## 1. What is Scientific Realism?


### 1.1 Epistemic Achievements versus Epistemic Aims



It is perhaps only a slight exaggeration to say that scientific
realism is characterized differently by every author who discusses it,
and this presents a challenge to anyone hoping to learn what it is.
Fortunately, underlying the many idiosyncratic qualifications and
variants of the position, there is a common core of ideas, typified by
an epistemically positive attitude toward the outputs of scientific
investigation, regarding both observable and unobservable aspects of
the world. The distinction here between the observable and the
unobservable reflects human sensory capabilities: the observable is
that which can, under favorable conditions, be perceived using the
unaided senses (for example, planets and platypuses); the unobservable
is that which cannot be detected this way (for example, proteins and
protons). This is to privilege vision merely for terminological
convenience, and differs from scientific conceptions of observability,
which generally extend to things that are detectable using instruments
(Shapere 1982). The distinction itself has been problematized (Maxwell
1962; Churchland 1985; Musgrave 1985; Dicken & Lipton 2006) and
defended (Muller 2004, 2005; cf. Turner 2007 regarding the distant
past). If it *is* problematic, this is arguably a concern
primarily for certain forms of antirealism, which adopt an
epistemically positive attitude only with respect to the
observable. It is not ultimately a concern for scientific realism,
which does not discriminate epistemically between observables and
unobservables *per se*.



Before considering the nuances of what scientific realism entails, it
is useful to distinguish between two different kinds of definition in
this context. Most commonly, the position is described in terms of the
epistemic *achievements* constituted by scientific theories
(and models--this qualification will be taken as given
henceforth). On this approach, scientific realism is a position
concerning the actual epistemic status of theories (or some components
thereof), and this is described in a number of ways. For example, most
people define scientific realism in terms of the truth or approximate
truth of scientific theories or certain aspects of theories. Some
define it in terms of the successful reference of theoretical terms to
things in the world, both observable and unobservable. (A note about
the literature: "theoretical term", prior to the 1980s,
was standardly used to denote terms for unobservables, but will be
used here to refer to any scientific term, which is now the more
common usage.) Others define scientific realism not in terms of truth
or reference, but in terms of belief in the ontology of scientific
theories. What all of these approaches have in common is a commitment
to the idea that our best theories have a certain epistemic status:
they yield knowledge of aspects of the world, including unobservable
aspects. (For definitions along these lines, see Smart 1963; Boyd
1983; Devitt 1991; Kukla 1998; Niiniluoto 1999; Psillos 1999; and
Chakravartty 2007a.)



Another way to think about scientific realism is in terms of the
epistemic aims of scientific inquiry (van Fraassen 1980: 8; Lyons
2005). That is, some think of the position in terms of what science
aims to do: the scientific realist holds that science aims to produce
true descriptions of things in the world (or approximately true
descriptions, or ones whose central terms successfully refer, and so
on). There is a weak implication here to the effect that if science
aims at truth, and scientific practice is at all successful, the
characterization of scientific realism in terms of aim may then entail
some form of characterization in terms of achievement. But this is not
a strict implication, since defining scientific realism in terms of
aiming at truth does not, strictly speaking, suggest anything about
the success of scientific practice in this regard. For this reason,
some take the aspirational characterization of scientific realism to
be too weak (Kitcher 1993: 150; Devitt 2005: n. 10; Chakravartty
2007b: 197; for skepticism about scientific aim-talk more generally,
see Rowbottom 2014)--it is compatible with the sciences never
actually achieving, and even the impossibility of their achieving,
their aim as conceived on this view of scientific realism. Most
scientific realists commit to something more in terms of achievement,
and this is assumed in what follows.


### 1.2 The Three Dimensions of Realist Commitment



The description of scientific realism as a positive epistemic attitude
toward theories, including parts putatively concerning the
unobservable, is a kind of shorthand for more precise commitments
(Kukla 1998: ch. 1; Niiniluoto 1999: ch. 1; Psillos 1999:
Introduction; Chakravartty 2007a: ch. 1). Traditionally, realism more
generally is associated with any position that endorses belief in the
reality of something. Thus, one might be a realist about one's
perceptions of tables and chairs (sense datum realism), or about
tables and chairs themselves (external world realism), or about
mathematical entities such as numbers and sets (mathematical realism),
and so on. Scientific realism is a realism about whatever is described
by our best scientific theories--from this point on,
"realism" here denotes scientific realism. But what, more
precisely, is that? In order to be clear about what realism in the
context of the sciences amounts to, and to differentiate it from some
important antirealist alternatives, it is useful to understand it in
terms of three dimensions: a metaphysical (or ontological) dimension;
a semantic dimension; and an epistemological dimension.



Metaphysically, realism is committed to the mind-independent existence
of the world investigated by the sciences. This idea is best clarified
in contrast with positions that deny it. For instance, it is denied by
any position that falls under the traditional heading of
"idealism", including some forms of phenomenology,
according to which there is no world external to and thus independent
of the mind. This sort of idealism, however, though historically
important, is rarely encountered in contemporary philosophy of
science. More common rejections of mind-independence stem from
neo-Kantian views of the nature of scientific knowledge, which deny
that the world of our experience is mind-independent, even if (in some
cases) these positions accept that the world in itself does not depend
on the existence of minds. The contention here is that the world
investigated by the sciences--as distinct from "the world
in itself" (assuming this to be a coherent distinction)--is
in some sense dependent on the ideas one brings to scientific
investigation, which may include, for example, theoretical assumptions
and perceptual training; this proposal is detailed further in
 section 4.
 It is important to note in this connection that human convention in
scientific taxonomy is compatible with mind-independence. For example,
though Psillos (1999: xix) ties realism to a "mind-independent
natural-kind structure" of the world, Chakravartty (2007a: ch.
6) argues that mind-independent properties are often conventionally
grouped into kinds (see also Boyd 1999; Humphreys 2004: 22-25, 35-36, and cf. the
"promiscuous realism" of Dupre 1993).



Semantically, realism is committed to a literal interpretation of
scientific claims about the world. In common parlance, realists take
theoretical statements at "face value". According to
realism, claims about scientific objects, events, processes,
properties, and relations (I will use the term "scientific
entity" as a generic term for these sorts of things henceforth),
whether they be observable or unobservable, should be construed
literally as having truth values, whether true or false. This semantic
commitment contrasts primarily with those of certain
"instrumentalist" epistemologies of science, which
interpret descriptions of unobservables simply as instruments for the
prediction of observable phenomena, or for systematizing observation
reports. Traditionally, instrumentalism holds that claims about
unobservable things have no literal meaning at all (though the term is
often used more liberally in connection with some antirealist
positions today). Some antirealists contend that claims involving
unobservables should not be interpreted literally, but as elliptical
for corresponding claims about observables. These positions are
described in more detail in
 section 4.



