Presented at HSD (Human & Social Dimensions of Science & Technology) Second Year Project Colloquium Series. Tempe, AZ. February 2, 2011.

1. Second Year Project Presentation
Human & Social Dimensions of Science & Technology PhD Program (HSDST)

2. An anthropologist in a biophysics
laboratory

3. Why biophysics ?
Why anthropological method?
Why laboratory?
An anthropologist in a biophysics laboratory

4. Why biophysics?
Biophysics provides a reference point to
explore how the domain differences
between physics and biology are instituted
and re-configured

5. Molecular Biology (MB)
vs.
High-energy Physics (HEP)
Epistemic cultures

6. MB HEP
Leadership style &
power structure
Individually
embodied by the
lab director
Collectivized in
large-scale
experiment under
which individuals
are subsumed
Epistemic
apparatus
Immutable mobiles
and standardized
lab manuals
The
“superordering” of
components &
instruments
Epistemic goal Positive knowledge
Negative/liminal
knowledge
Epistemic site
Laboratory as an
internal processing
unit for experiment
Separation of
experiment and
laboratory

7. Why biophysics ?
Why anthropological method?
Why laboratory?
An anthropologist in a biophysics laboratory

8. Laboratory studies in anthropological and ethno-
methodological traditions.
the socially-derived authority of laboratories ->
“the transformation of the whole of society
according to laboratory experiments” Latour
(1988)

9. Why biophysics ?
Why anthropological method?
Why laboratory?
An anthropologist in a biophysics laboratory

10. The laboratory as the unit of analysis.
Discipline-specific laboratory cultures mirror the
culture of the knowledge society:
“the laboratory has emerged as carrying a
systematic ‘weight’ in our understanding of
science. This weight can be linked to the
reconfiguration of the natural and social order
which in my opinion constitutes a
laboratory.” (Knorr-Cetina 1992:114)

11. “a new emerging order that is neither social nor
natural, an order whose components have mixed
genealogies and continue to change shape as
laboratory work goes on.” (Knorr-Cetina 1999:121)
The analysis of epistemic cultures is centered around
the laboratory as the locale of knowledge making in
sciences.

12. Fieldwork and Findings

13. Fieldwork
The field site
• Site: Center for Single Molecule Biophysics (SMB), the
Biodesign Institute, ASU
• About the site: nanomaterial engineering, DNA self-assembly
and sequencing, molecular electronics etc.
• Members: physics(6), chemistry(1), chemical engineering(1),
electrical engineering(1), material engineering(1), biochemistry
(1).
Data-collection
methods
• Duration:
• first stage (intensive): January 2009-July 2009
• second stage (follow-up): August 2009- July 2010
• Sources of evidence:
• 3 months embedded classroom observation and participation
• 6 months weekly lab meeting observation
• archival study of the lab profile (funding acquisition, journals,
conference posters, proposal docile)
• 6 months face-to-face interviews
Record of
interaction
• high-level interaction: laboratory director and 1 graduate student
(n=2); mid-level interaction: 5 grad students, 1 postdoc (n=6); low-
level interaction: 1 faculty collaborator, 1 visiting scholars, 1 lab
manager (n=3)
• 1 invited presentation to the laboratory
Languages
• Interviews with grad students: Mandarin + English
• Interviews with lab director and faculty: English

14. Reasoning with the intractable data

15. What the lab is working on: to
sequence DNA mechanically
“Single base resolution in tunneling
reads of DNA composition.” Nature
Nanotechnology 2009
“Tunneling readout of hydrogen-bonding
based recognition.” Nature Nanotechnology
2009

16. The hypothesis of
reasonability“the successful bonding of DNA base pairs will
stabilize the tunneling junctions and decrease the
AC response amplitude. get perfect looking on-off
tunneling without the bond breaking. (Nature Nano
2010) --> base trapped much longer in the junction
by the AFM experiments entropy in solutions
resolution of unreasonable data: telegraph noise
According to this hypothesis, the stronger the
hydrogen bond, the weaker the measured AC
amplitude between the tunneling junction.

17. student A student B
strong h-bond
strong AC
GC base pair base-nucleoside
Affirmative
results
Negative
results
strong h-bond
weak AC

18. Possible sources of
unreasonable data in the lab meeting
The lab director meeting Joe Biden, April 2010
“I don’t see two types
of bond breaking from
this.”
“I bet it’s a monolayer
problem. Try
characterizing the film
as I don’t see other
alternatives.”
“Why is C behaving
differently from T?” “...something goofy
about the measurement
of C.”
Lab director to student A: “Stop AC
modulation and try characterizing C
with SAM.”

19. “I talked to the theoretical physicist in our
group, and we agreed that the hypothesis may
not be sophisticated enough to capture the
variations of DNA molecules.…This
hypothesis presumes that ac amplitude is
directly proportional to beta value, but actually
it should be proportional to beta times I
(tunneling current). So any fluctuations in the
part of tunneling current will affect the
resultant ac amplitude. The assumption that ac
amplitude is a pure function of beta value is
faulty....I think this is the crux of the problem
(of getting unreasonable data), as there is a
considerable overlap between certain segments
of reasonable and unreasonable data…”
Student A outside the lab meeting

20. “By the way, this (the alternative
explanation) would also explain why he
(student B) got fairly reasonable and
clean result, because his measurement is
done on nucleoside, the sugar ring
increases the distance of the tunneling
gap so the tunneling current becomes
insignificant, and therefore in his case, ac
amplitude can be reduced to beta value
only.”
Student A & peer comparison

