Can causality be opposed to explanation?

Greetings from Toronto, where I gave some talks and had a great time with the archaeologists at the University of Toronto.

Actually, I don't particularly like epistemology.

I just read American Anthropologist’s 2012 review article on archaeological publications in 2011 (Hauser 2012). I came away confused about author Mark Hauser’s epistemology. I can’t seem to translate his approach into my own understanding of social science concepts of explanation and causality. Like many archaeologists, Hauser seems reluctant to discuss these things clearly and explicitly, leaving readers to puzzle them out from fragmentary and cryptic phrases.

I was particularly confused by two statements in Hauser’s paper:

·       “addressing long-standing questions about agriculture with new data require a shift from causality to explanations of process in specified contexts.” (p. 185)

·       “One major shift was a general move from the search for causes to explanation of cultivation, domestication, and farming.” (p. 186).

I find this puzzling, because to me, explanation means finding the cause for something. So what does Hauser mean by a shift from causality to explanation? His phrasing suggests that causality is the old and bad way of looking at things, while explanation is a new and good approach. This statement might give a clue:

·       “interpretive narratives find their expressions in situated explanations—a grounding in the messy idiosyncrasies of evidence—context—culture—history that run counter to more ambitious inclinations to craft explanatory models of history at larger scales.” (p.184)

Leaving aside the confusing conjunction of four words with hyphens, this statement suggests that Hauser is advocating explanation at a small scale. But does he mean a smaller spatial scale (we should concentrate on explaining a particular event in a particular place, not a large-scale spatial process like an empire or world system)? Or does he mean a smaller analytical scale (we should explain this particular household, and not households in general)? In my view, we need to explain things at a variety of spatial and analytical scales, and it doesn’t make much sense to prefer one level over another. It depends on the research question one is asking.

To me, talk of explanations at different scales suggests the concepts of proximate and ultimate causality. These concepts were first articulated in biology by Ernst Mayr (Mayr 1961). Proximate causes concern immediate factors such as ontogeny, and ultimate causes produce evolutionary explanations. While new work in biology has complicated this dichotomy, the basic distinction remains important in that field (Laland et al. 2011).

The proximate-ultimate distinction in causality is also important in the social sciences:

·       “ultimate explanations are concerned with why a behavior exists, and proximate explanations are concerned with how it works.”(Scott-Phillips et al. 2011:38)

Some writers parallel the approach of Laland et al in biology by advocating a more complex concept of social causation, but retaining the basic insight of the proximate/ultimate distinction. John Gerring (2005, 2012), for example, talks about “causal distance”: how far is the cause from the event it generates? Lieberson and Lynn (2002) use the phrases “underlying conditions” and “precipitating conditions” for these concepts.

But I don’t think this is the kind of thing Hauser has in mind, since he seems hostile to (or at least dismissive of) the concept of causality.

OK, let’s step back and look at what kinds of explanatory models are available in the social sciences (and, by extension, in archaeology). I always return to Charles Tilly for this kind of thing. I’m not a very good abstract thinker, and Tilly clarifies many epistemological issues in terms I can understand. According to Tilly, five explanatory strategies are available in the social and historical sciences. The following is my paraphrasing of: Tilly (2001:365) and Tilly and Goodin (2006:12-13); see also Tilly (2008). The text following *** are my own comments.

1.     Skepticism. The world is too complex to explain. *** I think this would be the strong postmodern position.

2.     Law-seeking accounts. Social life is said to exhibit empirical regularities that at their highest level take the form of laws; explanation then consists of subsuming particular cases under broadly validated empirical generalizations or even universal laws. *** This  is “logical positivism,” a framework associated with Carl Hempel. Binford and the new archaeologists promoted this approach to explanation, EVEN THOUGH IT HAD ALREADY BEEN DISCREDITED FOR SOCIAL SCIENCE BY PHILOSOPHERS OF SCIENCE! This was one of the biggest mistakes of Binford and the new archaeology, and it set archaeological epistemology back for decades!

3.     Propensity accounts. Social units are seen as self-directing, whether driven by emotions, motives, interests, rational choices, genes, or something else. Explanation then consists of reconstructing the state of the social unit—for example, an individual’s beliefs at a given point in time and space—and plausibly relating its actions to that state.  *** Most examples of propensity accounts follow methodological individualism, or the standard model in economics that says social phenomenon can be explained by the goals, decisions, and behavior of individuals. But other individual-level approaches, such as phenomenology, probably fit here as well.

4.     Systemic explanations. Particular features of social life are explained by specifying their connections with putative larger entities: societies, cultures, mentalities, capitalist systems, and the like. Explanation then consists of locating elements within systems. Functional explanation is a subcategory of systemic explanations. *** This includes both cultural explanations and explanations invoking large structural features such as social classes or world systems.