Epistemologically, realism is committed to the idea that theoretical
claims (interpreted literally as describing a mind-independent
reality) constitute knowledge of the world. This contrasts with
skeptical positions which, even if they grant the metaphysical and
semantic dimensions of realism, doubt that scientific investigation is
epistemologically powerful enough to yield such knowledge, or, as in
the case of some antirealist positions, insist that it is only
powerful enough to yield knowledge regarding observables. The
epistemological dimension of realism, though shared by realists
generally, is sometimes described more specifically in contrary ways.
For example, while many realists subscribe to the truth (or
approximate truth) of theories understood in terms of some version of
the correspondence theory of truth (as suggested by Fine 1986a and
contested by Ellis 1988), some prefer a truthmaker account (Asay 2013)
or a deflationary account of truth (Giere 1988: 82; Devitt 2005; Leeds
2007). Though most realists marry their position to the successful
reference of theoretical terms, including those for unobservable
entities (Boyd 1983, and as described by Laudan 1981), some deny that
this is a requirement (Cruse & Papineau 2002; Papineau 2010).
Amidst these differences, however, a general recipe for realism is
widely shared: our best scientific theories give true or approximately
true descriptions of observable and unobservable aspects of a
mind-independent world.


### 1.3 Qualifications and Variations



The general recipe for realism just described is accurate so far as it
goes, but still falls short of the degree of precision offered by most
realists. The two main sources of imprecision thus far are found in
the general recipe itself, which makes reference to the idea of
"our best scientific theories" and the notion of
"approximate truth". The motivation for these
qualifications is perhaps clear. If one is to defend a positive
epistemic attitude regarding scientific theories, it is presumably
sensible to do so not merely in connection with any theory (especially
when one considers that, over the long history of the sciences up to
the present, some theories were not or are not especially successful),
but rather with respect to theories (or *aspects* of theories,
as we will see momentarily) that would appear, *prima facie*,
to merit such a defense, *viz*. our best theories (or aspects
thereof). And it is widely held, not least by realists, that even many
of our best scientific theories are likely false, strictly speaking,
hence the importance of the notion that theories may be "close
to" the truth (that is, approximately true) even though they are
false. The challenge of making these qualifications more precise,
however, is significant, and has generated much discussion.



Consider first the issue of how best to identify those theories that
realists should be realists about. A general disclaimer is in order
here: realists are generally fallibilists, holding that realism is
appropriate in connection with our best theories even though they
likely cannot be proven with absolute certainty; some of our best
theories could conceivably turn out to be significantly mistaken, but
realists maintain that, granting this possibility, there are grounds
for realism nonetheless. These grounds are bolstered by restricting
the domain of theories suitable for realist commitment to those that
are sufficiently mature and non-*ad hoc* (Worrall 1989:
153-154; Psillos 1999: 105-108). Maturity may be thought
of in terms of the well established nature of the field in which a
theory is developed, or the duration of time a theory has survived, or
its survival in the face of significant testing; and the condition of
being non-*ad hoc* is intended to guard against theories that
are "cooked up" (that is, posited merely) in order to
account for some known observations in the absence of rigorous
testing. On these construals, however, both the notion of maturity and
the notion of being non-*ad hoc* are admittedly vague. One
strategy for adding precision here is to attribute these qualities to
theories that make successful, novel predictions. The ability of a
theory to do this, it is commonly argued, marks it as genuinely
empirically successful, and the sort of theory to which realists
should be more inclined to commit (Musgrave 1988; Lipton 1990; Leplin
1997; White 2003; Hitchcock & Sober 2004; Barnes 2008; for a
dissenting view, see Harker 2008; cf. Alai 2014).



The idea that with the development of the sciences over time, theories
are converging on ("moving in the direction of",
"getting closer to") the truth, is a common theme in
realist discussions of theory change (for example, Hardin &
Rosenberg 1982 and Putnam 1982). Talk of approximate truth is often
invoked in this context and has produced a significant amount of often
highly technical work, conceptualizing the approximation of truth as
something that can be quantified, such that judgments of relative
approximate truth (of one proposition or theory in comparison to
another) can be formalized and given precise definitions. This work
provides one possible means by which to consider the convergentist
claim that theories can be viewed as increasingly approximately true
over time, and this possibility is further considered in
 section 3.4.



A final and especially important qualification to the general recipe
for realism described above comes in the form of a number of
variations. These species of generic realism can be viewed as falling
into three families or camps: explanationist realism; entity realism;
and structural realism. There is a shared principle of speciation
here, in that all three approaches are attempts to identify more
specifically the component parts of scientific theories that are most
worthy of epistemic commitment. *Explanationism* recommends
realist commitment with respect to those parts of our best
theories--regarding (unobservable) entities, laws,
etc.--that are in some sense indispensable or otherwise important
to explaining their empirical success--for instance, components
of theories that are crucial in order to derive successful, novel
predictions. *Entity realism* is the view that under conditions
in which one can demonstrate impressive causal knowledge of a putative
(unobservable) entity, such as knowledge that facilitates the
manipulation of the entity and its use so as to intervene in other
phenomena, one has good reason for realism regarding it.
*Structural realism* is the view that one should be a realist,
not in connection with descriptions of the natures of things (like
unobservable entities) found in our best theories, but rather with
respect to their structure. All three of these positions adopt a
strategy of selectivity, and this and the positions themselves are
considered further in
 section 2.3.



Arguably, the fact that realists have endeavored to qualify their view
and propose variations of it, as described above, suggests a
collective moral: though some (especially earlier) discussions of
realism give the impression that it is an attitude pertaining to
science across the board, this is likely too coarse a way to
understand the position. Adopting a realist attitude toward the
content of scientific theories does not entail that one believes all
such content, but rather that one believes those aspects, including
unobservable aspects, regarding which one takes such belief to be
warranted, thus indicating a realism about those things more
specifically. In a similar spirit, some argue for another sort of
specificity, suggesting that the best (or only good) arguments for
realism are formulated by concentrating on the details of specific
cases--the so-called "first-order evidence" of
scientific investigation itself. For example, leveraging a case study
of Jean Perrin's argument in 1908 for the reality of
unobservable molecules, Achinstein (2002: 491-495) contends that
even taking certain realist-friendly assumptions for granted, a
compelling argument for realism about any given entity can only be
given in terms of the empirical evidence concerning that entity, not
by means of more general philosophical arguments. (For similar views,
see Magnus & Callender 2004: 333-336 and Saatsi 2010; for
skepticism about this, see Dicken 2013 and Park 2016.)


## 2. Considerations in Favor of Scientific Realism (and Responses)


### 2.1 The Miracle Argument



The most powerful intuition motivating realism is an old idea,
commonly referred to in recent discussions as the "miracle
argument" or "no miracles argument", after
Putnam's (1975a: 73) claim that realism "is the only
philosophy that doesn't make the success of science a
miracle". The argument begins with the widely accepted premise
that our best theories are extraordinarily successful: they facilitate
empirical predictions, retrodictions, and explanations of the subject
matters of scientific investigation, often marked by astounding
accuracy and intricate causal manipulations of the relevant phenomena.
What explains this success? One explanation, favored by realists, is
that our best theories are true (or approximately true, or correctly
describe a mind-independent world of entities, laws, etc.). Indeed, if
these theories were far from the truth, so the argument goes, the fact
that they are so successful would be miraculous. And given the choice
between a straightforward explanation of success and a miraculous
explanation, clearly one should prefer the non-miraculous explanation,
*viz*. that our best theories are approximately true (etc.).
(For elaborations of the miracle argument, see J. Brown 1982; Boyd
1989; Lipton 1994; Psillos 1999: ch. 4; Barnes 2002; Lyons 2003; Busch
2008; Frost-Arnold 2010; and Dellsen 2016.)



