Fang the fauna

This is a verse collection with a back-story.

This work had its origins in a creative writing workshop that I was engaged in, probably in 1986. We were discussing commercial tendencies, and with an eye on the looming 1988 Bicentennial, I invented a fictional work, which I dubbed:

Gastromania Australiana, or
The Bicentennial Rhyming Cookbook.

That deliberate stalking-horse, that epitome of crude commercialism fed the debate and gave us a good laugh before we moved on, but that night, a few rough verses crept out, and a week later, I shared them with the workshop. We had another laugh, and again moved on. At home, the scribbles went into the bottom drawer, but in the summer of 1986-87, I had a thought.

As a classically-trained biologist, I knew how to illustrate with stipple, and I would sit in boring bureaucratic meetings, as pompous oafs droned on, wasting time. To keep myself sane, I drew stippled doodles, usually trying to create a nicely shaded sphere, but somehow, as I drew, each of them acquired textures, eyes and appendages, like this one on the right.

More importantly, I saw that the clowns all watched intently as my doodles emerged, gaining character, and slack-jawed, they forgot to drone. An intelligent colleague, a real artist, saw this, and sat opposite me, drawing scenes. We found that by each of us settling between two twits, we could mute four of them, leaving the intelligent people to deal with issues uninterrupted.

I ended up with lots of drawings, and some of them matched my verses, so in mid-1987, a limited but illustrated edition (one copy) of Gastromania Australiana emerged. For reasons that I won’t go into, that single copy was instrumental to my being awarded a post, managing a large creative staff, but the single copy was filed on my shelves and forgotten.

Early in 2022, I noted on Facebook that finding a mosquito in your tea was less bad than finding a fly in your soup, a friend called Nisaba asked if I swallowed the mossie, I said that I had not, and mentioned that I had once written some verses on eating mosquitoes, and having, as I approach advanced middle age, sorted most of my backburner books, I turned to the verses again.

I revisited, revised, refurbished, rewrote them and augmented, adding verses and new illustrations, so now here it is, with a more catchy title. Thanks fellow writers in the workshop, thanks boring drones, thanks Nisaba, thanks Rotring and Artline who supply my pens, thanks to family and friends who have giggled.

Now here's a taste of seriously bad taste, within the meaning of the act.

First, a small calming foreword for the PC brigade: 

Friends who know my email address can request almost the entire thing, as a 17-page 2 meg PDF. I'm not at all sure that this one is commercial, but it would make a great stocking-stuffer, and that's how I plan to pitch it in a few weeks, once I have ironed out a couple of scansion issues.

Behind the Easter bunny.

 I am currently working on what I refer to as my four last songs, the five books I want to get out of the way before hanging up my pen.

Of course, when I talk about stopping writing, my friends react like the Canterbury Pilgrims did, on their first day out:

Nonetheless, I forge ahead. Now about the Easter egg, one of the works is The Bruces’ Dictionary of Phrase & Fable: which is subtitled the origins of mythology and a mythology of origins.

From this, I have drawn the entry on the Rabbit:

A small and over-sexed mammal. They are rare in some areas as the female rabbits prefer to mate with roosters, which is the origin of the ‘Easter Bunny’ legend. To achieve this result, a rabbit must first associate with hens, to acquire a suitable smell, after which they move in with the rooster, but it does not last, for a fowl and his bunny are soon parted.

Another of the works being finalised is a selection of verse called Let's Fang the Fauna, and given the style, I considered using the pen-name Ogden Gnash, but I decided I wanted people to know who was doing it to them. Anyhow, here's a rabbit-related sample:

The finest perfumes in the land
Will make some noses runny;
The dinner that the hawk has planned
Is bad news for the bunny.

Many rabbits have the luck
To not become our meat
For almost every doe and buck
Has lucky rabbits’ feet.

The rabbit, served in various ways,
Has culinary merits.
Eat rabbits for a hundred days,
Then take a dose of ferrets.

By the way, there's an Easter egg buried here...

Happy Easter!

Oh yes, there will be more on this in the next entry. Here's a link.

Statistics

I'm picking a few bits out of my next book but three, Science is Like That.

