Renaissance Artists in a Half-Shell

Today’s comic provoked an awful lot of discussion on the forums, the LJ feed, and in my inbox over the respective notoriety of the various turtles/artists.

I got the percentages in the graph through Google. But direct Google comparison of turtles and artists has the problem that the artists seem to turn up quite a bit more material. There might be many reasons for this, but in creating the chart I decided to assume a priori that the ninja turtles and the Renaissance artists were, on the whole, equally notorious. I’ve seen merchandising for both — Ninja Turtle bedsheets and renaissance-artist-themed ceilings, so this is obviously a fair assumption. Then I used Google to find the respective notoriety of each turtle/artist with respect to their contemporaries — searching for [artist name] Renaissance, summing the total results, and getting each as a percentage. So Leonardo [da Vinci] takes up about 57% of the artist results, Michelangelo [long Renaissance name] takes up only 13%. Then I did the same thing for the turtles, seaching for [turtle name] Ninja Turtles, where Leonardo is again the most notorious, but by a smaller margin (47%). So the pie charts compare the notoriety of each within his group. Donatello gets an 18% share among the turtles but only a 3% share among the artists, so his ratio was 85% turtle : 15% artist. Michelangelo’s was 18:13 = 57:43. Michelangelo is more turtle than artist on the chart because while he’s popular among the artists, he’s more popular among the turtles, and we’re assuming that on the whole the turtles are as notorious as the artists.

Sure, I could’ve gotten all subjective about it, and said “but when I hear ‘Michelangelo’, I think of David before they think of the nunchucks,” or “Raphael is more a turtle than an artist in my mind,” but that’s a dangerous road to start down. Once you start letting your personal biases interfere with serious scientific research like this, it pollutes your data. And that kind of subjectivity not only changes the whole attitude of your research, it affects your project in unpredictable ways. The polluted data starts seeping out into other projects — infecting them, if you will — and creating these unscientific monsters, half natural phenomenon, half human bias. Fleeing the scientific community that shunned them, they seek solace underground, searching for results outside the establishment, delivering truth and justice as they see fit, living off delivery pizza. And that’s just the beginning.

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