Big Pictures are Made of Small DetailsPosted: November 14, 2014
— Lee G. Broderick (@LeeGBroderick) November 8, 2014
The above Tweet was made in response to a presentation which explicitly criticised the sweeping generalisations made by climate change models at the recent Association of Environmental Archaeology Conference, held in Plymouth. Billed as ‘The Big Picture’ the conference actually featured a number of papers dealing with Big Data. Some of these research projects were fascinating and its an area of academic enquiry that’s only become available to archaeologists recently, as computers capable of dealing with large amounts of data become widely available and archives of data are accessed.
Being an environmental archaeology conference held in a geography department, it was perhaps inevitable that climate modelling would have been a theme of some papers. It struck me though, that climatologists are coming at the problems from a different direction to many archaeologists. A warning that broad models might mask some stories is superficially fair but also, importantly, misrepresents what a model is for. Climate modellers, in particular, and perhaps some palaeoecologists too, are interested in modelling climate change as a way in which to understand future patterns as much as past ones. This means that they have to understand the differences from one valley to the next if they are to get an accurate grasp of the story. As they get more data, they struggle to redefine their models to accommodate it.
Either side of the conference, I’ve been working on an assemblage from the Oyo Empire, in modern day Nigeria. The first day back in the lab after the weekend I performed the kind of eye-roll and exasperated, irritated sigh that will be familiar to many zooarchaeologists upon finding human bone in their material.
It’s always a source of potential unwanted problems getting these gangly bipedal mammals in your assemblage and the usual frantic discussion with the site director ensued with the predictable and routine answer of ‘no, there shouldn’t be any humans in it’. Well there are, but why?
Closer inspection of the 3rd metacarpal responsible for my vexation revealed small puncture marks at the distal end consistent with what might be made by a small dog or jackal if it were to pick the bone up and move it (not that I’m implying that small canids might deliberately sabotage future archaeology sites). Here then, is one possible explanation for human bones ending up in a midden. It’s a small part of the story on this site but it’s a part of it, nevertheless – an episode in the life of the site for which we have few other clues.
Archaeologists have got better at combining different types and scales of evidence to understand sites. This is probably driven in part by an acknowledgement of the weaknesses in the archaeological record but its a problem that other disciplines are perhaps only now beginning to worry about. My own presentation at AEA 2014, I hope, epitomised this approach (feel free to criticise me in the comments below!) by combining geomorphological, stable isotopic, zooarchaeological, ethnoarchaeological and landscape archaeology data, complemented by regional palynological studies, to understand the relationship between human settlement and subsistence patterns and the environment through four millennia in Central Mongolia.
The point is though, that whether I’m discussing bone-moving agents in West Africa or shifting settlement patterns in East Asia, there comes a point where some portion of the assembled data doesn’t fit the model. That doesn’t mean you throw the model away and start again – this is precisely what models are made for.
Perhaps modelling climate change is different – our needs for doing so might well be – but in archaeology we do not, or at least should not, seek to create general models which explain everything. If everything fitted it, either that would mean that the world is a very boring place or else that the data are wrong. The point of a model is to highlight inconsistencies. These aberrations in the data are the twists in the plot – the small details that make the big picture interesting.
There is a place for sweeping generalisations and there is a place for fine detailed analysis. Both should exist side by side, testing each other to form a cohesive tale; trying to force both together into a single strand would be like expecting a student’s 500 word summary of War and Peace to be in any way comparable to the original. It misses the subtlety of the little things as well as the sweeping grandeur of the big picture.