READING
GUIDE TO: Latour, B (1987) Science in Action, Milton
Keynes: Open University Press
Two
useful appendices summarise the approach:
(scan of pp 258, 259 of Latour)
APPENDIX 1 Rules of Method
Rule
1 We study
science in action and not ready made science or technology;
to do so, we either arrive before the facts and machines are blackboxed
or we
follow the controversies that reopen them. (Introduction)
Rule
2 To determine the
objectivity or
subjectivity of a claim, the efficiency or perfection of a mechanism,
we do not
look for their intrinsic qualities
but at all the transformations they undergo later
in the hands of others. (Chapter 1)
Rule
3 Since the settlement
of a
controversy is the cause of Nature's representation, not its
consequence, we
can never use this consequence, Nature, to explain how and why a
controversy
has been settled. (Chapter 2)
Rule
4 Since the settlement
of a
controversy is the cause of Society's stability, we cannot use Society
to
explain how and why a controversy has been settled. We should consider
symmetrically the efforts to enrol human and non-human resources.
(Chapter 3)
Rule
5 We have to be as undecided as the various actors we
follow as to what technoscience is made of; every time an
inside/outside divide
is built, we should study the two sides simultaneously and make the
list, no
matter how long and heterogeneous, of those who do the work. (Chapter 4)
Rule
6 Confronted with the
accusation
of irrationality, we look neither at what rule of logic has been
broken, nor at
what structure of society could explain the distortion, but to the
angle and
direction of the observer's displacement,
and to the length of the network thus
being built. (Chapter 5)
Rule
7 Before attributing
any special
quality to the mind or to the method of people, let us examine first
the many
ways through which inscriptions are gathered, combined, tied together
and sent
back. Only if there is something unexplained once the networks have
been
studied shall we start to speak of cognitive factors. (Chapter 6)
APPENDIX 2 Principles
First principle The fate of facts and machines is in
later users'
hands; their qualities are thus a consequence, not a cause, of a
collective
action. (Chapter 1)
Second
principle Scientists
and engineers
speak in the name of new allies that they have shaped and enrolled;
representatives
among other representatives, they add these unexpected resources
to tip the
balance of force in their favour. (Chapter 2)
Third
principle We are never
confronted
with science, technology and society, but with a gamut of weaker and
stronger
associations; thus understanding what
facts and machines are is the same task as understanding who
the people are. (Chapter 3)
Fourth
principle The more
science and
technology have an esoteric content the further they extend outside;
thus,
`science and technology' is only a subset of technoscience.
(Chapter 4)
Fifth
principle Irrationality
is always
an accusation made by someone building a network over someone else who
stands
in the way; thus, there is no Great Divide between minds, but only
shorter and
longer networks; harder facts are not the rule but the exception, since
they
are needed only in a very few cases to displace others on a large scale
out of
their usual ways. (Chapter 5)
Sixth
principle History of
technoscience
is in a large part the history of the resources scattered along
networks to
accelerate the mobility, faithfulness, combination and cohesion of
traces that
make action at a distance possible. (Chapter 6)
My
commentary:
Rules
of Method
Rule
one It is science in action that is
studied, before things are solidified and black boxed. The idea is to
trace the
acceptance of initial conclusions and propositions as fact, either by
doing
history, or by reopening controversies. The examples in Chapter 1
include the
tentative steps leading up to the acceptance of the double helix model
of DNA.
The uncertainties and contingencies included not only the decision to
share
knowledge with other teams, but also a very interesting case where the
alternative model of Linus Pauling was examined. At first it looked as
if the
Pauling model would triumph, since it emerged from a world-famous
scientist and
a large laboratory, whereas Watson and Crick were not really supposed
to be
working on the structure of DNA at
all
. Watson and Crick found the confidence
from somewhere to examine his model critically and found some errors --
unbelievably. This spurred them on to continue with their model and
also to
rush to solve the remaining problems before Pauling discovered his
mistake. The
other example turns on the eventual emergence of a particular kind of
personal
computer, with an number of competing interests, including rival
companies and skeptics
within the company, who had to be persuaded that the new model would
work.
Finally, almost accidentally, the last few major bugs were fixed
sufficiently
for the new model to play a game, which convinced the skeptics. Modern
scientists, working in the 1980s simply took for granted that Watson
and
Crick's model was an accurate one, and that the computer they were
using to
display the model was reliable -- both a model and the computer had
been black
boxed.
Rule two.
