Bias in science: natural and social
- PDF / 374,096 Bytes
- 22 Pages / 439.37 x 666.142 pts Page_size
- 3 Downloads / 169 Views
Bias in science: natural and social Joshua May1 Received: 12 November 2019 / Accepted: 24 October 2020 © Springer Nature B.V. 2020
Abstract Moral, social, political, and other “nonepistemic” values can lead to bias in science, from prioritizing certain topics over others to the rationalization of questionable research practices. Such values might seem particularly common or powerful in the social sciences, given their subject matter. However, I argue first that the welldocumented phenomenon of motivated reasoning provides a useful framework for understanding when values guide scientific inquiry (in pernicious or productive ways). Second, this analysis reveals a parity thesis: values influence the social and natural sciences about equally, particularly because both are so prominently affected by desires for social credit and status, including recognition and career advancement. Ultimately, bias in natural and social science is both natural and social—that is, a part of human nature and considerably motivated by a concern for social status (and its maintenance). Whether the pervasive influence of values is inimical to the sciences is a separate question. Keywords Values in science · Wishful thinking · Conflicts of interest · Replication crisis · Research integrity · Motivated reasoning · Rationalization
1 Introduction Science has long been influenced by financial conflicts of interest, politics, and other biases. The replication crisis and high-profile cases of misconduct, however, have renewed concerns about the generation of biased data and conclusions, owing perhaps to the outsized influence of apparently “nonepistemic values,” such as political ideology and personal gain. Due to a number of factors—e.g. low sample sizes, small effect sizes, and ideological influences—one prominent scientist famously estimated that most published scientific findings are false (Ioannidis 2005). A key concern is that a researcher’s preferences or values can contribute to the rationalization of experimen-
B 1
Joshua May [email protected] University of Alabama at Birmingham, University Hall, Room 5010, 1402 10th Ave South, Birmingham, AL 35294-1241, USA
123
Synthese
tal designs or interpretations of data that will bring the researcher status, support their favored ideology, or promote what they perceive to be social justice (see e.g. Wilholt 2009). Social science has received a disproportionate amount of criticism and skepticism. With headlines like “How Academia’s Liberal Bias is Killing Social Science” in The Week (Gobry 2014) and “Social Sciences Suffer from Severe Publication Bias” in Nature (Peplow 2014), there certainly appears to be a “crisis of confidence” about findings in these fields (Pashler and Wagenmakers 2012: p. 528). Similar sentiments can be found in the popular media, such as The Washington Post, which has dispassionately stated: “The social end of the science spectrum is notorious for publishing questionable research, even in the most well-respected journals” (Gebelhoff 2017). In Scientific American, the scie
Data Loading...
