Robot Drums

Patrick Flanagan works at the intersection of numbers and drum beats. He uses a pair of controllers — one a Wii remote, the other custom — to send signals into a scripting language that then talks to a Java machine running some code he himself has written:

The Winner of Eurovision

The big winner at Eurovision, again, was the English language. Well, that and the American pop ballad (mixed with the remnants of disco that Europe appears to hold so dear). Just scanning through the preview (see the video montage below) for the performance, English had at least the simple majority (over half).

I missed a few countries that stuck to their own language (and obviously England and Ireland don’t count in any of this), but my rough list is: Bulgaria, Croatia, Cyprus, Estonia, France, Macedonia, Iceland, Israel, Italy, San Marino, Serbia, Spain, Switzerland.

Of those, France, Spain, and Italy were no surprise. Germany and Russia going English seemed interesting. Croatia and Serbia stayed native, but Slovenia went English.

Outside of language, the other curious thing was the countries that didn’t do the pop ballad: Iceland and Switzerland seemed more country, and Georgia sounded like they were from Georgia. (See what I did there?) But, to be honest, the boundary between the pop ballad and the country ballad is pretty fuzzy these days.

And for those who need a cheat sheet for Eurovision, [Buzzfeed has it all](http://www.buzzfeed.com/ellievhall/everything-americans-need-to-know-about-eurovision).

How to Make Things Happen

> If you want to build a ship, don’t drum up people to collect wood and don’t assign them tasks and work, but rather teach them to long for the endless immensity of the sea.

— Antoine de Saint ExupĂ©ry

Thanks to [Schloss](http://schloss.quora.com/Culture).

Morphological Mumbling

I decided to focus the paper I am giving at the International Society for the Study of Contemporary Legend a little less than two weeks from today on a group of twenty treasure legends collected in south Louisiana. The legends range in size from a little over one hundred words to a little over a thousand words in length. Of the twenty legends, fourteen focus on the experience of seeking treasure, four focus on how the treasure came to be located where it is, and two include both the seeking and the burying of treasure (one in that order and one in chronological order).

With that distinction aside, the texts are remarkably similar, and since the two kinds of stories above, the stories about seeking treasure and the origin stories, actually appear in two texts, I think it is best to think of the two kinds as really two components in a larger morphology of Louisiana treasure legends.

Since I am trying to develop a morphology, I decided to label tese two larger pieces of the narratives τ and α. Most readers will be familiar with α as the first letter of the Greek alphabet and also a common symbol for origins. A brief search of the interweb suggested that τ is sometimes used to designate experience, and that was good enough for me. All of this is work-in-progress and so I am open to any suggestions: I just needed some stable nomenclature that also didn’t get in my way as I worked on the legends. I originally used A and B, but the letters of the Latin alphabet are typically used for morphological functions … and at least one schema I worked with had capital letters (A and B), then numbers for variants, and then smaller letters for actions within each component. Too much.

For now, τ has the following *functions*, to use Propp’s term, in it:

A – goto location # woods, well, country
B – given interdiction # don’t talk
C – dig for treasure OR do an agricultural task
D – see spirit

As most folklorists, and other readers of Propp, will note, C should probably be split into two functions: one for digging for treasure and one for performing agricultural task. Often, doing the latter actually reveals the treasure — e.g., in the course of plowing, someone comes upon a treasure — but even then the treasure can be lost again, as it would be in those texts where people dig for treasure.

It’s how to represent this material that I find both fascinating and frustrating. I am on the third, or maybe fourth, complete revision of the table holding all this material and thus of the morphology itself. Every time I come across something new, it shifts columns in the table right or left, or sometimes moves a cell right that causes a cascade of failures that usually results in me seeing where a previous analysis had been in error or not complete.

Scrivener Tips

A number of my graduate students have taken the [Scrivener][] challenge and are finding their writing lives made much easier. Since I feel like there is a whole lot more to this application yet for me to learn, too, I am creating this post as a place to list various tips and usage scenarios that look interesting.

* The first thing that many writers find themselves doing, after perhaps re-arranging the deck furniture (sizing windows, setting the text zoom) is to set up their preferred typographic schema: type face (font), type size, line spacing, paragraph indentation, block quote citation, etc. If that’s the case, then Gwen Hernandez has a nice [run-down][] of how to make that scheme standard for all your new documents as well as how to convert existing documents to your scheme.
* The next thing most researchers in need of citation management want to do is to figure out how to use their preferred citation manager. Scrivener supports BookEnds and Sente out of the box, and it appears that Papers is quite workable. (I am currently testing Papers, having skipped Sente because it requires syncing through its own servers, at an additional cost and because Bookends seems to have developed so slowly. I have tried and tried to love Zotero, but it does not love me back, and so I am going to spend the money to see how well Papers works for me. And let’s not discuss EndNote, which is just too expensive for my regional-public-university-salary-frozen-for-the-past-eight-year’s budget.)
* **CMD + SHIFT + T** is your friend. It allows you to check your progress for a given session, day, or other period you specific. I write Monday through Friday, and my goal is 500 words a day. I have set the pop-up to calculate from midnight to midnight, so if I quite Scrivener, for whatever reason, during the say, then my count for the day is not lost. (It also means that if I leave it open overnight, I don’t get credit for the previous day’s work.) When things are going well, I can get more work done than that — sometimes averaging 1000 words a day at a stretch — but I regard 500 words as a reasonable average. For my own records, I’ll write down the day’s word count at the end of the day in the margins of my calendar.

[Scrivener]: http://literatureandlatte.com/
[run-down]: http://gwenhernandez.com/2011/03/29/tech-tuesday-formatting-tips-for-scrivener-2-x/

Merging Columns in Excel

I am cleaning up an Excel spreadsheet that holds the values for a morphology of twenty treasure legends collected in Louisiana. Building the table (and perhaps future matrix) has been an interesting exercise. As a giant table, I have constantly juggled with adding and subtracting various dimensions or components of the texts: examination of one text will spark a realization that something needs to be included and then, with that refinement, one needs to go back and double-check the other texts to see if the refinement applies to them as well. (It usually does.) As an Excel spreadsheet, it has the benefits of being faster to work with than a Word table, and that’s about it. (The person who invents the truly human-friendly spreadsheet will, I hope, make a decent sum of money — rather like Kevin Brown did with [Scrivener][].)

At the moment, I need to merge data that’s in two columns into a single column, as I realized that *go to* and *location()* were really one thing, what folklorists might call a *function* and what computer scientists might call a narrative *state*. Excel doesn’t make it easy, but here are notes on how to do this next time:

First, **merge the data** without doing disturbing it by *inserting a column* and then entering the following formula in the topmost cell:

=A1&” “&B1

If that gives you the results you want, *fill down.* While all the relevant cells are still selected, *copy* them and then *paste values*.

If you have a series of cells, then the syntax is `=A1&” “&B1&” “&C1` etc.

[Scrivener]: http://literatureandlatte.com

“My Old Man and the Sea”

The new media horizon is at its best when people make beautiful films about things they know and love. “My Old Man and the Sea” is a perfect example of just what can be done: the video and audio are quite good; the editing keeps thing moving along; and the subject matter is allowed to shine in, this case, his full glory, which includes the occasional rough edge of a word or two.

She’s so mad…

A student passed this onto me last semester:

> She’s so mad she’s about to shove a milk bone down your throat and a hungry dog up your ass.

He heard it on a local radio show. It’s not clear if the host is especially good at making some of these sayings up or if he simply has an extremely good ear for picking up on colorful sayings he hears around town.