Jürgen von Beckerath (1920-2016)

This came in from Angelika Lohnwasser:

Prof. em. Dr. Jürgen von Beckerath, 1920-2016

Am 26.6.2016 verstarb in seinem Haus in Schlehdorf/Bayern der frühere Direktor des Instituts für Ägyptologie und Koptologie der Westfälischen Wilhelms-Universität Münster, Prof. Dr. Jürgen von Beckerath im Alter von 96 Jahren. Er war der zweite Vertreter der Ägyptologie in Münster und amtierte von 1970 bis 1985. Seine Karriere verlief nach früher „klassischem“ Muster: Promotion in München 1948, 1952 Reisestipendium nach Ägypten (als erster deutscher Wissenschaftler nach dem Zweiten Weltkrieg), 1955 Stipendium der Deutschen Forschungsgemeinschaft, später Assistent am Ägyptischen Museum in München, 1958 Lehrauftrag für Ägyptologie in München, Habilitation ebendort 1963, 1966/67 Associate Professor an der Columbia University in New York, 1970 Ruf nach Münster als Nachfolger von Walther Wolf. Chronologie und Geschichte des Alten Ägypten waren seine hauptsächlichen Forschungsschwerpunkte. Neben zahlreichen einschlägigen Artikeln (der letzte aus dem Jahre 2003) gehören drei Bücher zu seinen wichtigsten Veröffentlichungen: Untersuchungen zur politischen Geschichte der Zweiten Zwischenzeit in Ägypten (Habilitationsschrift), 1965; die beiden folgenden sind Handbücher geworden: Chronologie des pharaonischen Ägypten. Die Zeitbestimmung der ägyptischen Geschichte von der Vorzeit bis 332 v. Chr., 1997; Handbuch der ägyptischen Königsnamen, 1984, 1999.

 I have found von Beckerath's Handbuch der ägyptischen Königsnamen extremely useful (I was using it just yesterday).

I would like to highlight an article of von Beckerath's which I have found extremely helpful. Jürgen von Beckerath, "Die Lesung von "Regierungsjahr": ein neuer Vorschlag," Zeitschrift für ägyptische Sprache und Altertumskunde 95/2 (1969): 88-91. In this article von Beckerath establishes that the reading of the regnal year group is ḥsbt, not ḥ3t-zp or rnpt-zp. This reading was confirmed in Kaul-Theodor Zauzich, "Das topographische Onomastikon im P. Kairo 31169," Göttinger Miszellen 99 (1987): 83-91.

It was also von Beckerath who pointed out that we really have no evidence that the Egyptians knew about the Sothic cycle before the Ptolemaic period.

It has been at least a decade since von Beckerath was active in the field, but he made some important contributions.

A Lutheran on the Trinity

Hans Fiene is a Lutheran pastor in Illinois. I am disappointed with his anti-Mormon tendencies but I appreciate his thoughtfulness. In this video, however, he makes a point that I have often heard my friend, Lou Midgley, make:

You cannot make a popular explanation of the Christian Trinity of the creeds without falling into heresy. 

From my perspective, the formulations of the creeds tend to be incoherent gibberish, and I appreciate a good Lutheran pastor being able to articulate this. Perhaps there is some common ground we can build on.

How Many Books in a Preexilic Israelite Personal Library?

So how many books did the typical preexilic Israelite own? By books, we mean literary works or works of knowledge, not things like tax receipts and property deeds.

If I had to guess, I think that it would be pretty safe to say that the mode was zero. That means that a majority of ancient Israelites could not read and did not personally own any books. But some percentage of ancient Israelites could read. Some percentage of them did own literary texts or works of knowledge. Again, the absolute percentage need not be large, but chances are that if you were privileged enough to read, you probably wanted to possess something to read.

