Why count? Why formalize?

Here are a few suggestions for further readings after you have read our Introduction and Chapter 1. Read them if you would like to better understand where we (and some others!) stand in the debates today as to why and how to use quantification – or formalization, to use a broader term.

We have not cited Scott Weingart’s “Argument Clinic” in our book, but we should have*. He succinctly addresses all the most important and vexing questions related to quantification in history (and the humanities), stressing the back-and-forth between data and theories (with rather practical details). He sums up his argument as follows:

I argue that one good approach to computational history cycles between data summaries and focused hypothesis exploration, driven by historiographic knowledge, in service to finding and supporting historically interesting agendas.

His explanations on how “hypotheses” and “experimentation” can be relevant in history – even, or especially, in a non-positivistic, constructivist version of history – very much resonate with what we try to say in Chapter 1. (you will also find his insistence on comparison consistent with our other chapters, esp. Chapter 2) We even agree with his last paragraphs on the status of “causality” and “truth” in these matters – something that constantly comes up in our workshops, that we did not dare put in so many words in our book, and that we rarely found in other texts.

As for very general papers, our classic is Charles Tilly’s “Observations of Social Processes and Their Formal Representations.” It is a short paper, partly written as a pointer to the author’s works and others that he likes. But it is also a succinct discussion of why the quantitative-qualitative divide tends to obscure discussions on actual methods (written by a sociologist who knew a lot about history and political science). It includes very useful reminders as to the fact that there are no intrinsically quantitative or qualitative topics, or types of evidence (the distinction only applies to tools of analysis). Moreover, it is better to talk about “formal” rather than quantitative methods, esp. as some produce visualizations rather than numbers. (we use “quantitative” in our title because it is customary to do so, but we very much agree on this point) Tilly also usefully sketches the different steps in a research schema (between the extreme points marked by sources in the beginning and narrative in the end) where formalization can be useful – if only as an incentive to stop and think.

 

* We cited his reminder that there has been quantitative history long before “digital humanities.” This post ends with a nice, short list of pitfalls to avoid and is also part of a possible “further reading” list for our Chapter 1.


Author: Claire Lemercier

CNRS research professor of history in Paris / Directrice de recherche au CNRS en histoire, au Centre de sociologie des organisations

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