Literature DB >> 25666493

Gould on Morton, Redux: What can the debate reveal about the limits of data?

Jonathan Michael Kaplan1, Massimo Pigliucci2, Joshua Alexander Banta3.   

Abstract

Lewis et al. (2011) attempted to restore the reputation of Samuel George Morton, a 19th century physician who reported on the skull sizes of different folk-races. Whereas Gould (1978) claimed that Morton's conclusions were invalid because they reflected unconscious bias, Lewis et al. alleged that Morton's findings were, in fact, supported, and Gould's analysis biased. We take strong exception to Lewis et al.'s thesis that Morton was "right." We maintain that Gould was right to reject Morton's analysis as inappropriate and misleading, but wrong to believe that a more appropriate analysis was available. Lewis et al. fail to recognize that there is, given the dataset available, no appropriate way to answer any of the plausibly interesting questions about the "populations" in question (which in many cases are not populations in any biologically meaningful sense). We challenge the premise shared by both Gould and Lewis et al. that Morton's confused data can be used to draw any meaningful conclusions. This, we argue, reveals the importance of properly focusing on the questions asked, rather than more narrowly on the data gathered.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Keywords:  Cranial capacity; Nested analysis of variance; Race; Research bias; Scientific controversy; Skull sizes

Mesh:

Year:  2015        PMID: 25666493     DOI: 10.1016/j.shpsc.2015.01.001

Source DB:  PubMed          Journal:  Stud Hist Philos Biol Biomed Sci        ISSN: 1369-8486


  2 in total

1.  Morton, Gould, and Bias: A Comment on "The Mismeasure of Science".

Authors:  Michael Weisberg; Diane B Paul
Journal:  PLoS Biol       Date:  2016-04-19       Impact factor: 8.029

2.  The fault in his seeds: Lost notes to the case of bias in Samuel George Morton's cranial race science.

Authors:  Paul Wolff Mitchell
Journal:  PLoS Biol       Date:  2018-10-04       Impact factor: 8.029

  2 in total

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