It is not so much the
intrinsic logical or deductive qualities other scientific claim that
means it
gets accepted, but the 'transformations they undergo later in hands of
others'
(258)[ same as the specialist term ? see below] . The examples in
Chapter 2
consist of a marvellously detailed analysis of the argumentative twists
and
turns associated with original scientific claims, especially one that
claims to
have discovered a particular hormone associated with human growth.
Latour
traces the complex interweaving of claims and counter-claims, ways of
attacking
counter-claims, further ways of gaining support for original claims and
so on. Additional
references play a major part in this struggle, as do various kinds of
presentations of data, which themselves may lead to further
controversies,
claims and counter-claims.
In
the end, a successful claim is buttressed by whole arrays of supporting
resources, and a complex stratified structure of argument. Some
excellent
examples are given of processes referred to as 'stacking' - an
interesting
practical version of induction, where some observations of biological
specimens
are stacked to lead to conclusions about entire species (see 51);
'staging and
framing' -- where ideal readers and their possible objections are
addressed and
persuaded; 'captation'--
a way of steering obstinate readers towards
particular conclusions by leading them down various argumentative
routes.
The
whole process might well be described as 'fact writing', essentially
the same
process as fiction writing but with more limited options. Ultimately,
only a
few people are left to thoroughly arbitrate the claims, most possible
critics
or dissenters would have given up or gone along with the argument. Of
course,
lots of texts are never even read at all. Scientific writing is another
kind of
rhetoric, more admired because of its dispassionate style, and able to
'mobilize
on one spot more resources than [its
rivals]' (61). Because facticity and objectivity depend on connections
with
other resources, Latour argues that successful science is 'extremely'
social (62). It is these connections to
authorities, experiments, definitions and previous work that makes it
almost
impossible to disagree with a successful claim. [Is there a pragmatic
way of
limiting the long list we are supposed to draw up as in Rule 5? Let
scientists
draw one up until they are convinced of the objectivity of the claim?
Otherwise
the list would be endless – tracing all the references and background
to a
single Sports Science article would be prohibitive! Why should we want
to draw
up any such list that is longer than what the scientists themselves
would draw
anyway?]
Rule three. It is
not that easy to argue
from what 'nature' is really like to settle any controversy. In
practice, what
seems natural and real is what emerges at the end of long debates and
disputes,
when some consensus has been arrived at, or, rather, dissenters have
been
driven off or given up. Incidentally, this forgotten [repressed?]
creative
process is what Latour calls the 'tacit knowledge' of the scientist.
This is a
long process, and in natural science, much depends on what goes on in
laboratories.
Latour's examples turn on controversies that went very deep indeed into
the organization
of laboratories, the calibration of instruments, the purity of samples,
very
detailed attempts to control variables and so on. He insists that this
should
really be seen as an element in the resolution of disputes or trials of
strength, where laboratories serve to discourage dissenters: the only
way to
respond to laboratory evidence is to develop bigger and better
laboratories. An
instrument here is defined as something that produces data connected to
displays. The relation between instruments and their 'spokesmen' (those who interpret the data and attempt to
make it as objective as possible) is crucial. Scientists interpreting
data
strive to be objective spokespersons of instruments, while the
dissenters
attempt to argue that some subjective matters have been introduced into
the
interpretation. Anyone shown to be subjective loses the strength of
support
gathered by a scientific writing and laboratory experiments. There are
many
interesting examples of how particular laboratory demonstrations or
experiments
or even canonical pieces of work became decisive allies of particular
point of
view, including Mead's work on Samoan adolescents, which became a
decisive
issue for those arguing for cultural versus biological determinism of
sexual
behaviour. There are also political struggles where spokesmen claim to
be
speaking objectively for their constituents.
This
is actually an example of Latour means by the term 'actant' -- 'whoever and whatever is represented [by a
spokesman]' (84) and it can be a machine as well as a person. [This is
unexceptional, but is not the root and branch challenge to human
subjectivity
that I had expected. I can see that Latour wants to represent science
as wholly
and irredeemably rhetorical, and thus he has to take on what looks like
the
objective elements. So he denies their objectivity by saying they have
no
meaning until they are interpreted and woven into controversies. But
this is
not saying, so far at least, that objects and machines are fully
subjective as
humans are. Machines cannot be spokespersons for and on behalf of
themselves.
Of
course, people also need spokespersons to become active in
controversies - much
work is simply ignored. This is also illustrated by 'publication bias',
where
only positive results tend to be reported, both by the companies that
sponsor
the research and by the scientific journals, even the
Lancet]
Occasionally
instruments and their readings are interpreted to suggest that a whole
new
object has been discovered. Unusual readings or findings raise a
tentative
claim to have discovered a new object, and again these claims are black
boxed
in due course. One example was the discovery of polonium, which
originally
appeared as a set of interesting findings in the laboratory of the
Curies. In
this early stage, 'a "thing" is a score list for a series of trials'
(89).
