A puppet show on objectivity and quantification

December 2, 2018 – 11:51 am

This post contains the script for a puppet show on objectivity and quantification, based largely on Theodore Porter’s book Trust in Numbers. It was part of a challenge set by our first-year honors students, and yes, that’s also how we ended up singing open science songs in the next class (see the results: part 1, part 2).

Note that this script was deliberately slightly stilted; there were long passages thrown in straight out of the book, extended monologues, etc. so students could feel the difference between those portions and the more interactive/engaging parts of the presentation (we debriefed afterward on the audience experience so they could think more critically about their own presentation designs).

Roles:
MEL (Mel Chua, course instructor – abbreviation based on name sign variant)
COK (Corrine Occhino, course instructor – abbreviation based on name sign variant)
QUANT (everyone)
SCIENTIST A
SCIENTIST B
LAVOISIER
FRENCH RAILROAD
LOUISIANAN

Setting: performed with everyone sitting/standing in a circle with minimal staging otherwise; paper-bag puppets failed and were replaced by talking hands. The script was projected for read-through.

MEL: So there’s this problem in my field, which is STEM education research. We have a lot of really messy, interesting spaces to investigate. What are the ethics of engineering? How do really little kids, like preschoolers, think about science? Is technical education different in different countries — say, Brazil versus Japan — or schools, like RIT versus the University of Illinois? Faced with these fascinating questions, what do we do? We turn them… into numbers. I’ll demonstrate. What are the ethics of engineering?

COK: 8 out of 10 people say engineers should be required to take an ethics class!

MEL: How do really little kids, like preschoolers, think about science?

COK: 64% of them like Legos before the age of 5!

MEL: Is technical education different in different countries — say, Brazil versus Japan — or schools, like RIT versus the University of Illinois?

COK: RIT students have 207% more homework!

MEL: You’re just making up all of these numbers, aren’t you?

COK: Yes. Well, you wrote them in the script, so technically you made them up.

QUANT: Numbers! Wooooo! (general cheering noises)

MEL: How did we get here? What about all the cool qualitative research methods that use data like interviews and observations, or photography or video, or think about how people feel or act or what they believe?

COK: Let’s go back in time and find out how this happened.

EVERYONE: (make time-travel noises)

SCIENTIST A: I am a scientist! I am discovering new things!

SCIENTIST B: Hello, my friend. Where are you discovering them?

SCIENTIST A: In my living room, of course. I am a privately wealthy individual.

SCIENTIST B: I would like to learn about your discoveries!

SCIENTIST A: Great! Do you have the ancient equivalent of millions of modern-day dollars?

SCIENTIST B: What? No. I’m a college student.

SCIENTIST A: Sorry. That’s how much books cost. We’re living before the 1400′s and the invention of the printing press.

COK: At this point in the history of science, experiments are intrinsically private. There is no basis for constructing public knowledge.

SCIENTIST A: Only I and my friends — if they happen to be around — can see an experiment, and therefore, only we can learn from it!

SCIENTIST B: But how am I supposed to learn what you’re doing?

SCIENTIST A: Well, if I already know you, and like you, I might write you a letter about it.

SCIENTIST B: I have no other options, so that sounds great!

COK: How do we make knowledge more open and able-to-be-shared? This was the driving force behind developing what we now call “objectivity” in modern science. Otherwise, we would run into situations like this one.

LAVOISIER: I am Lavoisier! It is the 1700′s, and I have done experiments on oxygen that will become the basis for modern chemistry!

SCIENTIST B: Who are you, and how do I know I can trust your results?

LAVOISIER: Because I am Lavoisier!

SCIENTIST A: Uh… huh.

COK: This was not very convincing.

LAVOISIER: Okay, fine, I will write down my methods so that you can replicate my experiments. Now all my problems have been solved!

COK: They were not.

LAVOISIER: Let us try this again. I am Lavoisier! It is the 1700′s, and I have done experiments on oxygen that will become the basis for modern chemistry!

SCIENTIST A: Uh, I repeated your experiment and got different results.

SCIENTIST B: I also got… completely different results.

LAVOISIER: Fine. Next time, you can come to my place and be my witnesses for the experiment. Then you can tell everyone else you were there, and saw what happened, and that they should believe me.

SCIENTISTS A AND B: We have no other options, so that sounds great!

COK: We still see this phenomenon happening often today. For instance, if Mel is teaching an engineering lab class…

MEL: Okay, everyone — how is your circuit doing? Did you get your code working?

LAVOISIER: It was working last night! I swear!

SCIENTIST A: I saw it! This code totally worked yesterday! Really!

MEL: Uh… huh.

COK: This practice of providing replication instructions led to an interesting thing. Only people with a certain level of experimental mastery could participate in science, for one. Also, “acceptable” methods and instruments are ones that can have written replication instructions — if it wasn’t replicable, it could not really be science.