5.     Mechanism-based accounts. This approach claims that explanation consists of identifying in particular social phenomena reliable causal mechanisms and processes of general scope. Causal mechanisms are events that alter relations among some set of elements. Processes are frequent (but not universal) combinations and sequences of causal mechanisms. *** This is the way I think about explanation and causality. To explain an event is to identify the mechanisms responsible for bringing about that event. There is a BIG literature outside of anthropology on causal mechanisms. Some good starting points are:  (Bunge 2004), (Hedström and Ylikoski 2010), (Sampson 2011), and various works by Tilly, e.g. (Tilly 2008). Or check out Daniel Little’s blog, “Understanding Society” and search it for mechanisms.

When I started thinking about Hauser’s puzzling statements on causality and explanation, I thought Tilly’s scheme of the five explanatory approaches would clarify the situation, but now I’m not so sure. I still can’t figure out what Hauser’s explanatory position is, or how he can oppose the terms causality and explanation. I have almost given up trying to understand archaeological writing in this genre, that might be called “postmodern-light.”  I guess I will just have to admit defeat here.

My broader point is that archaeologists need to discuss epistemology more frequently, more explicitly, and more in tune with the relevant social science literature. Our own field has a rather poor track record in this area, and cultural anthropology is not much better. If this stuff is new to you, check out Tilly or Bunge or some of the other sources below. When I find myself in a conceptual difficulty, I often ask myself, “what would Tilly say about this?” Maybe you should ask that question too.

Bunge, Mario

2004    How Does It Work?: The Search for Explanatory Mechanisms. Philosophy of the Social Sciences 34(2):182-210.

Gerring, John

2005    Causation: A Unified Framework for the Social Sciences. Journal of Theoretical Politics 17:163-198.

2012    Social Science Methodology: A Unified Framework. 2nd ed. Cambridge University Press, New York.

Hauser, Mark W.

2012    The Year in Review, Archaeololgy: Messy Data, Ordered Questions. American Anthroologist 114(2):184-195.

Hedström, Peter and Petri Ylikoski

2010    Causal Mechanisms in the Social Sciences. Annual Review of Sociology 36:49-67.

Laland, Kevin N., Kim Sterelny, John Odling-Smee, William Hoppitt, and Tobias Uller

2011    Cause and Effect in Biology Revisited: Is Mayr's Proximate-Ultimate Dichotomy Still Useful? Science 334:1512-1515.

Lieberson, Stanley and Freda B. Lynn

2002    Barking up the Wrong Branch: Scientific Alternatives to the Current Model of Sociological Science. Annual Review of Sociology 28:1-19.

Mayr, Ernst

1961    Cause and Effect in Biology. Science 134:1501-1506.

Sampson, Robert J.

2011    Neighborhood Effects, Causal Mechanisms and the Social Structure of the City. In Analytical Sociology and Social Mechanisms, edited by Pierre Demeulenaere, pp. 227-249. Cambridge Universitiy Press, New York.

Scott-Phillips, Thomas C., Thomas E. Dickins, and Stuart A. West

2011    Evolutionary Theory and the Ultimate–Proximate Distinction in the Human Behavioral Sciences. Perspectives on Psychological Science 6(1):38-47.

Tilly, Charles

2001    Relational Origins of Inequality. Anthropological Theory 1(3):355-372.

2008    Explaining Social Processes. Paradigm Publishers, Boulder, CO.

Tilly, Charles and Robert E. Goodin

2006    It Depends. In Oxford Handbook of Contextual Political Analysis, edited by Robert E. Goodin and Charles Tilly, pp. 3-32. Oxford University Press, New York.

Natural experiments in archaeology

I've been wondering recently why more archaeologists don't use the method and concept of "natural experiment." In one sense, natural experiments are not uncommon in archaeology; we sometimes call them "controlled comparisons," probably borrowing that term from cultural anthropology (Eggan 1954). But we rarely use the phrase "natural experiment," which has been gaining ground in the comparative branches of the social sciences, history, and ecology. This isn't just a terminological issue; natural experiments are all about how to determine causality. Most archaeologists, however, avoid discussing causality, and this may account for the rarity of the natural experiment concept in our field.

(Postmodern, postprocessualist, and other "post" archaeologists can probably stop reading here, unless you are looking for more fodder to critique simplistic scientistic Smith).


A natural experiment is "an observational study that nonetheless has the properties of an experimental research design.” (Gerring 2007: 216). The recent collection edited by Jared Diamond and James Robinson (2010) presents a series of historical natural experiments, including one archaeological case study. In an insightful review of the book in the journal Science, James Mahoney notes:

·         “Historical analysts cannot, of course, test their ideas by running controlled experiments. They cannot randomly assign cases to treatment and control groups. But they can sometimes make a credible claim that the assignment of cases to different groups is “as if” random. The label “natural experiment” (or “quasi-experiment”) is often reserved for those studies in which this assumption seems especially plausible.”(Science vol. 357, p. 1578)

It is probably no surprise that the archaeological example in this book is by Patrick Kirch (2010), who has been doing "natural experiments" or "controlled comparisons" for years. Island societies are productive candidates for natural experiments because of their boundedness and relative isolation. In this chapter he compares Hawaii, the Marquesas and Mangaia as contrasting environments in which initially similar ancestral Polynesian societies evolved in very different directions.