Though intuitively powerful, the miracle argument is contestable in a
number of ways. One skeptical response is to question the very need
for an explanation of the success of science in the first place. For
example, van Fraassen (1980: 40; see also Wray 2007, 2010) suggests
that successful theories are analogous to well-adapted
organisms--since only successful theories (organisms) survive, it
is hardly surprising that our theories are successful, and therefore,
there is no demand here for an explanation of success. It is not
entirely clear, however, whether the evolutionary analogy is
sufficient to dissolve the intuition behind the miracle argument. One
might wonder, for instance, why a *particular* theory is
successful (as opposed to why theories in general are successful), and
the explanation sought may turn on specific features of the theory
itself, including its descriptions of unobservables. Whether such
explanations need be true, though, is a matter of debate. While most
theories of explanation require that the *explanans* be true,
pragmatic theories of explanation do not (van Fraassen 1980: ch. 5).
More generally, any epistemology of science that does not accept one
or more of the three dimensions of realism--commitment to a
mind-independent world, literal semantics, and epistemic access to
unobservables--will thereby present a putative reason for
resisting the miracle argument. These positions are considered in
 section 4.



Some authors contend that the miracle argument is, in fact, an
instance of fallacious reasoning called the base rate fallacy (Howson
2000: ch. 3; Lipton [1991] 2004: 196-198; Magnus & Callender
2004). Consider the following illustration. There is a test for a
disease for which the rate of false negatives (negative results in
cases where the disease is present) is zero, and the rate of false
positives (positive results in cases where the disease is absent) is
one in ten (that is, disease-free individuals test positive 10% of the
time). If one tests positive, what are the chances that one has the
disease? It would be a mistake to conclude that, based on the rate of
false positives, the probability is 90%, for the actual probability
depends on some further, crucial information: the base rate of the
disease in the population (the proportion of people having it). The
lower the incidence of the disease at large, the lower the probability
that a positive result signals the presence of the disease.



By analogy, using the success of a scientific theory as an indicator
of its approximate truth (assuming a low rate of false
positives--cases in which theories far from the truth are
nonetheless successful) is arguably, likewise, an instance of the base
rate fallacy. The success of a theory does not by itself suggest that
it is likely approximately true, and since there is no independent way
of knowing the base rate of approximately true theories, the chances
of it being approximately true cannot be assessed. Worrall (unpublished,
Other Internet Resources) maintains that these contentions are
ineffective against the miracle argument because they crucially depend
on a misleading formalization of it in terms of probabilities
(cf. Menke 2014; for a criticism of the miracle argument based on a
different probabilistic framing in terms of likelihoods, see Sober
2015: 912-915).


### 2.2 Corroboration



One motivation for realism in connection with at least some
unobservables comes by way of "corroboration". If an
unobservable entity is putatively capable of being detected by means
of a scientific instrument or experiment, this may well form the basis
of a defeasible argument for realism concerning it. If, however, that
same entity is putatively capable of being detected by not just one,
but rather two or more *different* means of
detection--forms of detection that are distinct with respect to
the apparatuses they employ and the causal mechanisms and processes
they are described as exploiting in the course of detection--this
may serve as the basis of a significantly enhanced argument for
realism (cf. Eronen 2015). Hacking (1983: 201; see also Hacking 1985:
146-147) gives the example of dense bodies in red blood
platelets that can be detected using different forms of microscopy.
Different techniques of detection, such as those employed in light
microscopy and transmission electron microscopy, make use of very
different sorts of physical processes, and these operations are
described theoretically in terms of correspondingly different causal
mechanisms. (For similar examples, see Salmon 1984: 217-219 and
Franklin 1986: 166-168, 1990: 103-115.)



The argument from corroboration thus runs as follows. The fact that
one and the same thing is apparently revealed by distinct modes of
detection suggests that it would be an extraordinary coincidence if
the supposed target of these revelations did not, in fact, exist. The
greater the extent to which detections can be corroborated by
different means, the stronger the argument for realism regarding their
putative target. The argument here can be viewed as resting on an
intuition similar to that underlying the miracle argument: realism
based on apparent detection may be only so compelling, but if
different, theoretically independent means of detection produce the
same result, suggesting the existence of one and the same
unobservable, then realism provides a good explanation of the
consilient evidence, in contrast with the arguably miraculous state of
affairs in which theoretically independent techniques produce the same
result in the absence of a shared target. The idea that techniques of
(putative) detection are often constructed or calibrated precisely
with the intention of reproducing the outputs of others, however, may
stand against the argument from corroboration. Additionally, van
Fraassen (1985: 297-298) argues that scientific explanations of
evidential consilience may be accepted without the explanations
themselves being understood as true, which once again raises questions
about the nature of scientific explanation.


### 2.3 Selective Optimism/Skepticism



In
 section 1.3,
 the notion of selectivity was introduced as a general strategy for
maximizing the plausibility of realism, particularly with respect to
scientific unobservables. This strategy is adopted in part to square
realism with the widely accepted view that most if not all of even our
best theories are false, strictly speaking. If, nevertheless, there
are aspects of these theories that are true (or close to the truth)
and one is able to identify these aspects, one might then plausibly
cast one's realism in terms of an epistemically positive
attitude toward those aspects of theories that are most worthy of
epistemic commitment. The most important variants of realism to
implement this strategy are explanationism, entity realism, and
structural realism. (For related work pertaining to the notion of
selectivity more generally, see R. Miller 1987: chs. 8-10; Fine
1991; Jones 1991; Musgrave 1992; Harker 2013; and Peters 2014.)



Explanationists hold that a realist attitude can be justified in
connection with unobservables described by our best theories precisely
when appealing to those unobservables is indispensable or otherwise
important to explaining why these theories are successful. For
example, if one takes successful novel prediction to be a hallmark of
theories worthy of realist commitment generally, then explanationism
suggests that, more specifically, those aspects of the theory that are
essential to the derivation of such novel predictions are the parts of
the theory most worthy of realist commitment. In this vein, Kitcher
(1993: 140-149) draws a distinction between the
"presuppositional posits" or "idle parts" of
theories, and the "working posits" to which realists
should commit. Psillos (1999: chs. 5-6) argues that realism can
be defended by demonstrating that the success of past theories did not
depend on their false components: 



> 
> 
> it is enough to show that the theoretical laws and mechanisms which
> generated the successes of past theories have been retained in our
> current scientific image. (1999: 108) 
> 
> 
> 



The immediate challenge to explanationism is to furnish a method with
which to identify precisely those aspects of theories that are
required for their success, in a way that is objective or principled
enough to withstand the charge that realists are merely rationalizing
*post hoc*, identifying the explanatorily crucial parts of past
theories with aspects that have been retained in our current best
theories. (For discussions, see Chang 2003; Stanford 2003a,b; Elsamahi
2005; Saatsi 2005a; Lyons 2006; Harker 2010; Cordero 2011; Votsis
2011; and Vickers 2013.)



