Sometime in
the late ’70s, MSc student Dave
Marmorek, now Lead Scientist and Director
of ESSA Technologies Ltd, an ecological and social
systems consulting company in Vancouver and Ottawa,
came to me to announce a discovery. His discovery
was not about the lakes he studied, but
about how to study them.
He wanted
to know how lakes “work” as
ecosystems and how lake acidification affects
plankton. He collected many hundreds of samples of
water from a range of depths in a set of
experimental cylinders in a lake
to help him find out.
In one of
many sets of analyses,
Dave compared all those samples
chemically. Crunching that enormous
data set was one way to answer his question.
Each chemical analysis of each sample took
time. Switching from one sample to the
next took time. Organizing and
keeping track of all that
took more.
Everything
took time, so organizing
and managing his
own time had to
be a key.
♥
Before
I tell you about Dave
Marmorek’s discovery, I need
to tell you something about science.
Imagine him doing all that, over and
over and over again, day after day,
working his way through the jars
for the umpteenth time.
Imagine how
boring it
could
be.
I used to tell
undergrads who thought
they wanted to be scientists that
if they didn’t love working out
how not to be bored,
they shouldn’t
try.
They’d hate it, get bored,
make mistakes, and
vanish in black
holes of frus-
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Maybe
you have to be
nuts to be a scientist, because
‘normal people’ can’t stand doing the
same thing over and over and over
again, precisely the same way,
hundreds or thousands
of times.
As Dave
worked out his time
problem with small changes
in procedures, the work went
faster and more accurately, and
was far more enjoyable. Thou-
sands of scientists make dis-
coveries like that.
My
point here is
that I think what
Dave discovered that
day was how not
to be bored.
They say
“Pile it higher & Deeper”
about the PhD, and there’s a lot of
truth in that. Over and over, and it does
seem endless, we do the same things, as
nearly as we can the same way,
almost ad infinitum.
If we can’t
get computers to do it,
that is. Back then, computers
couldn’t look through microscopes
or analyze samples automatically like
they can now, so Dave did it the only
way there was: painstakingly, by
hand, one after another.
What was Dave’s discovery?
What set the
world on fire for him that day?
What made us glad he discovered it?
What was earth-shaking
about it? Why?
It’s simple.
Dave realized he
didn’t like to be bored
and did something
about it.
By breaking long,
complex tasks into sets of shorter,
simpler ones, he worked faster, got better
data, stayed sharp and attentive,
and had a good time.
They don’t
give Nobel Prizes
for discoveries like that.
But they might give prizes
because of them.
Dave saw that
as something worth cele-
brating and I did too. He made an
assembly line out of his work and manned
all the stations. It was almost as if Dave’s
body was a robot and Dave was
controlling it.
If he did
just one kind of thing at a
time with full attention, his robot
could attend fully to the work and leave Dave
free to reflect, somehow, on other things. Plan
things. Imagine things. Catch errors.
Improve procedures. Other
things.
When Dave
exercised his thinking, imagining,
reflecting self, that made him a creative
scientist. Exercising his robotic self made
him a good technician. Until he was
a good technician, he didn’t have
time to think, imagine,
or reflect.
Escaping boredom
was the key to his discovery.
Here’s what Dave says about it now:
“when I saw each step of the work
as part of a dance, it became fun.
I attended to the thing I was
doing, then danced on
to the next.”
A little later,
Glenn Sutherland had a
similar revelation. He was an MSc
student in my lab at the time, then got a PhD in
advanced mathematical and statistical modeling
of ecosystems, worked at ESSA for years, and is now
with Cortex Ecological Consultants. He is an award-
winning composer of symphonic music. To
celebrate his revelation, Glenn wore a
T-shirt declaring SLAVE! when
he experimented.