The
chapter ends with the points summarized in rule three about nature.
Scientists sometimes
want to claim that nature will resolve disputes in the end. At the same
time
though, they face the other way [Janus figures appear throughout],
because much
of their activity is designed to find out what actually is natural.
Only after
a great deal of activity does this become apparent. In this way,
scientists
face both ways, claiming to be both realists and relativists. Latour
does not
want to argue for one option rather than the other, but to agree with
the
scientists themselves -- that once a controversy is settled, we can
call the
result natural and real. However, all the time controversies persist,
what is
natural and real is in doubt. Nor is it any good to use current science
to
arrange past scientific experiments in terms of their correspondence
with what
is now thought of as real and natural. This is merely 'Whig history,
that is, a
history that crowns the winners, calling them the best... and... the
losers...
simply... wrong' (100). [In other words,
it is teleological, or historicist]. The double stance toward nature is
also
used to fight off critics, invoking the realist stance against
relativists, and
occasionally vice versa [possibly when
accused of being naive positivists . This might happen with sports
science --
on one hand, approaches are simply either right or wrong, but on the
other,
sports scientists congratulate themselves on finding ingenious ways to
define
and
operationalize particular matters, and maybe even to manage
controversies].
Rule 4 It is a
problem to decide who
actually qualifies for the title of scientist -- is it those few who
work in
leading laboratories, or the much wider group of people who keep them
there,
including those senior scientists who travel the world getting funds
and
licences? [This is going to be one of
those
distinctions that Latour simply sidesteps, by refusing to prioritize or
organize
them into a hierarchy instead of a network]. The latter group is
important to
permit the former to operate. When we look at where scientists or
actually
employed and who pays for them, we find only a few are engaged in
experimental
laboratory work, and that the biggest budgets are found in defence and
health.
Latour says that these tend to have limitless budgets so it is a good
idea for
any scientific programme to get connected to them if it can. Scientists
themselves are not interested in these links, and don't understand
anything
about society, certainly not in the way that sociologists understand
it
-- hence the absence from the book of any terms like class or gender.
What
'society' amounts to is a pragmatic matter for the scientists
themselves, and
they don't really understand its extent until they can point to a
stabilized
network of contacts. Thus both society and nature are sometimes seen as
the
causes of scientific activity, but they are really the results of
extensive
activity stabilized into a network.
Rule 5 Chapter 5
has a very interesting
discussion on relativism with some excellent examples including the
Azande and
the Trobriand Islanders. It is easy to demonstrate that the simple
opposition
between Western thought as rational, and everyone else's as limited and
partly
irrational, will not hold water. Western thinking and practices are
every bit
as irrational as Azande witchcraft, and vice versa. Both systems of
belief and
science result from a network of claims, problem-solving and activity
developed
according to an everyday logic - a 'sociologic'. [Here
and elsewhere we find echoes of American pragmatism
both as a way
of organizing ordinary beliefs and of developing scientific knowledge].
There
are important differences between science and belief, however, seen
best when
scientific networks encounter nonscientific ones. There are a number of
ways in
which this can happen, and Latour uses terms like the angle, direction
or scale
of the encounter. [There are also hints of Schutz's work on different
notions
of reality between 'strangers' and residents, and between scientists
and
others.]
Latour points out that scientists go off to investigate other social
lives, not
to settle among them and maintain their network of belief, but to
return back
to their home countries and strengthen and extend scientific networks.
There is
also a hint, developed fully in Chapter 6 of the greater explanatory
power of
scientific networks.
Rules 6 and 7 There is no difference
between
the way that ‘savages’ think and the way that scientists think, no
‘Great
Divide’. Scientific networks and belief systems are elaborated and
extended in
the same way, buttressing claims, managing crises and refuting rivals
using the
same pragmatic procedures – ‘sociologic’. Science is organized
differently
though, since it operates with much more data, gathered systematically
and then
processed, abstracted and rationalized into systems. Science operates
just like
bureaucracies do. Back at the metropolitan centres in Europe,
people are despatched to discover data about other people and bring it
back for
processing and addition (this is like capital accumulation but Latour
says the
term capitalism is confusing and ambiguous). A large interlocking
network is
required, of scientists but also politicians, explorers, rulers etc.
Once
collected or imported, data is subject to further processing,
abstraction (like
the ‘stacking’ mentioned earlier), and is ideally mathematicised.