Another version of realism that adopts the strategy of selectivity is
entity realism. On this view, realist commitment is based on a
putative ability to causally manipulate unobservable entities (like
electrons or gene sequences) to a high degree--for example, to
such a degree that one is able to intervene in other phenomena so as
to bring about certain effects. The greater the ability to exploit
one's apparent causal knowledge of something so as to bring
about (often extraordinarily precise) outcomes, the greater the
warrant for belief (Hacking 1982, 1983; cf. B. Miller 2016; Cartwright
1983: ch. 5; Giere 1988: ch. 5; on causal warrant more generally, see Egg 2012). Belief
in scientific unobservables thus described is here partnered with a
degree of skepticism about scientific theories more generally, and
this raises questions about whether believing in entities while
withholding belief with respect to the theories that describe them is
a coherent or practicable combination (Morrison 1990; Elsamahi 1994;
Resnik 1994; Chakravartty 1998; Clarke 2001; Massimi 2004). Entity
realism is especially compatible with and nicely facilitated by the
causal theory of reference associated with Kripke (1980) and Putnam
([1975b] 1985: ch. 12), according to which one can successfully refer
to an entity despite significant or even radical changes in
theoretical descriptions of its properties; this allows for stability
of epistemic commitment when theories change over time. Whether the
causal theory of reference can be applied successfully in this
context, however, is a matter of dispute (see Hardin & Rosenberg
1982; Laudan 1984; Psillos 1999: ch. 12; McLeish 2005, 2006; Chakravartty 2007a:
52-56; and Landig 2014; see Weber 2014 for a case study on
genes).



Structural realism is another view promoting selectivity, but in this
case it is the natures of unobservable entities that are viewed
skeptically, with realism reserved for the structure of the
unobservable realm, as represented by certain relations described by
our best theories. All of the many versions of this position fall into
one of two camps: the first emphasizes an epistemic distinction
between notions of structure and nature; the second emphasizes an
ontological thesis. The epistemic view holds that our best theories
likely do not correctly describe the natures of unobservable entities,
but do successfully describe certain relations between them. The ontic
view suggests that the reason realists should aspire only to knowledge
of structure is that the traditional concept of entities that stand in
relations is metaphysically problematic--there are, in fact, no
such things, or if there are such things, they are in some sense
emergent from or dependent on their relations. One challenge facing
the epistemic version is that of articulating a concept of structure
that makes knowledge of it effectively distinct from that of the
natures of entities. The ontological version faces the challenge of
clarifying the relevant notions of emergence and/or dependence. (On
epistemic structural realism, see Worrall 1989; Psillos 1995, 2006;
Votsis 2003; and Morganti 2004; regarding ontic structural realism,
see French 1998, 2006, 2014; Ladyman 1998; Psillos 2001, 2006; Ladyman
& Ross 2007; and Chakravartty 2007a: ch. 3. See Frigg & Votsis
2011 for an extensive critical survey).


## 3. Considerations Against Scientific Realism (and Responses)


### 3.1 The Underdetermination of Theory by Data



Lined up in opposition to the various motivations for realism
presented in
 section 2
 are a number of important antirealist arguments, all of which have
pressed realists either to attempt their refutation, or to modify
their realism accordingly. One of these challenges, the
underdetermination of theory by data, has a storied history in
twentieth century philosophy more generally, and is often traced to
the work of Duhem ([1906] 1954: ch. 6; this is not an argument for
underdetermination as such, but is regarded as sowing the seeds). In
remarks concerning the confirmation of scientific hypotheses (in
physics, which he contrasted with chemistry and physiology), Duhem
noted that a hypothesis cannot be used to derive testable predictions
in isolation. To derive predictions one also requires
"auxiliary" assumptions, such as background theories,
hypotheses about instruments and measurements, etc. If subsequent
observation and experiment produces data that conflict with those
predicted, one might think that this reflects badly on the hypothesis
under test, but Duhem pointed out that given all of the assumptions
required to derive predictions, it is no simple matter to identify
where the error lies. Different amendments to one's overall set
of beliefs regarding hypotheses and theories will be consistent with
the data. A similar result is commonly associated with the later
"confirmational holism" of Quine (1953), according to
which experience (including, of course, that associated with
scientific testing) does not confirm or disconfirm individual beliefs
*per se*, but rather the set of one's beliefs taken as a
whole. This sort of contention is now commonly referred to as the
"Duhem-Quine thesis" (Quine 1975; see Ben-Menahem 2006 for
a historical introduction).



How then does this give rise to underdetermination, a presumptive
concern for realism? The argument from underdetermination proceeds as
follows: let us call the relevant, overall sets of scientific beliefs
"theories"; different, conflicting theories are consistent
with the data; the data exhaust the evidence for belief; therefore,
there is no evidential reason to believe one of these theories as
opposed to another. Given that the theories differ precisely in what
they say about the unobservable (their observable
consequences--the data--are all shared), a challenge to
realism emerges: the choice of which theory to believe is
*underdetermined* by the data. In contemporary discussions, the
challenge is usually presented using slightly different terminology.
Every theory, it is said, has empirically equivalent rivals--that
is, rivals that agree with respect to the observable, but differ with
respect to the unobservable. This then serves as the basis of a
skeptical argument regarding the truth of any particular theory the
realist may wish to endorse. Various forms of antirealism then suggest
that hypotheses and theories involving unobservables are endorsed, not
merely on the basis of evidence that may be relevant to their truth,
but also on the basis of other factors that are not indicative of
truth as such (see
 sections 3.2,
 and
 4.2-4.4).
 (For recent explications, see van Fraassen 1980: ch. 3; Earman 1993;
Kukla 1998: chs. 5-6; and Stanford 2001.)



The argument from underdetermination is contested in a number of ways.
One might, for example, distinguish between underdetermination in
practice (or at a time) and underdetermination in principle. In the
former case, there is underdetermination only because the data that
would support one theory or hypothesis at the expense of another is
unavailable, pending foreseeable developments in experimental
technique or instrumentation. Here, realism is arguably consistent
with a "wait and see" attitude, though if the prospect of
future discriminating evidence is poor, a commitment to future realism
may be questioned thereby. In any case, most proponents of
underdetermination insist on the idea of underdetermination in
principle: the idea that there are always (plausible) empirically
equivalent rivals no matter what evidence may come to light. In
response, some argue that the principled worry cannot be established,
since what counts as data is apt to change over time with the
development of new techniques and instruments, and with changes in
scientific background knowledge, which alter the auxiliary assumptions
required to derive observable predictions (Laudan & Leplin 1991).
Such arguments may rest, however, on a different conception of
observation than that assumed by many antirealists (defined above, in
terms of human sensory capacities). (For other responses, see Okasha
2002; van Dyck 2007; Busch 2009; and Worrall 2011.)



Stanford (2006, 2015) proposes a historicized version of the argument
from underdetermination, suggesting that the history of science
reveals a recurring "problem of unconceived alternatives":
typically, at any given time, there are theories that do not occur to
scientists but which are just as well confirmed by the available
evidence as those that are, in fact, accepted; furthermore, over time,
such unconceived theories often supplant the theories adopted by
historical actors as the relevant science develops. (For discussions
and evaluations of this challenge, see Chakravartty 2008;
Godfrey-Smith 2008; Magnus 2010; Lyons 2013; Mizrahi 2015:
139-146; and Egg 2016; cf. Wray 2008 and Khalifa 2010 on the
related notion of "underconsideration", as described by
Lipton 1993, [1991] 2004: 151-163.)


