Tuesday, July 8, 2014

Coding Systems in Zooarchaeology

I've analyzed fauna on three continents, and I've worked with zooarchaeologists from a variety of academic and national backgrounds. We all have some system for coding fauna, that is, for quickly characterizing attributes of individual specimens, so the data can be used for quantitative and qualitative analysis.

Coding systems can be handed down along academic lineages. I use a system based on Chris Szuter's. I never worked with Chris, but as a young graduate student, I worked with older students who mentored me using the same coding system that they had learned from Chris when they themselves were young graduate students and she was the mentor. I'm currently working on fauna from the Marana Platform Mound site, and much of the analyzed fauna is in Chris's code, since she was the first to work there.

Chris Szuter's system influenced a generation of Southwestern faunal analysts, and it's easy to see how coding systems can become regional. Faunal analysis requires what is essentially an apprenticeship: you need to work on real archaeological bone with an experienced supervisor in order to master the skill.* There are a limited number of faunal analysts teaching in large graduate programs, and they influence many students, both in academia and CRM; their influence is often focused in particular geographic regions. This, for example, is why my coding system was influenced by Chris, even though my approach to zooarchaeological research in general was inspired by my graduate advisor, Mary Stiner. Mary's work was/is my research foundation, but she works in a different part of the world, so I use a Southwestern coding system while applying Old World research questions.

When I code, I use a spreadsheet rather than a database (or an index card!), and for each identifiable specimen I include information on taxon, bone, portion of bone, side, fusion, burning, type of breakage, weathering, non-human animal modifications (like rodent gnawing or digestive marks), human modifications (like cut marks or manufacturing), non-human natural modifications (like calcium carbonate buildup, or staining), length, and weight. For certain bones, I collect metrics. I fill out my Excel spreadsheet with simple alphanumeric codes that are easy to remember and understand, such as "fem" for femur, or "cal" for calcium carbonate buildup.

The only major difference between my system and Chris Szuter's is that a) I don't use numbers (like "47" instead of "fem"); and b) I use a landmark system for portions (for example, noting that I have the distal, medial condyle of the femur, rather than a more simple "distal portion").

My system results in high-quality data for each specimen, but each category of data collected adds seconds - even minutes! - to the overall time it takes to code each bone. When I work with large collections, like those at Marana Platform Mound, it's just too slow. I need to find the optimal trade-off between high-quality data collection and speed, so I can get a sufficiently large sample, but still have the data I need to answer my research questions.

My compromise has been this: I don't measure the length of each bone, nor weigh each individually (those are two tasks that add a lot of time to the process). I do weigh the bag as a whole, however. I also move the columns for rare traits to the far right of my spreadsheet, and I only tab over in that direction if the bone requires it. For example, I seldom find carnivore gnawing, so the "non-human animal modifications" column is on the far right. Similarly, 95% of the bones are weathering stage 1, so I only fill in that column if the bone is unusually weathered.

These may seem small changes, but they double my rate of data collection.

I'm really interested in other faunal analyst's systems. Please share yours! I'd be happy to post my full "coding sheet", if people are interested.

*Yeah, I know some people think they can pick up faunal analysis with a few books, a scanty comparative collection, and pure will. Trust me, they can't. Yes, we can tell the difference.

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