Archaeology, like many disciplines, focuses mainly on expanding the horizons of what we know about the world and how it works. Archaeologists make and test hypotheses about past human beings and cultures using material remains (pottery, stone tools, plant remains, etc.) that are left behind in the archaeological record. In the process, we learn more about what people were up to in the past and how they responded to the geographic, environmental, and social conditions of the times.
But how do we know what we don’t know? This is often a much more difficult question. Identifying gaps in knowledge and how they came to be even has its own field of study—agnotology. Archaeologists may not know about a particular time period, culture, or set of behaviors for a variety of reasons (Wylie 2008), including:
- The relevant evidence hasn’t survived to the present for one reason or another. For example, bone and shell are rarely recovered from archaeological sites in western Illinois due to acidic soils and natural decay over time. Learning about past diets or the use of organic technologies can be difficult in these circumstances.
- The technology to gather or analyze certain kinds of archaeological data doesn’t yet exist. For example, advances in geophysical surveys and equipment now allow archaeologists to document subsurface features over very large areas which would be too difficult or expensive to excavate using traditional methods.
- We lack the right theoretical framework to make sense of certain kinds of archaeological datasets. How we think about and contextualize archaeological questions and data matters quite a lot.
- The human behaviors and cultural practices we want to study are very complex, and the ways those intersect with the natural and social environment can sometimes defy our best attempts at prediction and explanation.
- Archaeologists make choices about what to study (or not) that hinge on theoretical (what data are relevant to my hypothesis?), economic (how much funding do I have to hire survey crews this summer?), or personal considerations (what types of material do I find interesting?).
For all that, the answer to why we don’t know much about a particular region or time period is sometimes pretty simple—no one has ever bothered to look there or archaeological collections that do exist in those regions have not been systematically documented by professional archaeologists.
Despite more than 100 years of archaeological research in Illinois, large parts of the state have received very little professional survey. If we look at a map showing the amount of survey that has been done across the state (Figure 1, left), we can see that there is a huge amount of variation in where archaeological survey has taken place (blue is low survey, red is high survey). Places like the collar counties around Chicago and the East St. Louis area have been thoroughly investigated, but if we look at other parts of Illinois, less than 5% of the area in most townships has been surveyed. Almost one third of townships in Illinois have less than 1% of their area surveyed! By and large, places with high populations, a lot of modern development, more road building, or proximity to universities have received more attention from archaeologists.
Figure 2: Areas with high predicted site probability (red) that fall within under-surveyed townships (gray) in Illinois. Enlarge image for full detail.
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We can also use spatial statistics and GIS to help get a sense of how over- and under-surveyed areas are distributed in the state (Figure 1, center). In other words, where are the places that we don’t know a lot about the archaeological record? How do those compare to places that are comparatively very well surveyed? The second map shows statistically significant clusters of over-surveyed (red) or under-surveyed (blue) townships. Over- and under-surveyed clusters are analogous to hot and cold spots with similar values, and over- and under-surveyed spatial outliers fall next to townships with different values (e.g., under-surveyed next to over-surveyed). For example, large chunks of the uplands east of the Mississippi River in western Illinois are statistically under-surveyed.
So how do places where we don’t know much match up with our expectations about the archaeological record? The Illinois Archaeological Predictive Model (IAPM) is a GIS-based tool developed by the ISAS that predicts the probability of encountering pre-contact Native American sites across the state (Figure 1, right). Other things equal, we should expect to find more archaeological sites in places that have high probability (red) than low probability (blue). Interestingly, some of those areas fall in places that are statistically under-surveyed (Figure 2). We should expect to find sites in places like Ford and Iroquois counties in eastern Illinois, or along the Embarras River drainage in southeast Illinois, but no one has ever bothered to look there! Of course, that’s an oversimplification. Archaeologists would love to survey every square inch of the state, but limited time and resources mean that is usually not possible.
One way we can help fill in these gaps in our knowledge is through collaboration between professional archaeologists at places like ISAS and Tribal Nations, avocational archaeologists, and citizen-scientists. If you have archaeological collections from Illinois or know of archaeological sites in your area that may not be documented—especially if they come from an area that we just don’t know that much about—we would love to hear from you! If you have questions about an artifact or would like to share information about a site or collection, please consider filling out a short form that can be reached by clicking on the Ask an Archaeologist button on our website. Thanks to all Illinoisans who have already shared their finds with ISAS, helping to shed light on our state’s cultural history.
Wylie, A. 2008. Mapping Ignorance in Archaeology: The Advantages of Historical Hindsight. In Agnotology: The Making and Unmaking of Ignorance, edited by R. N. Proctor and L. Schiebinger, pp. 183-205. Stanford University Press, Stanford.