### 3.2 Skepticism about Inference to the Best Explanation



One especially important reaction to concerns about the alleged
underdetermination of theory by data gives rise to another leading
antirealist argument. This reaction is to reject one of the key
premises of the argument from underdetermination, *viz*. that
evidence for belief in a theory is exhausted by the empirical data.
Many realists contend that other considerations--most
prominently, *explanatory* considerations--play an
evidential role in scientific inference. If this is so, then even if
one were to grant the idea that all theories have empirically
equivalent rivals, this would not entail underdetermination, for the
explanatory superiority of one in particular may determine a choice
(Laudan 1990; Day & Botterill 2008). This is a specific
exemplification of a form of reasoning by which "we infer what
would, if true, provide the best explanation of [the] evidence"
(Lipton [1991] 2004: 1). To put a realist-sounding spin on it: 



> 
> 
> one infers, from the premise that a given hypothesis would provide a
> "better" explanation for the evidence than would any other
> hypothesis, to the conclusion that the given hypothesis is true.
> (Harman 1965: 89) 
> 
> 
> 



Inference to the best explanation (as per Lipton's formulation)
seems ubiquitous in scientific practice. The question of whether it
can be expected to yield knowledge of the sort suggested by realism
(as per Harman's formulation) is, however, a matter of
dispute.



Two difficulties are immediately apparent regarding the realist
aspiration to infer truth (approximate truth, existence of entities,
etc.) from hypotheses or theories that are judged best on explanatory
grounds. The first concerns the grounds themselves. In order to judge
that one theory furnishes a better explanation of some phenomenon than
another, one must employ some criterion or criteria on the basis of
which the judgment is made. Many have been proposed: simplicity
(whether of mathematical description or in terms of the number or
nature of the entities involved); consistency and coherence (both
internally, and externally with respect to other theories and
background knowledge); scope and unity (pertaining to the domain of
phenomena explained); and so on. One challenge here concerns whether
virtues such as these can be defined precisely enough to permit
relative rankings of explanatory goodness. Another challenge concerns
the multiple meanings associated with some virtues (consider, for
example, mathematical versus ontological simplicity). Another concerns
the possibility that such virtues may not all favor any one theory in
particular. Finally, there is the question of whether these virtues
should be considered evidential or epistemic, as opposed to merely
pragmatic. What reason is there to think, for instance, that
simplicity is an indicator of truth? Thus, the ability to rank
theories with respect to their likelihood of being true may be
questioned.



A second difficulty facing inference to the best explanation concerns
the pools of theories regarding which judgments of relative
explanatory efficacy are made. Even if scientists are likely reliable
rankers of theories with respect to truth, this will not lead to
belief in a true theory (in some domain) unless that theory in
particular happens to be among those considered. Otherwise, as van
Fraassen (1989: 143) notes, one may simply end up with "the best
of a bad lot". Given the widespread view, even among realists,
that many and perhaps most of our best theories are false, strictly
speaking, this concern may seem especially pressing. However, in just
the way that the realist strategy of selectivity (see
 section 2.3)
 may offer responses to the question of what it could mean for a
theory to be close to the truth without being true
*simpliciter*, this same strategy may offer the beginnings of a
response here. That is to say, the best theory of a bad lot may
nonetheless describe unobservable aspects of the world in such a way
as to meet the standards of variants of realism including
explanationism, entity realism, and structural realism. (For a
book-length treatment of inference to the best explanation, see Lipton
[1991] 2004; for defenses, see Lipton 1993; Day & Kincaid 1994;
and Psillos 1996, 2009: part III; for critiques, see van Fraassen
1989: chs. 6-7; Ladyman, Douven, Horsten, & van Fraassen
1997; Wray 2008; and Khalifa 2010.)


### 3.3 The Pessimistic Induction



Worries about underdetermination and inference to the best explanation
are generally conceptual in nature, but the so-called pessimistic
induction (also called the "pessimistic meta-induction",
because it concerns the "ground level" inductive
inferences that generate scientific theories and law statements) is
intended as an argument from empirical premises. If one considers the
history of scientific theories in any given discipline, what one
typically finds is a regular turnover of older theories in favor of
newer ones, as scientific knowledge develops. From the point of view
of the present, most past theories must be considered false; indeed,
this will be true from the point of view of most times. Therefore, by
enumerative induction (that is, generalizing from these cases), surely
theories at any given time will ultimately be replaced and regarded as
false from some future perspective. Thus, current theories are also
false. The general idea of the pessimistic induction has a rich
pedigree. Though neither endorse the argument, Poincare ([1905]
1952: 160), for instance, describes the seeming "bankruptcy of
science" given the apparently "ephemeral nature" of
scientific theories, which one finds "abandoned one after
another", and Putnam (1978: 22-25) describes the challenge
in terms of the failure of reference of terms for unobservables, with
the consequence that theories incorporating them cannot be said to be
true. (For a summary of different formulations, see Wray 2015.)



Contemporary discussion commonly focuses on Laudan's (1981)
argument to the effect that the history of science furnishes vast
evidence of empirically successful theories that were later rejected;
from subsequent perspectives, their unobservable terms were judged not
to refer and thus, they cannot not be regarded as true or even
approximately true. (If one prefers to define realism in terms of
scientific ontology rather than reference and truth, one may rephrase
the worry in terms of the mistaken ontologies of past theories from
later perspectives.) Responses to this argument generally take one of
two forms, the first stemming from the qualifications to realism
outlined in
 section 1.3,
 and the second from the forms of realist selectivity outlined in
 section 2.3--both
 can be understood as attempts to restrict the inductive basis of the
argument in such a way as to foil the pessimistic conclusion. For
example, one might contend that if only sufficiently mature and
non-*ad hoc* theories are considered, the number whose central
terms did not refer and/or that cannot be regarded as approximately
true is dramatically reduced (see references,
 section 1.3).
 Or, the realist might grant that the history of science presents a
record of significant referential discontinuity, but contend that,
nevertheless, it also presents a record of impressive continuity
regarding what is properly endorsed by realism, as recommended by
explanationists, entity realists, or structural realists (see
references,
 section 2.3).
 (For other responses, see Leplin 1981; McAllister 1993; Chakravartty
2007a: ch. 2; Doppelt 2007; Nola 2008; Roush 2010, 2015; and Fahrbach
2011. Hardin & Rosenberg 1982; Cruse & Papineau 2002; and
Papineau 2010 explore the idea that reference is irrelevant to
approximate truth).



In just the way that some authors suggest that the miracle argument is
an instance of fallacious reasoning--the base rate fallacy (see
 section 2.1)--some
 suggest that the pessimistic induction is likewise flawed (Lewis
2001; Lange 2002; Magnus & Callender 2004). The argument is
analogous: the putative failure of reference on the part of past
successful theories, or their putative lack of approximate truth,
cannot be used to derive a conclusion regarding the chances that our
current best theories do not refer to unobservables, or that they are
not approximately true, unless one knows the base rate of
non-referring or non-approximately true theories in the relevant
pools. And since one cannot know this independently, the pessimistic
induction is fallacious. Again, analogously, one might argue that to
formalize the argument in terms of probabilities, as is required in
order to invoke the base rate fallacy, is to miss the more fundamental
point underlying the pessimistic induction (Saatsi 2005b). One might
read the argument simply as cutting a supposed link between the
empirical success of scientific theories and successful reference or
approximate truth, as opposed to relying on an inductive inference
*per se*. If even a few examples from the history of science
demonstrate that theories can be empirically successful and yet fail
to refer to the central unobservables they invoke, or fail to be what
realists would regard as approximately true, this constitutes a
*prima facie* challenge to the notion that only realism can
explain the success of science.