According to Glenn,
wearing his Slave shirt when he
did slave work reminded him that he
was both the robot and the scientist, and
both had to do well. Glenn’s cheap trick helped
him make that happen. It sounds kind of schizy
to say it that way, I know. Scientists “should”
be more rational and not have to play tricks
on their own multiple personalities with
T-shirt labels. We all know that
and it’s true.
Scientists like
Dave and Glenn are rational
enough to think up tricks to fool them-
selves into learning action patterns that work
better than the automatic, inefficient, error prone,
unproductive, habitual ones they want to break.
They don’t like boredom, mistakes, or taking
“too long” to do things that “should”
be quick and dirty.
An added
benefit of Glenn’s T-shirt
trick was that every one in the
lab could see whether he was
scientist or a slave at the time
and respond to him accor-
dingly. As a social
signal, it worked.
Early in his
spatial memory experiments,
before he had automated the worst
of the Slave work, he had to do so many
things during one minute out of every
10 minutes for hours at a time, that
no one else could say or do any-
thing to distract him.
But only
if he was his SLAVE
at the time. Otherwise
it didn’t matter.
That is the nature
of experimental science, boring
and repetitive as it is. It is a creative
human venture as well – – exciting and
beautiful to experience when it works
well. What about dance, sculpting,
choreography, or anything else?
One thing I
learned by working in
Experiments, a dance production
expressing the essence of scientific creativity,
is that what I just said about experimental science
applies just as well to dance. I hinted at some of this
in a story about my daughter Susan learning to
dance and our learning to talk about that
over the phone. Here I will flesh out the
idea a little more.
Take
repetition
and precision, for
example. And take
chaos.
Imagine three
dancers rehearsing seriously
for a year, under the guidance of a chore-
ographer and a team of others who know their
stuff. Dramaturge, costume designer, sound, video,
and lighting experts, publicists, scientists to give
feedback and suggest new ideas, and several
investors such as the Government of Canada.
All want a miracle of precision, beauty,
and meaning conveying something
significant about science and
art, and that is a tall
order.
What actually
happens in rehearsal
studios?
You’d have
to ask Gail Lotenberg and the dancers
for the real story. I’m no choreographer or dancer
and haven’t been through this before. But I’ve gone to
rehearsals, talked back and forth on the phone with
Gail, responded to a million emails, and
observed the evolution
of Experiments.
Here are a few things
worth thinking about. It is crystal
clear to me now that when Gail first imagined
Experiments, she didn’t know what she was doing and
knew it. She had good ideas and some survived to the final
production. Most were vague, half-formed, and unworkable
in practice, just as they would be for scientists at that stage.
Ideas evolved as she explored them, and that is also true
of scientists. She tried other things, dancers suggested
changes, or scientists didn’t get it and she returned
to the drawing board. Sometimes we didn’t
get it when Gail didn’t get it and the
production grew richer and
more real as we
worked it
out.
Dance
productions, scientific
experiments, and careers
evolve that way.
Even
the best of us
learn what we are doing,
each time, by doing it. Also like
scientists, dancers improved things
accidentally sometimes by making
mistakes, then the mistakes
became new standards.
Ideas evolve. Possi-
bilities emerge. Things flow
into other things that they
didn’t flow into before.
This happened
for a year in the rehearsal
studio, not that dancers need years
to practice moves. They don’t. But if any-
one suggested something different, Gail
usually considered it, they tried it
the new way, and consi-
dered it some
more.
It astounded
me that they could discuss
specific moves made months or
years earlier and apply them in
new situations. What they needed
the year for, I think, was to ‘get’
what they were doing deeply
enough to do it well.
Repetition, precision, and chaos.
The blocks falling in this photo remind me of
unpredictability in the real world: accidents,
lives changing suddenly, new realities,
especially during transitions. Chaos.
That is what the scientists
on the team study in
their work.
Look again at
Darcy McMurray, the dancer
in the photo. Imagine being her in the
studio, live, Vancouver skyline vaguely in
the distance, just before. Then motion, then
blocks falling around you, photographer
shooting photos, hoping for a perfect
shot, just what you’d been
imagining.
