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The Genre Evolution Project

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The Genre Evolution
Project
Doing the Research of the Future
Becky Adams, Jon Bakos,
Caitlin Light, Ross Smith
New Material В© 2005
What We Believe
• Innovations in literature are not merely
caused by randomness, or sporadic acts
of genius.
• Cultural phenomena do not occur in a
vacuum.
• The culture can change because of
literature, and literature can change
because of the culture.
Founding Fathers
• Two professors at the University of Michigan
wanted a way to test these beliefs:
Dr. Eric Rabkin
Dr. Carl Simon
Hypothesis
• Cultural phenomena evolve in the same
way as do biological systems. . .
. . . that is, as complex
adaptive systems.
But what are CASs?
Hypothesis Defined
CAS: whole adapts to parts, parts adapt to whole Each
gives the other feedback, promoting change
•
•
•
•
Nonadaptive System:
Simple Adaptive System:
Complex Adaptive System:
VERY Complex Adaptive
System:
Meat Grinder
Radio
Thermostat
Biosphere
The GEP studies literature as if it were evolving in
the same way as a biosphere
Putting the Genre in GEP
• In order to test its hypothesis, the GEP needed
an object to study. We chose…
The American Science Fiction Short Story
Operationally Defined as…
Any story appearing in a self-described science fiction
magazine published in the United States.
Stories under 12,000 words
No serials
Operationally Defined?
• Rather than using the content of the stories to
tell if they are sci-fi, we use the context.
• If the magazine tells us the story is science
fiction, we take them at their word.
• This allows us to see what the aspects of
literature the culture considers to be science
fiction, and to see if these change over time.
Quantitative Study
• Traditional recipe for literary criticism:
– Old man in room
– Pen and paper
• This is all well and good, but what if you
want more than just an informed opinion?
• GEP attempts to study literature
quantitatively, using a set of well-defined
fields and values for its analysis.
Why Science Fiction?
• Dr. Rabkin’s area of expertise
• We like it
• We have a sensible operational definition:
(beginning April, 1926, with Amazing)
fiction that appeared in American SF magazines
• Adequately complex
also….
We have excellent contextual data, such as:
Contextual SF Data
–
–
–
–
–
–
–
precise dating
wide variations in format
observable advertising content
letters to the editor
letters from the editor
Astounding’s “Analytical Laboratory”
circulation figures
SF was born to be studied!
So How Does it Happen?
• University of Michigan affiliation
• Undergraduate and graduate students
• Weekly Meetings
Collaborative effort!
• Sibling groups:
– Michigan State University
– Texas A&M University
– University of Trento, Italy
So We’re Gathering Data… But How?
• Group members are put into reading pairs.
Each pair reads a magazine per week.
• Using pairs helps improve the reliability of our
data by giving readers a chance to discuss and
compare. Objective reading!
• Pair results are then entered into an online
Access database, and checked over one more
time to ensure that nothing is left
blank/erroneous.
Fields and Values
• What we use to code a story
• Extremely detailed list
• Over 30 fields, up to 19 values each
• Many fields have evolved down through the
years
Some GEP Fields
Genre Content
- The element in the story that would make most
readers recognize the story as Science Fiction and
without which the story might not be generally
considered to be science fiction by ordinary readers.
Genre Form
- The basic form, or skeleton, on which the story is built.
Dominant Science
- The science whose workings are central to creating the
narrative world and/or dramatic problem(s).
Some GEP Fields
• Character Count / Dimensionality
пѓ Good example of a field that evolved:
1. Counting Char.
2. Defining Dimension
3. Invention of “1D” Char.
4. Instances “1D” Char.
5. Organization of Instances
6. Defining a Scene
7. Scene Boundaries
The Databases
Our project uses 3 databases that are linked
together:
пѓ Text database detailing information from the
stories, including every incarnation of a story.
пѓ Author database with biographical information
пѓ Context database that includes data about the
magazines, and also anthologies.
We have an additional magazine covers project
that’s examining that aspect of context.
Why an Access Database?
• Access is a relational database, which means
we can have fields whose values depend on
other fields.
• We can also examine several fields at a time by
creating queries within Access. If you want to
study stories from the 1950’s, written only by
women, with alien protagonists and sad endings,
you can!
Getting Good Data
ICR пѓ Inter-Coder Reliability
– Agreement between researchers on codings
– Keystone of our credibility
– Many of our methods serve to increase ICR:
В» group meetings
В» pair discussion
В» layout of instrument
GEP data collection is
complicated – ICR is very
important!
Some GEP Publications
• “Age, Sex, and Evolution in the Science
Fiction Marketplace”
В» Eric S. Rabkin & Carl P. Simon
• “The Medical Lessons of Science
Fiction”
В» Eric S. Rabkin
• “Who Really Shaped American
Science Fiction?”
В» Eric S. Rabkin, James Mitchell, & Carl P. Simon
“Age, Sex, and Evolution in the
Science Fiction Marketplace”
• Looking at:
В» Author Sex
В» Word Count
В» Main Character Sex
В» Genre Content
В» Main Character Age
we discovered…
Differences by Sex
Though Genre Contents in published stories were the
same for men and women, stories differ in many ways:
• Women:
– Shorter stories
– Main char. gender =
50/50 split
– Female characters in
male roles
– Younger main char.
• Men:
– Longer stories
– Main char. gender =
90% male
– Male characters in
male roles
– Older main char.
