Friday Seminar Series: Continuity

Dear Readers,

As is my custom on (your) Fridays, I have prepared a summary of one of my CHRN/AUG 100 lectures. This week, we'll talk about "Continuity." This one is a little bit shorter than most, because there is typically a discussion component to this class.

Always,
Dr. John Skylar
Chairman
Department of Anachronism
University of Constantinople

Continuity

Last time, we talked about how to analyze sources, how to understand them in context, and how to take questionable sources and still obtain information from them. Continuity is a related topic. Now normally, "continuity" just means a consistent, unbroken quality of something. In the context of Anachronism, continuity means establishing such a connected, unbroken story.

The information that we get from the Augury Department comes in bursts, as we've talked about before. That's because augurs have a challenging job; the machinery, even when it's in its best repair, gives them short bursts of unconnected data. It is to their credit that they even manage to figure out what data is contemporaneous at all.

It falls to the anachronist, therefore, to figure out the order to the contemporaneous packages of data that he or she is given by the augur. This is one of the trickiest--and most controversial--parts of our work. If I have two data sets, it takes painstaking analysis to be certain that they are even from the same time stream, let alone to propose an order in which the records were produced. With the neo-Aegean work I have done lately, this comes through with special clarity. Those records speak of gods and men, and are the entertainment writings of a dark age maritime society. Likewise, many records from Earth's Ancient Greek period are entertainments from a dark age maritime society. An anachronist not paying sufficiently close attention might place a neo-Aegean dataset into the era and time stream of one of Earth's Ancient Greek societies, and not even realise his mistake until after publication. An embarassing situation, to be sure.

So how do we get around these kinds of pitfalls? The first and easiest way is to treat each dataset as if it is independent of every other dataset. Come up with names, unique identifiers, characteristics, and analyze everything in a vaccuum first. But do not stay in that vaccuum! Once you are sure that you understand the ins and outs of your original dataset, you have found the clues for the next step. These are subtle things, things about the past and future of your dataset. News articles are rare in the world of the anachronist, as only certain periods kept records of that quality. But there are still hints; past wars, past events. From those references, you stitch the pieces together.

There are pitfalls here too. It's important to remember that what you're saying is only a possible association. There is a lot of time out there, my students, and not all of it is interconnected. To say that one thing happened before another might not just be wrong, in that they happened simultaneously or in the reverse order, but might be wrong in that they are from completely divergent time streams! So, at first we speak only of potential "association" between datasets. The clever anachronist makes correlations and reveals those to the world. This is the second step of establishing a continuity: the construction of a map of correlations between your various sets of data.

The last step is to actually add an order to these events. To be able to do this is often a once-in-a-career event. It requires not only correlations, but correlations of events that can only have a cause-effect relationship. The simplest example is one where you have an account of a battle at a certain place in a certain time, then a record which makes reference to that battle, and to its outcome. Then you know that the battle was a branch point in the timestream in the first dataset, and the second dataset is the branch where a specific outcome occurred. Of course, it's much more complicated than that, but the example should show you the principle.

To re-cap, the steps are as follows:

1) Establish the data with reference to itself (internal consistency)
2) Establish correlations with other data sets (correlation)
3) Establish causality arguments (causality)

Remember those steps!

The final point I will make is that you have to be careful not to let your time-normal memories interfere with your work in establishing a continuity. The time-normal person you were is not the person you are, and those memories may be faulty, or the differences between your time stream and your data's time stream may be too subtle for you to notice. If you fall into that trap, then you're already lost, and this seminar was pointless for you. So watch out!