Results Of extracts studied, 12.8% ( n = 24) were classed as inaccurate, with 87.2% ( n = 163) being classed as accurate. A second dimension of agreement was examined with 96.3% ( n = 180) agreeing with the control article and only 3.7% ( n = 7) disagreeing. The categories of accuracy and agreement form a two by two matrix. Conclusion Rather than simply blaming individuals for quotation error, systemic factors should also be considered. Vaughan's theory, normalization of deviance, is one systemic theory that can account for quotation error. Application Quotation error is occurring in human factors and should receive more attention. According to Vaughan's theory, the normal everyday systems that promote scholarship may also allow mistakes, mishaps, and quotation error to occur.

Keywords: Challenger; Vaughan; academics; normalization of deviance; quotation error.

MeSH terms

  • Bibliographies as Topic*
  • Ergonomics* / statistics & numerical data
  • Humans
  • Research* / standards
  • Research* / statistics & numerical data