Lord Rutherford is supposed to have said “If your experiment needs statistics, you ought to have done a better experiment”. Yet statistical analysis reveals the underlying truths in complex situations, the sort of messes that true physicists used to shy away from. It spoils the story a bit, but Rutherford once sat in on Horace Lamb’s lectures on mathematical statistics to improve his analysis of alpha particle deflections, a task which demanded some serious statistical work.

Once upon a time, simple patterns were solved by simple analysis, with simple mathematics revealing the laws that lay beneath the patterns. By the 19th century, nothing was quite so simple any more. The patterns were more complicated, and even physics needed statistics to help deal with the large masses of data. Most medical and biological research, all social science research and many other areas of modern scientific enquiry can only work by using statistics.

While modern statistics owe more to Karl Pearson, R. A. Fisher and J. B. S. Haldane, the first steps were taken by Adolphe Quételet, and then carried forward by Florence Nightingale. Quételet was a brilliant mathematician, who learned about probability from Pierre-Simon de Laplace while studying in Paris, before he returned to his native Belgium to run a new observatory there. While the observatory was being built, Quételet began exploring the ideas of ‘social physics’ and ‘moral statistics’.

He saw that there were many predictable sets of data. Crimes, suicides and marriages all involved individual free choice, but they happened at predictable rates in different age groups, giving him the starting point for his ‘moral statistics’.

Sad condition of the human race! We can tell beforehand how many will stain their hands with the blood of their fellow-creatures, how many will be forgers, how many poisoners, almost as one can foretell the number of births and deaths.
—Adolphe Quételet, Treatise on Man, 1835.

Florence Nightingale makes an excellent case study, because while we usually know her as a nurse who gained fame during the Crimean War, the Lady of the Lamp, few people are aware that after this middle-aged spinster returned to London in 1857, she used statistics to argue for better nursing.

First, she prepared a pamphlet, based on the report of a Royal Commission, about the Crimean war campaign, where Britain and France had fought Russia. Nightingale wanted to rally public support for nursing reforms.

The pamphlet showed where the problems lay, and her Mortality in the British Army, featured the first use of pictorial charts to present data, those charts with tiny wheat bags, or oil barrels or human figures lined up like so many paper dolls. She hammered away again in 1858 in her Report on the Crimea:

It is not denied that a large part of the British force perished from causes not the unavoidable or necessary results of war…(10,053 men, or sixty percent per annum, perished in seven months, from disease alone, upon an average strength of 28,939. This mortality exceeds that of the Great Plague)…The question arises, must what has here occurred occur again?

In 1858, Nightingale was elected to the newly formed Statistical Society and turned her attention to hospital statistics on disease and mortality in Britain. You could never, she said, discover trends unless figures were recorded in the same way. She prepared a plan, published in 1859, for uniform hospital statistics. Her aim was to compare the death rates for each disease in different hospitals, which could not be done without a standardised recording system.

Others could also be counted as part-founders of statistics. John Graunt published his Observations on the Bills of Mortality of the City of London in 1662. This work has sometimes been attributed to Sir William Petty, but George Udny Yule showed by statistical analysis (how else?) that the sentence length in Observations did not match known samples of Petty’s writing. Yule turns up again in chapter 5 (but you may have to buy the book to find out about that).

Graunt’s figures became the basis of the first life insurance tables, but he also revealed that for a small fee, a death from “French-pox” (syphilis) could be listed as “consumption” saving the family of the deceased much embarrassment, while hiding a medical truth. Before the 19th century, statistics were just numbers describing the state of a nation, and this is what Mark Twain had in mind when he spoke of “Lies, damned lies, and statistics”.

After 1860, statistics began to take on a whole new meaning, with a statistic becoming a summary figure for a large number of measurements, a way of getting a handle on complex data. To experienced eyes, the mean and standard deviation of a set of measures is a quick summary, though lay people may still say statistics cannot be trusted.

The simple fact is that figures don’t lie, but liars can figure. “Statistics” always need to be looked at carefully, but the use of statistics in science is fully justified. Statistical analysis can reveal such things as Burt’s fraudulent work on twins and inherited intelligence (chapter 9 of the book), or Mendel probably massaging his data, where he faked his data. Statistics can also reveal amazing patterns, laws and truths.

Statistics would end up being the glue which tied together evolution and genetics in the 1920s, helping biologists to understand what was going on in large populations. In time, ecology would absorb pattern analysis as a powerful tool, just as numerical methods would find a place in biological taxonomy and classification. Tied in with this were tests of significance in  sets of results, tests which provide an estimate of how likely numbers are to mean something.