21. “Note the large range in the predicted
conductances for the three molecular pairs and the
large predicted difference between conductances
for two and three hydrogen-bond connections (a
factor between 4 and 5 X). This is in sharp contrast
to values calculated for base-nucleoside pairs
where the number of hydrogen bonds makes little
difference to the predicted (and measured)
molecular conductance.”
Peer comparison in published texts
(Source: “Recognition Tunneling Measurement of the Conductance
of DNA Bases Embedded in Self-Assembled Monolayers,” Journal of
Physical Chemistry C, July, 2010 )

22. “The predicted trends in conductance for three
DNA base pairings (2AA-T, G-C, and A-T) are not
observed in single molecule conductance
measurements made with monolayers of thiolated
bases attached to bare gold electrodes.”
Representation of “reasonable” and “unreasonable”
data in published text
“Unreasonable” data
“Reasonable” data
“We have determined the tunneling conductance of
DNA base-nucleoside pairs using this method,
obtaining results that are in reasonable agreement
with the predictions of density functional
calculation. (my emphasis)”

23. “Once a paper is issued, the laborious
process of writing and disputing and
controversy is black-boxed and what
is published in the peer-reviewed
j o u r n a l s a r e t a k e n - f o r -
granted.” (Latour and Woolgar 1976:
63)

24. “one time I processed my data on a perfect
monolayer, where everything (the structures of
molecular bonding) is well ordered, and yet I still
got the same messy result. The uniform monolayer
means that there is no contamination. Then I realize
maybe we were using the wrong viewpoint and we
have to change ourselves.”
me: How do you change yourselves?
Student A:

25. “there is a logical mistake in the ac
modulation technique: using one base to
recognize another. What happen is that this
base cannot recognize the other three.
Finally, we notice that most data are
reasonable. There’s no unreasonable
data. We solved the problem by
normalizing the data. There is a
normalized constant (with which) we need
to divide (ac amplitude).”

26. &

27. “(Name of student B) was the first one who introduced
the term ‘unreasonable’ data. (Name of student B) likes
to predict data, he can get rid of the data he doesn’t like
with no reason, and he can give the data a name:
unreasonable; but this is not scientific because maybe
you are treating trash as gold and gold as trash. Every
piece of data you got from the experiment should have
some meanings, they should give you some
information. And you cannot simply judge them from
your arbitrary viewpoint.”

28. “Yes, we stop calling our data
‘reasonable’ or‘unreasonable’ after
that...But you have to understand, we
need to give raw data a name to
facilitate our communication. Like if I
am a detective, I need to name my
suspects like...Mr. Big or Miss
Beauty...you know just to facilitate the
investigation. It doesn’t matter how he
named the suspects. The important
thing is to catch the culprit and solve
the case .”
“But some names have
consequences.In the
detective analogy, sure I
understand the detective
needs to name the
s u s p e c t s f o r h i s
investigation. But is it ok
for him to call a suspect,
say a criminal?”

29. “I think I agree with you. We were, at
least (name of student B) was, quite
arbitrary on this matter. Although you
raised a very good point, I think it
doesn’t matter how we describe the
data until we publish the data. We
were only talking about it within the
group before publication. If we label
our data as “unreasonable” in our
published paper then we need to be
accountable for it. But it’s alright as
long as it is kept within the group.
“Sure. Just like the
detective cannot call a
suspect a criminal in the
court before the suspect is
convicted right? But the
question here is, is it ok
for the detective to call
the suspect a criminal
during the investigation
before revealing the case
to the public?”

30. “No, it’s not ok. I think you are right. It’s a
psychological problem. If you keep talking that
something is bad, it may subconsciously lead you
into the predisposed direction and clouds your
judgment. So...yes, I think you are absolutely right
on this point. And I think this is why we stop
calling any data set ‘unreasonable’ after that point.”

31. Publication is established as the golden
parameter with which the ethics of
discursive practice is assessed.
Publication legitimizes the obscurity of the
decision-making process of the elimination
of “unreasonable” data.

32. beyond black-boxing by scientists and
unblack-boxing by anthropologists
results of participation-observation-
engagement: rendering the violation of the
principle of “benefit of the doubt” in the
process of knowledge production explicit
by revealing that the justice of the process
of the investigation matters just as much as
the justice of the results

33. Qualification
Limited duration; limited sample
Limited access to informants and intended scope of
interaction
Sustained hierarchy among the researchers in the lab, and
between ethnographer-scientist within and outside the lab

34. Malinowski “The Ethnographer”
at work in Omarakana,
Trobriand Islands, 1922 (Stocking
1995: 262)
“The scientists” at work,
2009 (Bioethics cartoon
lab)

35. Conclusion
the intersection between physics and biology introduces
uncertainty and offer a broader room for not just
participant-observation but collaborator-engagement.
In the course of following the evolution of how scientists
“reason” with their data, the role of laboratory
ethnographers is not reduced to the level of mere
observation and documentation. It is possible for the
laboratory ethnographer, after familiarizing herself with
the workfloor context, to engage in the ongoing science
and make a difference.

36. Acknowledgement
Thanks for their comments on the written draft:
• Dr. Ann Koblitz
• Dr. Hoyt Tillman
• Dr. Dave Guston
Thanks for their comments on the oral draft:
• Abigail Perez Aguilera
• Brenda Trinidad
• Chad Monfreda
• Federica Lucivero
• Hannot Rodriguez Zabaleta
• Lijing Jiang
Thanks for your attention!