One of the few books of Stephen Jay Gould I never read was his Mismeasure of Man. I suppose it was a low priority – as I have never considered cranial capacity a measure of intelligence or state of advancement. This is partly because of an awareness that women tend to have smaller skulls than men and yet this has no bearing on their cognitive skills. I knew that Gould was taking Samuel George Morton to task because Morton had considered cranial capacity to be significant for ranking human races in some sort of hierarchical order. Gould considered that Morton provided a case study of someone who had “finangled” his data and his analysis to reach unwarranted conclusions. His 1978 paper concluded in this way:
“Yet, through all this juggling, I find no indication of fraud or conscious manipulation. Morton made no attempt to cover his tracks, and I must assume that he remained unaware of their existence. He explained everything he did, and published all his raw data. All I discern is an a priori conviction of racial ranking so powerful that it directed his tabulations along pre-established lines. Yet Morton was widely hailed as the objectivist of his age, the man who would rescue American science from the mire of unsupported speculation.”
Gould carried the day with his analysis of Morton’s work. There were some who questioned his conclusions, but most regarded Gould’s paper and book as definitive. It took on an iconic status.
“Gould used Morton as a case study to argue that “unconscious or dimly perceived finagling, doctoring, and massaging are rampant, endemic, and unavoidable in a profession that awards status and power for clean and unambiguous discovery”. Gould’s analysis of Morton is widely read, frequently cited, and still commonly assigned in university courses. Morton has become a canonical example of scientific misconduct and an oft-told cautionary tale of how human variation is inevitably mismeasured.”
The icon has been demolished by Jason Lewis and colleagues, who have remeasured Morton’s skulls and revisited the data analysis issues.
For more, go here: