Mismeasuring the mismeasure of man?

Thirty years ago, the late Stephen Jay Gould published The Mismeasure of Man, a key work for those who wished to decouple empirical science from the search for truth.

These mostly social science thinkers were quick to latch onto both Gould’s argument and his most famous evidence. Gould wrote that “science, since people must do it, is a socially embedded activity. … Facts are not pure and unsullied bits of information.”

Now, in an article available online, it’s Gould himself whose facts have been shown to be a result of cultural context.

In 1981, in The Mismeasure of Man, Gould charged 19th century investigator Samuel George Morton with having unconsciously skewed the results of his study of cranial size capacity in human skulls. As a man of his time, Morton was trying to determine if there was evidence for polygenesis (the separate creation of the races), rather than the Biblical account of  monogenesis. After measuring close to 1,000 skulls in two separate procedures, Morton concluded that there were, indeed, racial differences in cranial size and, therefore, in intellectual capacity. His results neatly fit the prevailing ideas of his time.

Gould did not repeat Morton’s tests, but he did reanalyze Morton’s results. Gould’s work showed that, contrary to Morton’s claim, there was no racial variation in the skulls. As a result of this new analysis, Gould wrote, it was clear that Morton had been a victim of unwitting bias, both in the ways he may have selected his test skulls and in the ways he applied his measurement methodologies. Morton had not been purposely deceptive — he was just another victim of his unavoidable expectation biases:

My message is not that biological determinists were bad scientists or even that they were always wrong. Rather, I believe that science must be understood as a social phenomenon, a gutsy, human enterprise, not the work of robots programmed to collect pure information.

Gould’s conclusions seem to bolster the popular postmodernist idea that truth is unobtainable because “facts” are always culturally construed.

But in The Mismeasure of Science: Stephen Jay Gould versus Samuel George Morton on Skulls and Bias it’s Gould’s turn to be outed as culturally biased — and a chance for the article’s authors to offer a different view of the objectivity of scientific investigation.

The article’s authors (too many to list here) acquired access to many of the skulls Morton had used in his original work and, unlike Gould, repeated his tests with today’s techniques. They found that Gould had achieved his results through a selective and flawed regrouping of the original data. (The details are available in the article, but they’re not necessary for the purposes of this article, so I’m omitting them here.) When the skulls were reexamined, the original results were proved to be correct. The data did show differences between skull groups.

The article’s authors are quick to point out — at some length — that they agree with Gould that scientists always bring biases and expectations to their work. They also decry Morton’s racist presumptions about the causes of the cranial capacity variation, noting that most scientists now argue that cranial capacity variations are due to climate rather than to race, and that where racial groups are concentrated in certain climates they show falsely “racial” differences.

So what comes of this recalibration? Gould was no more purposely deceptive than was Morton, the authors write — but he was just as susceptible to 20th century cultural biases as was Morton to those of his time. In other words, Gould, who campaigned against racism and the I.Q. testing that he saw as one of its agencies, expected, even “needed,” to find no racial differences — so he found none. By interpreting Morton’s results in a particular way, he got the results he expected. One can only speculate how many other ways Gould tried to crunch the data before he got rid of the result that he “knew” couldn’t be there.

Again, it’s important to emphasize that Morton’s racial conclusions were quite wrong. First, there is no true racial difference in cranial capacity, and second, there is no evidence that directly links intelligence to cranial capacity. So Morton’s data was correct, but he was wrong about what it meant.

And it’s equally important to restate that no one, from Gould to the article’s authors to this writer, is claiming that scientific inquiry is free of the skills, capacities, and weaknesses of its practitioners.

But the article’s authors take their results a step further.

Just as Gould and the hard relativists used the original Morton study as an example of the subjectivity of science, the authors use the revisited data as an example of the power of science to overcome investigative bias. They state the issue this way:

Our results falsify Gould’s hypothesis that Morton manipulated his data to conform with his a priori views. The data on cranial capacity gathered by Morton are generally reliable, and he reported them fully.

Morton’s initial reputation as the objectivist of his era was well-deserved. That Morton’s data are reliable despite his clear bias weakens the argument of Gould and others that biased results are endemic in science.

In other words, it’s clear that Morton was biased. It’s now also clear that Morton reported his findings accurately, despite his bias. What led him to do this? The authors’ answer: his commitment to the scientific method.

But the power of the scientific approach is that a properly designed and executed methodology can largely shield the outcome from the influence of the investigator’s bias. Science does not rely on investigators being unbiased “automatons.” Instead, it relies on methods that limit the ability of the investigator’s admittedly inevitable biases to skew the results. Morton’s methods were sound, and our analysis shows that they prevented Morton’s biases from significantly impacting his results. The Morton case, rather than illustrating the ubiquity of bias, instead shows the ability of science to escape the bounds and blinders of cultural contexts.

As one reviewer put it, all scientists are biased — but not all of their results.

We seem once again to have an argument that relativist cynicism about science should correctly be viewed as a caution, not a condemnation.

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3 thoughts on “Mismeasuring the mismeasure of man?

  1. I am not a fan of all these blogs popping up and writing about Gould by describing him in such terms as him being a “hard relativist.” It says more about the biases of the writers (or of our time) than anything else, which, in keeping with Thomas Kuhn, is exactly the message that Gould frequently drew attention to.

    This re-analysis I think suggests one thing: that Gould was a human, and humans are fallible. The scientists re-assessing his work have their own biases. One of the authors is quoted as saying: “I just didn’t trust Gould,” he said. “I had the feeling that his ideological stance was supreme. When the 1996 version of ‘The Mismeasure of Man’ came and he never even bothered to mention Michael’s study, I just felt he was a charlatan.” Who’s to say that their views didn’t play a role in this ‘re-telling’ of the story. Perhaps it will be re-told again.

    “All scientists are biased – but not all of their results?” I know these are the concluding words of the authors, not yours. But it sounds like scientistic ideology or positivist spin if you ask me. The ‘results’ are always interpreted through some scientific lens or another, each with its own inherent theoretical assumptions. There is no such thing as evidence ‘out there.’ I am not a relativist or a postmodernist, but I would take those views over that of the modern-day positivists any day.

    • If it’s at all relevant, I have half a shelf of books by Stephen Jay Gould. He was the writer whose work first interested me in evolutionary biology, a subject very far removed from my “natural” interests and experience.

      I don’t have a problem with “all scientists are biased — but not all of their results.” I believe that the claim relies on the difference between data and interpretation. I know that these definitions — bias, data, interpretation — can get tricky, but if one measures the volume of a skull cavity, one gets a number. Bias may have influenced the decision to do the measurement, and it certainly can influence what one makes of the measurement. But in this case, I believe that the article’s authors were making the point that despite his erroneous assumptions, Morton got the numbers right. He didn’t fudge or suppress data. And, unlike behavioural studies, where there is no truly “hard” data, physical measurements can be “true.”

      Yet, I see what you mean when you quote the ideological attacks on Gould — and I concede the article’s authors’ agenda. At the same time, I agree with them that the scientific method, including its unavoidable human limitations, is our best means to ascertain “the best truth, for now.”

  2. This suggests that the individual who claims that only the numbers count in science has a point.

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