But look at the falling blocks.
Back up the tape
to when the motion started.
Imagine motion, collisions, all falling
down. Try to imagine timing, controlling,
or predicting any of it exactly or repeating
any of it, ever, in precisely the same way,
even once in 1000 takes. I don’t think
anything as complex as choreo-
graphy could come out the
same in a lifetime of
trying.
Close, maybe.
But not exactly, and that’s
the way it is in science too. As
hard as we may try, it just isn’t possible
to repeat ourselves exactly, and it
doesn’t really matter in the
long run anyway.
What matters
is not that we behave as robots,
but that we specify accurately enough
what our robotic selves must accomplish, not what
they must do, and make clear to ourselves, first,
what difference it makes that they
stay within bounds we
set for them.
That’s how it
is in science and sculpting, and
something like it is true in choreography
as well. I am beginning to understand that
choreography and rehearsals are conversations
about what might be. They push action toward
limits of human capability, considering how
audiences perceive, understand and re-
member from scene to scene, and
all of it is imaginary until
the premiere.
That particular
conversation must have included
the size and composition of blocks, both of
which determine what it takes to make them fall,
what they do when they collide with each other or
hit the floor, how long they take to rest, etc. It is all
both affected by and affects dancers’ movements.
Little things like that make enormous differ-
ences in what the audience takes
away. And they affect
the photo.
Here is an example
of lengths Gail Lotenberg went
to improve Experiments. At a continent
wide conference of dance professionals, she
staged three performances of one scene, early
in its development, and invited her peers to
comment on it in public (see Liz Lerman).
The professional feedback was deep,
candid, insightful, and figured
in the evolution of the
performance.
Again, my point
is not that I know anything
about dancing, which I don’t. It’s that
I see many parallels between how experiments
evolved and how wild animals, human children and
adults, families, and organizations of various sizes
learn anything. The feedback session with
the pros is what we call peer review in
science. Colleagues tell us what
does and doesn’t work, and
we adjust what we do,
usually for the
better.
A note on Experiments’ subtitle,
“Where logic and emotion collide”.
What a deliciously
ambiguous figure of speech that
is, especially with reference to experimen-
tation! What could Gail have meant by it? She
might have wanted to contrast cool, emotionless,
limitingly logical science with warm, emotional
dance but I don’t think she meant that at all.
My story about Dave Marmorek puts the
lie to that notion anyway. Besides, her
her husband of 18 years is a living,
breathing, Latino behavioural
ecologist, which clinches my
point about emotions.
Here’s what I think.
I think that subtitle
points not to a difference between
science and dance or between science and art
in general, but to a deep similarity. She just said
Experiments was where the collision occurs. Logic
and emotions almost necessarily collide whenever
we commit, without reservation, to learning
anything difficult – it is a Yin and Yang
of experience.
Experiments itself,
i.e. the production, is a difficult
choreographic experiment partly because
the dancing is difficult to perform. More funda-
mentally, it is challenging to communicate the
experience of discovery. To the extent that
it works, it will succeed in conveying
what it is ‘to experiment’.
Dave Marmorek’s book of poetry
Passing Through: Mountain Paintings and Poems,
with painter co-author Dennis Brown,
was published in 2018.
This story relates to many others.
Work on the Ugliest Part
addresses the issue in sculpting, and
Frank Spear and the Pea Seeds and Teaching for
Creativity in Teaching & Learning.
The Silver Dollar
has examples from my
first few years of navigating the
world. The story about olives curing
in The Case of Gerald Gass comes to mind
in relation to fine cuisine, and Saw Filer Guy
is a perfect example in industry. As my story
about Gerhard Herzberg makes clear, “if you
know what you’re doing, you’re not doing
science and It’s Not Just a Matter of
Technique addresses the same
set of issues from another
angle in teaching.
First published in the Vancouver Observer.
Edited April 2021