### 3.4 Skepticism about Approximate Truth



The regular appeal to the notion of approximate truth by realists has
several motivations. The widespread use of abstraction (that is,
incorporating some but not all of the relevant parameters into
scientific descriptions) and idealization (distorting the natures of
certain parameters) suggests that even many of our best theories and
models are not strictly correct. The common realist contention that
theories can be viewed as gradually converging on the truth as
scientific inquiry advances suggests that such progress is amenable to
assessment or measurement in some way, if only in principle. And even
for realists who are not convergentists as such, the importance of
cashing out the metaphor of theories being close to the truth is
pressing in the face of antirealist assertions to the effect that the
metaphor is empty. The challenge to make good on the metaphor and
explicate, in precise terms, what approximate truth could be, is one
source of skepticism about realism. Two broad strategies have emerged
in response to this challenge: attempts to quantify approximate truth
by formally defining the concept and the related notion of relative
approximate truth; and attempts to explicate the concept
informally.



The formal route was inaugurated by Popper (1972: 231-236), who
defined relative orderings of "verisimilitude" (literally,
"likeness to truth") between theories in a given domain
over time by means of a comparison of their true and false
consequences. D. Miller (1974) and Tichy (1974) proved that
there is a technical problem with this account, however, yielding the
consequence that in order for theory *A* to have greater
verisimilitude than theory *B*, *A* must be true
*simpliciter*, which leaves the realist desideratum of
explaining how strictly false theories can differ with respect to
approximate truth unsatisfied (see also Oddie 1986a). Another formal
account is the possible worlds approach (also called the
"similarity" approach), according to which the truth
conditions of a theory are identified with the set of possible worlds
in which it is true, and "truth-likeness" is calculated by
means of a function that measures the average or some other
mathematical "distance" between the actual world and the
worlds in that set, thereby facilitating orderings of theories with
respect to truth-likeness (Tichy 1976, 1978; Oddie 1986b;
Niiniluoto 1987, 1998; for critiques, see D. Miller 1976 and Aronson
1990). One last attempt to formalize approximate truth is the type
hierarchies approach, which analyzes truth-likeness in terms of
similarity relationships between nodes in tree-structured graphs of
types and subtypes representing scientific concepts on the one hand,
and the entities in the world they putatively represent on the other
(Aronson 1990; Aronson, Harre, & Way 1994: 15-49; for
a critique, see Psillos 1999: 270-273).



Less formally and perhaps more typically, realists have attempted to
explicate approximate truth in qualitative terms. One common
suggestion is that a theory may be considered more approximately true
than one that preceded it if the earlier theory can be described as a
"limiting case" of the later one. The idea of limiting
cases and inter-theory relations more generally is elaborated by Post
(1971; see also French & Kamminga 1993), who argues that certain
heuristic principles in science yield theories that
"conserve" the successful parts of their predecessors. His
"General Correspondence Principle" states that later
theories commonly account for the successes of their predecessors by
"degenerating" into earlier theories in domains in which
the earlier ones are well confirmed. Hence, for example, the often
cited claim that certain equations in relativistic physics degenerate
into the corresponding equations in classical physics in the limit, as
velocity tends to zero. The realist may then contend that later
theories offer more approximately true descriptions of the relevant
subject matter, and that the ways in which they do this can be
illuminated in part by studying the ways in which they build on the
limiting cases represented by their predecessors. (For further takes
on approximate truth, see Leplin 1981; Boyd 1990; Weston 1992; Smith
1998; Chakravartty 2010, and Northcott 2013.)


## 4. Antirealism: Foils for Scientific Realism


### 4.1 Empiricism



The term "antirealism" (or "anti-realism")
encompasses any position that is opposed to realism along one or more
of the dimensions canvassed in
 section 1.2:
 the metaphysical commitment to the existence of a mind-independent
reality; the semantic commitment to interpret theories literally or at
face value; and the epistemological commitment to regard theories as
furnishing knowledge of both observables and unobservables. As a
result, and as one might expect, there are many different ways to be
an antirealist, and many different positions qualify as antirealism
(cf. Kitcher 2001: 161-163). In the historical development of
realism, arguably the most important strains of antirealism have been
varieties of empiricism which, given their emphasis on experience as a
source and subject matter of knowledge, are naturally set against the
idea of knowledge of unobservables. It is possible to be an empiricist
more broadly speaking in a way that is consistent with
realism--for example, one might endorse the idea that knowledge
of the world stems from empirical investigation and contend that on
this basis, one can justifiably infer certain things about
unobservables. In the first half of the twentieth century, however,
empiricism came predominantly in the form of varieties of
"instrumentalism": the view that theories are merely
instruments for predicting observable phenomena or systematizing
observation reports.



According to the best known, traditional form of instrumentalism,
terms for unobservables have no meaning all by themselves; construed
literally, statements involving them are not even candidates for truth
or falsity (cf. a more recent proposal in Rowbottom 2011). The most
influential advocates of this view were the logical empiricists (or
logical positivists), including Carnap and Hempel, famously associated
with the Vienna Circle group of philosophers and scientists as well as
important contributors elsewhere. In order to rationalize the
ubiquitous use of terms which might otherwise be taken to refer to
unobservables in scientific discourse, they adopted a non-literal
semantics according to which these terms acquire meaning by being
associated with terms for observables (for example,
"electron" might mean "white streak in a cloud
chamber"), or with demonstrable laboratory procedures (a view
called "operationalism"). Insuperable difficulties with
this semantics led ultimately (in large measure) to the demise of
logical empiricism and the growth of realism. The contrast here is not
merely in semantics and epistemology: a number of logical empiricists
also held the neo-Kantian view that ontological questions
"external" to the frameworks for knowledge represented by
theories are also meaningless (the choice of a framework is made
solely on pragmatic grounds), thereby rejecting the metaphysical
dimension of realism (as in Carnap 1950). (Duhem [1906] 1954 was
influential with respect to instrumentalism; for a critique of logical
empiricist semantics, see H. Brown 1977: ch. 3; on logical empiricism
more generally, see Giere & Richardson 1997 and Richardson &
Uebel 2007; on the neo-Kantian reading, see Richardson 1998 and
Friedman 1999.)