SCIENTIST B: But if I’m studying an event like the Pompeii volcanic explosion, which only happened once?

SCIENTIST A: And would be really, really unethical to recreate?

QUANT: Sorry, it’s not replicable.

COK: As you can see, the demands of communication helped to define the subject matter of science and what science was and what it meant.

MEL: Objectivity became a classic scientific ideal. It refers to a cluster of attributes: truth to nature, impersonality, fairness, universality, and immunity to distorting factors like gender, nationality, language, personal interest, and other kinds of prejudice. Objectivity is about impersonality, excluding judgment and subjectivity. The scientific community has shaped and used quantification as a way to construct science as a global network and not just a collection of local research communities. Let’s talk about the different things science should be… first of all,

QUANT: Mechanized!

MEL: Science should be

QUANT: Objectified!

MEL: This means it should be grounded in specific techniques sanctioned by a body of specialists. And what do we do about human judgment, with all its gaps and idiosyncracies?

QUANT: Make it go away!

COK: But can we ever actually obtain that goal?

QUANT: No, but we can pretend it does!

MEL: Quantification is a way of making decisions without seeming to decide. Objectivity lends authority to officials who have very little of their own. Here are a couple of stories.

FRENCH RAILROAD: I am from the French railroad, in the 1840′s!

QUANT: Hello, French Railroad Person!

FRENCH RAILROAD: Where should our railroad run through France?

QUANT: We don’t know!

FRENCH RAILROAD: And we’re not going to leave this to messy human judgment, are we?

QUANT: No!

FRENCH RAILROAD: I have scientists here who will tell us which one is better! Using math!

SCIENTIST A: I have numbers that show we should run it through big cities! It will be better!

QUANT: Yay!

SCIENTIST B: I have numbers that show we should run it through small towns! It will be better!

QUANT: YAY!

FRENCH RAILROAD: Wait, but which one is actually better?

MEL: This was a maximization problem with no consensus on what ought to be maximized. But because they used numbers, it hid the underlying political discussion.

SCIENTIST B: What political discussion? We just have the numbers here.

SCIENTIST A: It’s cold, hard fact.

FRENCH RAILROAD: But then why do you not agree?

MEL: Then there was Louisiana in the 1930′s and 1940′s.

LOUISIANAN: Hello! I am from Louisiana – we would like to consult with the Army corps of engineers.

QUANT: Hello!

LOUISIANAN: We need to design the Mississippi floodway. Where should it go?

QUANT: In Louisiana!

LOUISIANAN: That sounds great! What does that mean? What will the floodway do to us?

QUANT: It will flood Louisiana!

LOUISIANAN: Wait, what?

QUANT: Flood Louisiana!

LOUISIANAN: Wait, you think we’re going to agree to this?

QUANT: Look, we have numbers!

LOUISIANAN: Well, I guess… uh… okay, maybe you have point there, let me think about this…

MEL: Even the representatives from Louisiana were taking this seriously, even if the thought of flooding Louisiana seemed somehow wrong to them, because… well, the numbers said so!

COK: Numbers are technologies of distance and trust. The big idea here is thinking about quantification — for instance, numbers, graphs, and formulas — as a long-distance communication technology.

MEL: As Porter says in his book, “Trust by Numbers”: Since the rules for collecting and manipulating numbers are widely shared, they can easily be transported across oceans and continents and used to coordinate activities or settle disputes. Perhaps most crucially, reliance on numbers and quantitative manipulation minimizes the need for intimate knowledge and personal trust. Quantification is well suited for communication that goes beyond the boundaries of locality and community. A highly disciplined discourse helps to produce knowledge independent of the particular people who make it.

COK: In other words, numbers let us keep on working even if we don’t know each other.

SCIENTIST A: Who are you?

SCIENTIST B: I’m a scientist. Who are you?

SCIENTIST A: I’m a scientist. We’ve never met before.

SCIENTIST A and SCIENTIST B: But I trust you, because SCIENCE.

MEL: Objectivity and boundaries are related; mechanical objectivity becomes really important when in/out groups are not clearly defined. It’s a defense against our tendencies to be suspicious of others. Even if I don’t know the particular people involved — or maybe I don’t even like the particular people involved — I can trust their work. Why? It’s because I’m not trusting them. What am I trusting?

QUANT: NUMBERS!

MEL: So back to the beginning: in my field of STEM education research, we have this huge tension. We are a new field. We don’t have a long history. We don’t know each other very well yet. We have people and their students here and there… we mostly have local research communities, and we want to become a global network. The question now is: can we have a global network without reducing everything to quantities? Can we have a global network where local communities are honored in their individual richness — and yet linked across into a larger community of collaborators? I hope so, and the work I’m doing — which is very not quantitative, which is all qualitative — is my contribution towards hoping in this space. Stay tuned for Thursday, when we talk about Free Culture and its relationship to science and research.

 

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