It took statistics, wielded by epidemiologists, to prove what people suspected in the 19th century, that tobacco causes lung cancer and other diseases. You can trust statistics, if they are properly used. Mind you, in the data set <1, 1, 1, 1, 2, 2, 2, 3, 3, 4, 10>, the mean is 3, the median is 2, and the mode is 1—and the average statistician won’t tell you about that!

Most modern scientific advances owe a great deal to statistical analysis, often in the form of correlation coefficients. Now if I can claim any special professional expertise aside from story-telling, it is to be found in the application of statistics, and in particular to the honest and dishonest uses of such statistics. I used statistical analysis to catch my frauds.

But that's another story...

Leibniz’ different base

This is a selection from a new book, Science is Like That, which is yet to find a publisher.

I’ll teach you differences.
—William Shakespeare, King Lear, I, iv, 90.

They say Gottfried Leibniz taught himself Latin when he was eight, and by fourteen, he could read Greek as well. We may as well believe this as not: these legends of precocity in scientific greats are as tenacious as any urban myth. It matters little if Leibniz taught himself Basque while hanging upside down like a bat at the age of two: what really counts is what he did later on.

The son of a professor of moral philosophy, Leibniz was interested in the mathematical side of philosophy. In his lifetime, he introduced the use of the dot to indicate multiplication, popularised the decimal point, the equals sign, the colon for division and ratio, and the use of numerical superscripts for exponents (like x² and x³) in algebra. We also owe the elongated sigma for summation in calculus, and the way we use the letter d in differential calculus (as in dy/dx) is his idea also.

He and Newton argued over who invented calculus, but whatever else Newton did, he never designed a calculating machine as Leibniz did. Only Blaise Pascal had done so before Leibniz, and Charles Babbage did so later. Leibniz’ design was used in building the first totalisator (also called a tote or pari-mutuel, a machine used to manage betting on horse races), because it could multiply and divide.

Leibniz wanted to create a united Europe, even before Germany was a single nation, and long before anybody dreamed of the European Union. In the end, he was librarian to the court of Hanover, but when the Elector of Hanover went off from there to England to take up his new throne as King George I in 1714, Leibniz was left in Germany, presumably because of his disputes with Newton.

Whatever the reason, he was definitely left behind, and he died a couple of years later, leaving a ‘sleeper’ in the form of a letter written to the French Academy of Sciences in 1701, in which he outlined the binary number system which is used by all modern computers.

I enclose an attempt to devise a numerical system that may prove to be entirely new. Briefly, here is what it is…By using a binary system based on the number 2 instead of the decimal system based on the number 10, I am able to write all of the numbers in terms of 0 and 1. I have done this not for mere practical reasons, but rather to allow new discoveries to be made…This system can lead to new information that would be difficult to obtain in any other way…

Talking of bases, there is a conundrum that depends on readers understanding the significance of the apparently erroneous sum: 6x9=42. (This will only make serious sense to people who have read the works of Douglas Adams, especially The Hitch Hiker’s Guide to the Galaxy and its successors.)

Something over two decades ago, I observed on an Internet list that the relationship 6x9=42 is true if the calculations are performed in base-13 notation. A list member, known only as Merlyn, noted that there is a pattern to be observed. If we take “six times x = forty-two,” and vary the value of the base, we find a number of values of x which satisfy the statement, and these form a pattern when we examine both x and the base used. Six times x equals forty two is true when x is:

5 and the base for the calculation is 7;

7 and the base for the calculation is 10;

9 and the base for the calculation is 13;

11 and the base for the calculation is 16;

13 and the base for the calculation is 19;

15 and the base for the calculation is 22;

17 and the base for the calculation is 25;

19 and the base for the calculation is 28;

21 and the base for the calculation is 31;

23 and the base for the calculation is 34;

25 and the base for the calculation is 37;

27 and the base for the calculation is 40;

29 and the base for the calculation is 43…

The pattern continues beyond that, and it is an elegant pattern. Explaining it requires finding a formula for each of x and the nominated base in terms of its order n, in the pattern. These days, most computing is based on binary (base 2) or hexadecimal (base 16) numbers, but we didn’t start out that way, because we have 10 digits on our hands (old sawmillers excepted, sometimes).