Van Fraassen (1980) reinvented empiricism in the scientific context,
evading many of the challenges faced by logical empiricism by adopting
a realist semantics. His position, "constructive
empiricism", holds that the aim of science is empirical
adequacy, where "a theory is empirically adequate exactly if
what it says about the observable things and events in the world, is
true" (1980: 12; p. 64 gives a more technical definition in
terms of the embedding of observable structures in scientific models).
Crucially, unlike logical empiricism, constructive empiricism
interprets theories in precisely the same manner as realism. The
antirealism of the position is due entirely to its
epistemology--it recommends belief in our best theories only
insofar as they describe observable phenomena, and is satisfied with
an agnostic attitude regarding anything unobservable. The constructive
empiricist thus recognizes claims about unobservables as true or
false, but feels no need to believe or disbelieve them. In focusing on
belief in the domain of the observable, the position is similar to
traditional instrumentalism, and is for this reason sometimes
described as a form of instrumentalism. (For elaborations of the view,
see van Fraassen 1985, 2001 and Rosen 1994.) There are also affinities
here with the idea of fictionalism, according to which things in the
world are and behave *as if* our best scientific theories are
true (Vaihinger [1911] 1923; Fine 1993).


### 4.2 Historicism



The collapse of the logical empiricist program was in part facilitated
by a historical turn in the philosophy of science in the 1960s,
associated with authors such as Kuhn, Feyerabend, and Hanson.
Kuhn's highly influential work, *The Structure of Scientific
Revolutions*, played a significant role in establishing a lasting
interest in a form of historicism about scientific knowledge,
particularly among those interested in the nature of scientific
practice. An underlying principle of the historical turn was to take
the history of science and its practice seriously by furnishing
descriptions of scientific knowledge *in situ*. Kuhn argued
that the fruits of such history illuminate a recurring pattern:
periods of so-called normal science, often fairly long in duration
(consider, for example, the periods dominated by classical physics, or
relativistic physics), punctuated by revolutions which lead scientific
communities from one period of normal science into another. The
implications for realism on this picture derive from Kuhn's
characterization of knowledge on either side of a revolutionary
divide. Two different periods of normal science, he said, are
"incommensurable" with one another, in such a way as to
render the world importantly different after a revolution (the
phenomenon of "world change"). (Among the many detailed
studies of these topics, see Horwich 1993; Hoyningen-Huene 1993;
Sankey 1994; and Bird 2000.)



The notion of incommensurability applies to (*inter alia*) a
comparison of theories operative during different periods of normal
science. Kuhn held that if two theories are incommensurable, they are
not comparable in a way that would permit the judgment that one is
epistemically superior to the other, because different periods of
normal science are characterized by different "paradigms"
(commitments to symbolic representations of the phenomena,
metaphysical beliefs, values, and problem solving techniques). As a
consequence, scientists in different periods of normal science
generally employ different methods and standards, experience the world
differently via "theory laden" perceptions, and most
importantly for Kuhn (1983), differ with respect to the very meanings
of their terms. This is a version of meaning holism or contextualism,
according to which the meaning of a term or concept is exhausted by
its connections to others within a paradigm. A change in any part of
this network entails a change in meanings throughout--the term
"mass", for instance, has different meanings in the
contexts of classical physics and relativistic physics. Thus, any
judgment to the effect that the latter's characterization of
mass is closer to the truth, or even that the relevant theories
describe the same property, is importantly confused: it equivocates
between two different concepts which can only be understood in an
appropriately historicized manner, from the perspectives of the
paradigms in which they occur.



The changes in perception, conceptualization, and language that Kuhn
associated with changes in paradigm also fuelled his notion of world
change, which further extends the contrast of the historicist approach
with realism. There is an important sense, Kuhn maintained, in which
after a scientific revolution, scientists live in a different world.
This is a famously cryptic remark in *Structure* ([1962] 1970:
111, 121, 150), but he (2000: 264) later gives it a neo-Kantian spin:
paradigms function so as to create the reality of scientific
phenomena, thereby allowing scientists to engage with this reality. On
such a view, it would seem that not only the meanings but also the
referents of terms are constrained by paradigmatic boundaries. And
thus, reflecting an interesting parallel with neo-Kantian logical
empiricism, the idea of a paradigm-transcendent world which is
investigated by scientists, and about which one might have knowledge,
has no obvious cognitive content. On this picture, empirical reality
is structured by scientific paradigms, and this conflicts with the
commitment of realism to knowledge of a mind-independent world.


### 4.3 Social Constructivism



One outcome of the historical turn in the philosophy of science and
its emphasis on scientific practice was a focus on the complex social
interactions that inevitably surround and infuse the generation of
scientific knowledge. Relations between experts, their students, and
the public, collaboration and competition between individuals and
institutions, and social, economic, and political contexts became the
subjects of an approach to studying the sciences known as the
sociology of scientific knowledge, or SSK. Though in theory, a
commitment to studying the sciences from a sociological perspective is
interpretable in such a way as to be neutral with respect to realism
(Lewens 2005; cf. Kochan 2010), in practice, most accounts of science
inspired by SSK are implicitly or explicitly antirealist. This
antirealism in practice stems from the common suggestion that once one
appreciates the role that social factors (using this as a generic term
for the sorts of interactions and contexts indicated above) play in
the production of scientific knowledge, a philosophical commitment to
some form of "social constructivism" is inescapable, and
this latter commitment is inconsistent with various aspects of
realism.



The term "social construction" refers to any
knowledge-generating process in which what counts as a fact is
substantively determined by social factors, and in which different
social factors would likely generate facts that are inconsistent with
what is actually produced. The important implication here is thus a
counterfactual claim about the dependence of facts on social factors.
There are numerous ways in which social determinants of facthood may
be consistent with realism. For example, social factors might
determine the directions and methodologies of research that are
permitted, encouraged, and funded, but this by itself need not
undermine a realist attitude with respect to the outputs of scientific
work. Often, however, work in SSK takes the form of case studies that
aim to demonstrate how particular decisions affecting scientific work
were (or are) influenced by social factors which, had they been
different, would have facilitated results that are inconsistent with
those ultimately accepted as scientific fact. Some, including
proponents of the so-called Strong Program in SSK, argue that for more
general, principled reasons, such factual contingency is inevitable.
(For a sample of influential approaches to social constructivism, see
Latour & Woolgar [1979] 1986; Knorr-Cetina 1981; Pickering 1984;
Shapin & Schaffer 1985; and Collins & Pinch 1993; on the
Strong Program, see Barnes, Bloor, & Henry 1996; for a historical
study of the transition from Kuhn to SSK and social constructivism,
see Zammito 2004: chs. 5-7.)



By making social factors an inextricable, substantive determinant of
what counts as true or false in the realm of the sciences (and
elsewhere), social constructivism stands opposed to the realist
contention that theories can be understood as furnishing knowledge of
a mind-independent world. And as in the historicist approach, notions
such as truth, reference, and ontology are here relative to particular
contexts; they have no context-transcendent significance. The later
work of Kuhn and Wittgenstein in particular were influential in the
development of the Strong Program doctrine of "meaning
finitism", according to which the meanings of terms are
conceived as social institutions: the various ways in which they are
used successfully in communication within a linguistic community. This
theory of meaning forms the basis of an argument to the effect that
the meanings of scientific (and other) terms are products of social
negotiation and need not be fixed or determinate, which further
conflicts with a number of realist notions, including the idea of
convergence toward true theories, improvements with respect to
ontology or approximate truth, and determinate reference to
mind-independent entities. The subject of neo-Kantianism thus emerges
here again, though its strength in constructivist doctrines varies
significantly. (For a robustly finitist view, see Kusch 2002; for a
more moderate constructivism, see Putnam's (1981: ch. 3)
"internal realism" and cf. Ellis 1988).