Gerring 2007: 153

I won't go into details here, beyond recommending Diamond and Robinson and other works on natural experiments (Gerring 2007; Dunning 2008; Labizna 2011). But just to show how this line of methodological thinking lines up with archaeology, consider John Gerring's depiction of types of experimental design in case study research (recall that most research in archaeology follows the approach called case study research in other disciplines).

Quadrant #1 is the classic experimental design. Two populations, the treatment group and control group (spatial variation) are observed through time, before and after the "treatment" or the "perturbation" (the term used in Diamond and Robinson 2010). Quadrants 2 and 3, with only temporal or spatial variation, are relatively common in archaeology. The fourth quadrant is for studies where there is no spatial or temporal variation. This is perhaps the most common archaeological situation. You do a study, come up with some results, and then put forward an argument about what they mean: what were the dynamics, how and why did something happen, etc. But since you have made no formal comparison of either a before-and-after nature, or a spatial nature, it is very difficult to demonstrate causality. The typical course of action is make as strong an argument as one can. "That's my story and I'm stickin' to it!" But a methodologically superior method would be to find a way to make an explicit temporal and/or spatial comparison.

When there just happens to be no good comparison one can make, then you need to use counterfactual logic to make a causal claim. There is a rather large literature on formal counterfactual causality in sociology and political science (e.g., Gerring 2005, Heckman 2005, Morgan & Winship 2007). In its simplest form, making a causal claim without an experiment or comparison requires one to consider the counterfactual situation of what would have happened had the hypothesized causal agent not been present, or acted differently. One then shows that such a situation does not match reality, which gives support to the causal hypothesis.

Here is an example. I think that the ability of people (whose houses I have excavated) to cultivate cotton in Aztec-period Morelos was the main source of their economic prosperity. That is, cotton cultivation was a major cause of their prosperity. I don't have a "before and after" comparison (first no cotton, then cotton cultivation), and there are not enough comparative cases of sites where we know about cotton cultivation (presence or absence) and prosperity in enough detail. (Once some current project are complete, this situation will improve). So I explore the counterfactual situation: what would the local economy be like if they were not able to grow cotton? They would have had fewer resources to trade with other areas. Cotton textiles served as money, and thus cotton was far more valuable than other local resources such as maize, bark paper, or basalt. Also, it would have been far more difficult to come up with their taxes, assessed in cotton textiles. (And there would probably be far fewer spindle whorls in domestic middens).

Now I can come up with all sorts of plausible factors to support my causal claim about cotton and prosperity, but the argument will be much more effective once I can add some formal comparisons. For example, were people at Calixtlahuaca, where cotton was not cultivated, less prosperous? This will be a start, but more cases are needed to make a strong argument. Or perhaps I could show that prosperity declined after the Spanish conquest (it almost certainly it did, but demonstrating that is quite difficult), when historical sources tell us that irrigated cotton fields were converted to sugar cane.

In any case, these various comparative scenarios are natural experiments. We mostly do observational (case study) research in archaeology. To the extent that we can design and describe our research in quasi-experimental terms and use this approach to explore causality, our explanations will be more convincing, and scholars and others outside of archaeology will be more likely to view our discipline as an empirical scientific field with something to say about the world. Now, many archaeologists don't want our field to be scientific. They want to use fashionable high-level theory to interpret the past, without the constraints of scientific methods. That is fine for some purposes, but if we want anyone outside of the humanities to pay attention to us and find something of value in our research, then we need to do all we can to beef up our methods in a scientific direction. We need to pursue science #1 (epistemological science) and just just science #2 (jazzy technical methods). And natural experiments are one way to do this.

Diamond, Jared and James A. Robinson (editors)
2010    Natural Experiments of History. Harvard University Press, Cambridge.

Dunning, Thad
2008    Improving Causal Inference: Strengths and Limitations of Natural Experiments. Political Research Quarterly 61: 282-293

Eggan, Fred
1954    Social Anthropology and the Method of Controlled Comparison. American Anthropologist 56:743-763.

Gerring, John
2005    Causation: A Unified Framework for the Social Sciences. Journal of Theoretical Politics 17: 163-198.

Gerring, John
2007    Case Study Research: Principles and Practices. Cambridge University Press, New York.

Heckman, James J.
2005    The Scientific Model of Causality. Sociological Methodology 35: 1-97.

Kirch, Patrick V.
2010    Controlled Comparison and Polynesian Cultural Evolution. In Natural Experiments of History, edited by Jared Diamond and James A. Robinson, pp. 15-52. Harvard University Press, Cambridge.

Labzina, Elena
2011    No Free Lunch: Costs and Benefits of Using the Concept of Natural Experiments in Political Science. M.A. thesis, Department of Political Sciences, Central European University.

Morgan, Stephen L. and Christopher Winship
2007    Counterfacturals and Causal Inference: Methods and Principles for Social Research. Cambridge University Press, New York.