Unfortunately, we cannot answer that question, but we can get some idea by looking at ownership of literary works in the Neo-Assyrian empire. SAA VII 49-51 are three lists of tablets owned by various individuals in the Neo-Assyrian empire. The texts are somewhat fragmentary, but they typically list the works and how many tablets in the work, and a summary of the number of tablets accompanied by the name of the individual. Taking the entries where the total number of tablets owned is more or less intact in all of the texts, we get the following list (in ascending order by tablet):

• Aplaya owned 1 tablet


• Mushezib-Nabu owned 1 tablet


• Tabni owned 2 tablets


• Nabu-balassu-iqbi owned [x]+2 tablets


• Nabu-shum-[. . .] owned [1]5 tablets


• Assur-mukin-pale'a owned [1]8 tablets


• Shamash-eriba owned 28 tablets


• Nabu-shakin-shulmi owned [x]+37 tablets


• [...] owned 100+[x] tablets


• Arraba owned 185 tablets


• Nabu-nadin-apli owned 188 tablets


• Nabu-[. . .] owned 435 tablets

What is interesting about this list is the spread. About a third of those who owned tablets owned only one or two. About a third of them more than dozen tablets. About a third owned more than a hundred tablets. Remember these are literary texts or works of knowledge (the ancient equivalent of scientific literature). The average of those whose numbers are completely intact is 120 tablets.

I would expect ancient Israelite personal libraries to show a similar spread. Some would only own a work or two. Some would have several. What is somewhat surprising is that multiple individuals had extensive libraries, the equivalent of dozens of scrolls. We should suppose that ancient Israel would be the same.

It would be nicer to have a larger sample size. It would be nice if we had equivalent lists from Israel. But based on the information we do have, highly literate individuals with large libraries are known from pre-exilic Israelite times.

More on the Gospel of Jesus's Wife Forgery

Apparently Karen King, who introduced the papyrus fragment of the Gospel of Jesus's Wife has admitted that the document is probably a forgery.

I noted evidence for it as a forgery four years ago. Interesting that the forger seems to have been an Egyptology student at one time.

Some Perils of Mathematical Modeling

Mathematical models can be great. They do, however, have some limitations. Suppose, for example, that you are trying to predict some data that you suspect has some mathematical relationship and you want to know the future behavior. A mathematical model might be useful to predict the future results of the data. Your predictive abilities will only be as good as the model (or formula) that you are using. Presumably, if your model accounts for past data, it should work for future data as well. We'll keep this fairly simple.

Lets say that you start with an initial condition and it starts at zero. The next data point to come out is a one. So at x = 0, y = 0 and x=1, y=1. This gives us a nice formula: x = y. We are ready to predict the future. Our guess is that when x = 2, y =2. Our graph of the function looks like this:

This provides nice steady increase. If it is a graph of your investments, you will not be getting rich very quick, but you might not be getting poor either. If it is global temperatures, it might cause some concern. If it is crop yields per square meter, then it is steady and predictable.

But when x =2 comes out, it turns out that y = 0. Our prediction was off by 2. Our graph comparing our prediction with actual results looks like this:

This looks like a simple problem to fix. We simply change our equation to y = -x^2 + 2x. This equation also works for the first three values. Our graph comparing our prediction with actual results now looks like this:

Those curves are pretty close. We seem to be on the right track. Let's expand our prediction graph and predict what is going to happen in the future:

We predict that the next point on the graph will be -3. It looks as though the graph is going increasingly downward. If this is your return on investment, then it looks like you better get out of the market now. If this is global temperatures, then stock up on winter clothes.

In fact, the next point is -1. Again, we are off by 2. Out graph comparing our prediction with actual results looks like this:

This is a not so easy fix. We change our equation to y = (x^3)/3 - 2x^2 + 8x/3. This gives us the following graph:

This is not exact but it is close. If we look down the road, we can predict the following:

So if this is our investments, we should just ride it out because things look better down the road. If it is global temperatures, then hang on because things will get a lot hotter really quick.

When the next number comes in, it comes in as 0, exactly as our model predicted:

Surely, we are on the right track.

The next number, however, comes in as 1 rather then the 5 our model predicted.

Something is wrong again. If we look at our various model graphs, we can see that they end up going all over the place:

Clearly, while each of these graphs works for a bit, they all fail in the end. They all end up flying off on a tangent. This is even more clear when we look at the long term trajectories:

All of these graphs were based on the actual data, but they differ markedly in their projections (all of which turn out to be wrong in the long term). Remember that the extreme models accounted for almost the same range of data, but after a point made widely divergent predictions.

So, one take away is that the models, at some point, break down. We could make the models much more complicated and account for the first twenty points but they would then still go wildly wrong. The general point would remain. If you are looking at a fluctuating phenomenon and suddenly your model becomes monotonically increasing or decreasing (that is, it stops fluctuating) then that is the point where your model probably has broken down.