### 4.4 Feminist Approaches



Feminist engagements with science are linked thematically to SSK and
forms of social constructivism by their recognition of the role of
social factors as determinants of scientific fact. That said, they
extend the analysis in a more specific way, reflecting particular
concerns about the marginalization of points of view based on gender,
ethnicity, socio-economic status, and political status. Not all
feminist approaches are antirealist, but nearly all are normative,
offering prescriptions for revising both scientific practice and
concepts such as objectivity and knowledge that have direct
implications for realism. In this regard it is useful to distinguish
(as originally proposed in Harding 1986) between three broad
approaches. Feminist empiricism focuses on the possibility of
warranted belief within scientific communities as a function of the
transparency and consideration of biases associated with different
points of view which enter into scientific work. Standpoint theory
investigates the idea that scientific knowledge is inextricably linked
to perspectives arising from differences in such points of view.
Feminist postmodernism rejects traditional conceptions of universal or
absolute objectivity and truth. (As one might expect, these views are
not always neatly distinguishable; for some early, influential
approaches, see Keller 1985; Harding 1986; Haraway 1988; Longino 1990,
2002; Alcoff & Potter 1993; and Nelson & Nelson 1996).



The notion of objectivity has a number of traditional
connotations--including disinterest (detachment, lack of bias)
and universality (independence from any particular perspective or
viewpoint)--which are commonly associated with knowledge of a
mind-independent world. Feminist critiques are almost unanimous in
rejecting scientific objectivity in the sense of disinterest, offering
case studies that aim to demonstrate how the presence of (for
example) androcentric bias in a scientific community can lead to the
acceptance of one theory at the expense of alternatives (Kourany 2010:
chs. 1-3; for detailed cases, see Longino 1990: ch. 6 and Lloyd
2006). Arguably, the failure of objectivity in this sense is
consistent with realism under certain conditions. For example, if the
relevant bias is epistemically neutral (that is, if one's
assessment of scientific evidence is not influenced by it one way or
another), then realism may remain at least one viable interpretation
of the outputs of scientific work. In the more interesting case where
bias is epistemically consequential, the prospects for realism are
diminished, but may be enhanced by a scientific infrastructure that
functions to bring it under scrutiny (by means of, for example,
effective peer review, genuine consideration of minority views, etc.),
thus facilitating corrective measures where appropriate. The
contention that the sciences do not generally exemplify such an
infrastructure is one motivation for the normativity of much feminist
empiricism.



The challenge to objectivity in the sense of universality or
perspective-independence can be, in some cases, more difficult to
square with the possibility of realism. In a Marxist vein, some
standpoint theorists argue that certain perspectives are epistemically
privileged in the realm of science: *viz*., subjugated
perspectives are epistemically privileged in comparison to dominant
ones in light of the deeper insight afforded the former (just as the
proletariat has a deeper knowledge of human potential than the
superficial knowledge typical of those in power). Others portray
epistemic privilege in a more splintered or deflationary manner,
suggesting that no one point of view can be established as superior to
another by any overarching standard of epistemological assessment.
This view is most explicit in feminist postmodernism, which embraces a
thoroughgoing relativism with respect to truth (and presumably
approximate truth, scientific ontology, and other notions central to
various descriptions of realism). As in the case of Strong Program
SSK, truth and epistemic standards are here defined only within the
context of a perspective, and thus cannot be interpreted in any
context-transcendent or mind-independent manner.


### 4.5 Pragmatism, Quietism, and Dialectical Paralysis



It is not uncommon to hear philosophers remark that the dialogue
between the forms of realism and antirealism surveyed in this article
shows every symptom of a perennial philosophical dispute. The issues
contested range so broadly and elicit so many competing intuitions
(about which, arguably, reasonable people may disagree) that some
question whether a resolution is even possible. This prognosis of
potentially irresolvable dialectical complexity is relevant to a
number of further views in the philosophy of science, some of which
arise as direct responses to it. For example, Fine ([1986b] 1996: chs.
7-8) argues that ultimately, neither realism nor antirealism is
tenable, and recommends what he calls the "natural ontological
attitude" (NOA) instead (see Rouse 1988, 1991 for detailed
explorations of the view). NOA is intended to comprise a neutral,
common core of realist and antirealist attitudes of acceptance of our
best theories. The mistake that both parties make, Fine suggests, is
to add further epistemological and metaphysical diagnoses to this
shared position, such as pronouncements about which aspects of
scientific ontology should be viewed as real, which are proper
subjects of belief, and so on. Others contend that this sort of
approach to scientific knowledge is non- or anti-philosophical, and
defend philosophical engagement in debates about realism (Crasnow
2000, Mcarthur 2006). Musgrave (1989) argues that the view is either
empty or collapses into realism.



The idea of putting the conflict between realist and antirealist
approaches to science aside is also a recurring theme in some accounts
of pragmatism, and quietism. Regarding the first, Peirce ([1992] 1998,
in "How to Make Our Ideas Clear", for instance, originally
published in 1878) holds that the content of a proposition should be
understood in terms of (among other things) its "practical
consequences" for human experience, such as implications for
observation or problem-solving. For James ([1907] 1979), positive
utility measured in these terms is the very marker of truth (where
truth is whatever will be agreed in the ideal limit of scientific
inquiry). Many of the points disputed by realists and
antirealists--differences in epistemic commitment to scientific
entities based on observability, for example--are effectively
non-issues on this view (Almeder 2007; Misak 2010). It is nevertheless
a form of antirealism on traditional readings of Peirce and James,
since both suggest that truth in the pragmatist sense exhausts our
conception of reality, thus running foul of the metaphysical dimension
of realism. The notion of quietism is often associated with
Wittgenstein's response to philosophical problems about which,
he maintained, nothing sensible can be said. This is not to say that
engaging with such a problem is not to one's taste, but rather
that quite independently of one's interest or lack thereof, the
dispute itself concerns a pseudo-problem. Blackburn (2002) suggests
that disputes about realism may have this character.



One last take on the putative irresolvability of debates concerning
realism focuses on certain meta-philosophical commitments adopted by
the interlocutors. Wylie (1986: 287), for instance, claims that 



> 
> 
> the most sophisticated positions on either side now incorporate
> self-justifying conceptions of the aim of philosophy and of the
> standards of adequacy appropriate for judging philosophical theories
> of science. 
> 
> 
> 



Different assumptions *ab initio* regarding what sorts of
inferences are legitimate, what sorts of evidence reasonably support
belief, whether there is a genuine demand for the explanation of
observable phenomena in terms of underlying realities, and so on, may
render some arguments between realists and antirealists
question-begging. This diagnosis is arguably facilitated by van
Fraassen's (1989: 170-176, 1994: 182) intimation that
neither realism nor antirealism (in his case, empiricism) is ruled out
by plausible canons of rationality; each is sustained by a different
conception of how much epistemic risk one should take in forming
beliefs on the basis of one's evidence. An intriguing question
then emerges as to whether disputes surrounding realism and
antirealism are resolvable in principle, or whether, ultimately,
internally consistent and coherent formulations of these positions
should be regarded as irreconcilable but nonetheless permissible
interpretations of scientific knowledge (Chakravartty 2017; Forbes forthcoming).