Science then becomes
specialist and powerful, capable of considerable application – but only
if the
real world is transformed first (tidied, rationalized, made to resemble
the
data of science). This process ‘hardens’ facts (surrounds them with so
much
support that they are irrefutable).
Overall,
this is not quite as strange
and alien as it looks. I think Latour mystifies it a bit, possibly for
good
reasons: he is wary of using conventional terms such as
'abstract' to describe scientific theory,
although he is content to rely on that word as a verb in order to
describe the
explanatory power of scientific theory. The same goes for words like
'transformation', which is not much more than the process of
objectifying
complex reality so as to make it compatible with the formulae of
science. I
suppose both of these words indicate that scientific theory doesn't
just
describe worlds, but colonizes them (although Latour would not like the
political and critical sense of that term).
As
for the famous bits about agencies and networks, I think this is not
much more
than saying that individual action always takes place within collective
action.
Obviously, the efforts of others are crucial for understanding the
activities
of individual scientists. Those others include not only instrument
makers and
technicians, but collective activity going on in universities, funding
bodies,
government departments and the like. Instruments and machines become
actants
because they condense a large network inside them, so to speak? These
networks
are so interconnected that it makes no sense to describe events as 'theoretical', 'political', 'geographical', or whatever, since all of
these aspects
are
involved (the example here is a rather
good one -- initial explorations of Pacific islands by the French
government in
order to map and possibly settle particular areas of the Pacific
Rim. The more familiar case of Darwin's voyage on the Beagle might also serve. A
series of familiar social networks got Darwin on board, including the
social connections between his father and various Government agencies,
and it was also essential that he cope socially as a gentleman
companion for the Captain. The voyage itself was launched for
several interlocking reasons, including the Admiralty's desire to chart
the Pacific, commercial intersts wanting to establish trade with South
America, and the Church of England wanting to establish missionary
outposts. To achieve the latter, the
Beagle carried a missionary and three natives of
Tierra Del Fuego who had been 'brought to England' [actually abducted,
originally as hostages] several
years before and Anglicised: they were to be returned to their homeland
to set up a missionary station. Darwing says that retujrning the
Fuegians was the main motive for the journaey as far as the captain was
concerned. Darwin himself took several risks in his
adventures and might well have perished once or twice. The implications
for science would have been very interesting!).
The
notion of a network is actually rather like that of the rhizome ( in
Deleuze, as Latour himself says), extending in
different areas and dimensions in a kind of practical problem-solving
way --
a 'sociologic'. Theoretical science,
social science, and religious beliefs are identical in this sense --
they're
all cobbled together as they go, in order to extend themselves and
defend
themselves against rivals. We're not far away from the notion of
bricolage,
surely, with a possible role for particularly gifted bricoleurs?
Of
course science is organized and systematized, and this is the secret of
its
huge explanatory power. Experiences are turned into data, and this data
is
'mobile', that is it can be imported back to the centres of networks,
abstracted and managed, and slotted into systems of classification of
various kinds.
Cartography and taxonomy are the bases of the growth of science in Europe.
There is a power relation involved, in that, usually, data moves into
centres
and not the other way around.
This
is an area where Latour is occasionally evasive. For
example, he says that he will not use
sociological terms such as class or power because that is not the ways
that
scientists themselves understand the world, and he is simply trying to
map
their understandings -- Science in Action. Yet there other reasons as
well --
sociological theory is a form of science itself, and he would not wish
to
privilege one form in order to understand another. The implication is
that his
concepts, such as network, are more powerful than either, or at least
more
general. The usual lack of reflexive critique is applicable here -- has
Latour
simply been cobbling together bits of history, scientific practice,
observation
and sociological terminology in order to develop ANT?
De
Certeau’s critique of Foucault’s use of history might apply here:
Latour is
displaying such a grasp of historical and other detail that it is
impossible to
refute him. His decision to explore the esoteric realm of science also
leaves
many sociologists without any way to disagree.
More
mundanely, many of the examples are historical, no doubt to help us
understand
before things got really technical. But is modern science like that?
Does it
still do simple induction? Isn’t there another stage where
mathematicised
‘facts’ are themselves manipulated and never actually ‘applied’? To use
Lyotard’s terms, Latour is describing
modernist science where it all still ran
according to the performance criteria: now it is a mere game is it
easier to
extend networks? If it is now a research programmes, doesn’t that make
the
politics of universities more prominent?
At
times he seems apologetic towards the use of power, seeing it as
necessary to
consolidate networks, inevitable, or so well established that it is
irreversible. The links between knowledge and power need be clarified
though,
unless he really is doing a simple description of the world-view and
activities
of natural scientists, who could not be expected to want to clarify
them.
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