On this blog every Tuesday and Friday I write about story techniques, structure, and/or publishing. Comments and questions are welcome. I also have a personal blog, Amy Deardon, on which I write about a variety of topics purely as they catch my fancy.

I've written one novel, A Lever Long Enough, that I'm honored to say has won two awards. In my life BC (before children) I was a scientist who did bench research.

My book, The Story Template: Conquer Writer's Block Using the Universal Structure of Story, is now available in both hard-copy and e-book formats. I also coach would-be novelists and screenwriters to develop their story. YOU CAN CONTACT ME at amydeardon at yahoo dot com.

Tuesday, May 14, 2013

A Study with the Story Template Part One



One of my high-school students, Emily, did a school project using my story template algorithm. Her goal was to examine classic and non-classic stories to find any differences in the story structure. She decided to use just movies since the analysis is quicker, although still not trivial: for each story she broke it into a list of scenes, timed each scene, then calculated percentages of whole for duration and placement. Her definition of a classic was a film that had been adapted from a novel, had one or more sequels, and/or was recognized as the epitome of its genre. Furthermore, the original novel or film must have been made at least 25 years ago (1985 or earlier), since it takes at least about a generation to be recognized as a classic. Non-classics were films in that same time period that did not fit the "classic" criteria. She tried to choose films from a variety of genres.

She chose well-known movies:

Classics:

Charlotte's Web

Prince Caspian

Tuck Everlasting

High Noon

Raiders of the Lost Ark

Jaws

Rocky

Non-Classics:

Heaven Can Wait

War Games

LadyHawke

To analyze these movies, Emily studied the story template and then broke it down into 16 specific testable points. After doing her research, and contrary to all of my expectations, she found a real difference in structure between the classics and non-classics.

15 of the 16 points were present in all the stories. However, 1 of the points was present in 6 out of 7 classics, but in none of the non-classics. This blew me away. When she did a Fisher's exact t-test for binary data on the presence or absence of this one variable in identifying a classic, in a two-tailed test (which is harder to reach significance), she had a p value of 0.03, considered significant. (The p value means that if you did this test 100 times, in 3 out of 100 trials you would expect to obtain these results by chance. Scientific standards typically accept a p < 0.05 to be considered significant, meaning that the scientist is probably measuring a real phenomenon). This result indicates the presence of this one story point is highly correlated to having a "classic" whereas its absence means it is linked to being a non-classic.

These aren't clean statistics since the original project design looked for 16 variables. The likelihood with this many variables is that one might reach a level of significance with one of the variables just by chance. However, 1) none of the other points changed -- they were all present in both classics and non-classics; and 2) this point makes a lot of sense to me that it might distinguish the lasting stories from the throwaways. At the minimum, it seems to be important to remember to include this point. It sure can't hurt.

I'm sure you're wondering what this variable is? Well, this blog entry is already long, so I'm going to save that till Friday. In the meantime, I'd love to hear what you think it might be. Happy writing.

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