A u th o r S e x v S to ry L e n g th
W o m e n P u b lish S h o rte r S to rie s
7000
7000
6500
6500
6136
N u m b er o f w o rd s
6000
5500
Author Sex v Story Length
5352
6000
5500
5000
5000
4500
4500
4000
4000
3500
3500
3000
3000
M a le
F e m a le
A u th o r S e x
M a in C h a ra c te r S e x vs A u th o r S e x
Auth Sex v Main Char Sex
M e n w rite a b o u t m e n ; w o m e n w rite a b o u t b o th s e x e s
2
(n = 1 1 3 2 , d f= 1 , X = 1 7 1 .6 6 , p < 0 .0 0 0 1 )
100%
72
90%
80%
70%
56
H av e
F e m a le
M a in
C h a ra cte rs
60%
50%
938
40%
30%
20%
62
H av e
M a le
M a in
C h a ra cte rs
10%
0%
F e m a le
M a le
S e x o f A u th o r
Similarities
• No rapid growth of female authors (to coincide
with growth of feminist movement) in the 1960’s
• The number of women in SF has increased
slowly but steadily since the 1920’s, and our
data show no decline or boom.
A u th o r S e x v D e c a d e
S ig n ific a n t In c re a s e in N u m b e r o f F e m a le W rite rs
Auth Sex v Decade
2
(N = 1 2 0 3 , d f= 7 , X = 4 5 .9 7 , p < 0 .0 0 0 1 )
100%
3
4
18
12
18
27
90%
37
80%
70%
60%
50%
19
F e m a le
152
114
200
125
M a le
134
202
40%
138
30%
20%
10%
0%
1920s
1930s
1940s
1950s
1960s
D eacd e
1970s
1980s
1990s
“The Medical Lessons of Science
Fiction”
• Only 41 stories with Dominant Science
“Medicine” out of 1094 stories that had a
Dominant Science.
–Expected distribution, if all sciences
coded equally? 61
• Medicine only 2/3 of expected result!
Okay, 41 Stories. Reprints?
• Reprints indicate a story’s cultural “fitness” the
same way reproduction indicates an organism’s
biological success.
• Only 5 of 41 stories coded “Medicine” reprinted:
“Flowers for Algernon”
19
“Of Mist, and Grass, and Sand”
17
“The Planners”
8
“The Last Flight of Dr. Ain”
7
“The Miracle of the Broom Closet”
2
What do these
stories have
in common?
Similarities
• 3 of the 5 written by women
• All but last deal with society in which
physician is very strong, almost godlike,
and confirm society’s fearful attitudes about
that power.
Conclusion?
Conclusion
Medicine “…is a matter that science fiction typically
does not want to address, but when it does, it is
disproportionately women who show us the way, who
make clear that the only good doctor is the doctor who
puts his…or her…welfare after that of the patient. The
SF exploration of medicine, in Keyes and Wiener and
Wilhelm and Sheldon, makes us feel that we are
misspending our funds by supporting such people.”
“If one were to read science fiction about medicine
out of one’s common humanity, it would put one on
guard. If one were to read it as a physician, one would
draw one clear lesson: learn humility and service or
society will abandon you…the future of medicine,
science fiction tells us, will be molded not only by the
minds of doctors but by their characters.”
“Who Really Shaped American
Science Fiction?”
• After taking over Amazing, John W. Campbell
announced his intent to increase the depth of
science fiction’s characters. This was to nullify
the criticism that SF was solely interested in
ideas and technology, rather than people.
• The commonly held belief is that he succeeded.
The GEP wanted to test this claim.
The Study
• Examined:
В»Number of 3D characters in SF
overall during Campbell’s career
В»Number of 3D characters in Amazing
during Campbell’s career
• We left a 2 year gap between the date
Campbell took over the magazine and the
date we used to begin our study
В»Accommodate for editorial backlog
P e rc e n ta g e T h re e -D im e n s io n a l C h a ra c te rs v D e c a d e
% 3D Chars v Decade
8 0 s d iffe r fro m 4 0 s, 5 0 s, 6 0 , 9 0 s
9 0 s d iffe r fro m 3 0 s, 7 0 s, 8 0 s
2
(F = 7 .8 6 8 , p < 0 .0 0 0 1 , R = .0 3 1 )
1 2 .0 0
1 2 .0 0
1 0 .1 5
P ercen tag e T h ree-D im en sio n al C h aracters
1 0 .0 0
1 0 .0 0
9 .0 1
8 .6 3
8 .0 0
8 .0 0
5 .9 0
6 .0 0
5 .7 3
6 .0 0
5 .4 6
4 .0 0
4 .0 0
3 .2 2
2 .0 0
2 .0 0
0 .0 0
0 .0 0
30s
40s
50s
60s
D ecad e
70s
80s
90s
Conclusions?
• Not only did number of 3D characters not
increase under Campbell, they actually
decreased slightly overall!
• No more 3D characters overall
• No more 3D characters in Amazing
Campbell didn’t influence the evolution
of SF in the way everyone thought!
The GEP Online
Ann Arbor:
www.umich.edu/~genreevo
East Lansing:
www.msu.edu/~edisonsw/
Well, if that’s all of that…
…it’s coding time!
The GEP Online
Ann Arbor:
www.umich.edu/~genreevo
East Lansing:
www.msu.edu/~edisonsw/
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