Qualifications in Cliometrics/Quantitative History

This weeks readings, while occasionally controversial, have shown how cliometrics, quantitative history and the digital world as a whole have opened up new opportunities for historians to gather and assess vast amounts of data in making conclusions about the past. Websites like IPUMS have made this data even more available for scholars, and as discussed in the Ruggles article, have made it easier to code in demographic conditions as well as census data, making these conclusions even more accurate. However, there is trouble when trying to use the mathematic world to interpret the past.

This trouble is seen in Time on the Cross. When reading this I will say that I felt some of the wording and phrasing seemed a bit sketchy. I had assumed that most of the backlash would come from people who were like me, versed in traditional history and felt that the authors hadn’t considered enough of the stories behind slavery, focusing on numbers instead of human beings. However, like Haskell, I was surprised to find that a lot of the backlash came from the way in which the authors calculated their numbers. In his critique of the work, Haskell not only employs economic theory but also traditional historical methodology. One such example is, “Fogel and Engerman note the total absence of large free labor farms in the South and attribute it to the superior efficiency of slave labor. But it might just as well be attributed to the shortage of free laborers and the ideological opposition that slaveowners no doubt would have mounted against an alternative mode of production…” Clearly, cliometrics has its merits in the ability to disseminate large amounts of information in a clear and less time-consuming manner, but when taken out of context, it can bear very little meaning in the study of history.

In an example of using quantitative history in the context of the time period, the IPUMS website linked to a New York Times Article from April 2, 2012 that showed how newly digitized census data has proven that the Civil War death toll was about 20% higher than the numbers historians had been reporting for over a century. By factoring in information such as the type of health care available in the Union and in the Confederacy, high immigrant presence in the armies, and female death rates. However, Dr. Hacker, who came up with the new figures, admits that much of these numbers are based on estimates and assumptions that keep his data from being completely accurate.

My questions from our readings this week stem from the qualifications that each author has made regarding their cliometric and quantitative conclusions. In Time on the Cross, the authors acknowledge that the information they are presenting is controversial, however their contempt for past research into the economics of slavery keeps them from clarifying exactly how much of their data relies on qualifiers and assumptions about the Confederacy. The other authors and researchers make clear that in using data and numbers to make conclusions about the past there tends to be a lot of guesswork, and coming up with an exact, perfect number appears to be nearly impossible. I feel that this connects cliometrics and quantitative history with the traditional study of history in that, when studying primary sources, a historian can never be completely sure that they are getting the entire story. There is always bias or a hidden motive in records of the past, and in that way it appears that no matter if we are using numbers or words, there is always room for error in a historians work.

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