1. science
2. social science
3. philosophy

Experimental Explication
Jonah N. Schupbach, Philosophy, University of Utah∗
Abstract
Two recently popular metaphilosophical movements, formal philosophy and experimental philosophy, promote what seem to be conflicting methodologies. Nonetheless,
I argue that the two can be mutually supportive. I propose an experimentally-informed
variation on explication, a powerful formal philosophical tool introduced by Carnap.
The resulting method, which I call “experimental explication,” provides the formalist
with a means of responding to explication’s gravest criticism. Moreover, this method
introduces a philosophically salient, positive role for survey-style experiments while
steering clear of several objections that critics of “positive experimental philosophy”
raise. Thus, it provides the experimentalist with a more defensible example of how empirical work can have positive philosophical import. For these reasons, experimental
explication should appeal to experimental philosophers (at least those working within
the positive program) and formal philosophers alike.
Two seemingly incongruent movements have captured much recent metaphilosophical attention. “Experimental philosophy” calls for a renewed focus on empirical methods in the pursuit
of philosophical insight. According to experimental philosophers, philosophical positions and
arguments often involve empirical commitments. When they do, we can make progress by testing those commitments with empirical studies. For experimentalists who endorse the “negative
program,” progress comes by way of new skeptical worries for methods of contemporary analytic
philosophy; we make philosophical gains by realizing our methodological wrongs. For experimentalists who subscribe to the “positive program,” empirical methods constitute a tool to be
∗I
owe thanks to Jonathan Livengood, Joshua Shepherd, and Justin Sytsma for helpful conversation and criticism
regarding this paper. Additionally, I owe a special debt of gratitude to Jack Justus and Edouard Machery, who were both
extremely gracious with their time and energy, reading over several drafts of this paper and providing extensive feedback.
Research for this article was supported by an Aldrich Fellowship from the University of Utah’s Tanner Humanities Center.
1
employed in addition to those of contemporary analytic philosophy when investigating philosophical questions.1
The other movement, “formal philosophy,” calls for the application of logicomathematical
methods in the pursuit of philosophical insight. According to formalists, concepts of philosophical interest may be vague, conflated, unclear, and so on. When this is true, the questions that
philosophers ask involving these concepts adopt the imprecision inherent in the concepts. And
when the questions are unclear in these ways, so is the ensuing philosophical dialogue and the
conditions that must be satisfied by good philosophical answers. To improve this unfortunate
but arguably common situation, formalists endorse the application of formal tools (the languages
of various formal logics or mathematics) to the study of such concepts. By describing concepts
in a logicomathematical language, we gain exact, internally consistent, and disentangled formal
correlates to the original concepts that are clear enough for precise analytic study.
The differences between experimental philosophy and formal philosophy are manifest. One
movement recommends that philosophers enter the world of systematic empirical studies and
employ experimental-scientific tools, typically (though not always) to glean information about
people’s intuitive judgments. The other movement encourages philosophers to think more precisely about the concepts and questions at issue by using more exact tools of thought. Formally
rigorous thinking, presumably pursuable in the comforts of one’s favorite armchair, serves to clarify and demarcate important topics of philosophical debate. These two popular, recent movements
thus seem to oppose one another. At the very least, it is prima facie doubtful that they could be
mutually supportive. Nonetheless, that is what I shall argue in this paper.
To be more specific, I will focus on one common means of doing formal philosophy: Carnap’s
method of explication. In Section 1, I describe this method in some detail, and I distinguish its two
most common philosophical uses. In Section 2, I present the most important historic objection put
to the method of explication, what I call the “Strawsonian challenge.” I argue that this objection’s
merits very much depend on how one is using explication. In fact, Strawson’s objection is arguably
misguided when aimed at the target he had in his own sights – namely, Carnap. However, when
aimed at a common philosophical use of explication today, the Strawsonian challenge is truly
worrying. To meet it, I introduce an experimentally-informed variation on explication in Section
3; this move is not ad hoc, but is naturally motivated by the conditions of adequacy that Carnap
1 Among
others, Kauppinen (2007), Weinberg (2007), Liao (2008), Alexander et al. (2010), Sytsma and Machery (2013),
and Sytsma and Livengood (Forthcoming) all discuss the distinction between experimental philosophy’s negative and positive programs. This distinction is not meant here to be exhaustive of contemporary experimental philosophical research.
For a more careful and complete taxonomy of current experimental philosophical research, see (Sytsma and Livengood,
Forthcoming, Section 2.2).
2
himself imposes on explication. Experimental philosophy thus has much to offer the formal
philosopher. As a matter of terminology, when a philosopher applies experimental methods to
explication in the way that I describe, I will say that the philosopher is applying the method of
experimental explication.
Experimental explication finds an important positive role for people’s surveyed judgments in
doing philosophy. Consequently, objections arise from a chorus of critical voices. Most notably,
experimental philosophers who follow the negative program will question whether these “intuitions” are sufficiently reliable to be of any help in explication. I respond to this and other similar
criticisms in Section 4. Ultimately, I claim that experimental explication provides the experimental
philosopher with a more defensible example of how empirical work can have positive philosophical import. Accordingly, this paper attempts to convince experimentalists and formalists alike
of the value of experimental explication. The upshot is not that all philosophical questions are
susceptible to experimental explication, but rather that this method constitutes an effective but
largely neglected tool for investigating many philosophical questions.
1 Explication and Formal Philosophy
1.1
Carnap on Explication
In the first chapter of Logical Foundations of Probability, Carnap introduces a powerful methodological tool aptly suited for the formal philosopher’s task of making otherwise inexact concepts
precise. Finding inklings of this idea in Kant’s notion of an “explicative judgment” and Husserl’s
“Explikat,” Carnap (1950, p. 3) calls this tool explication.2 He describes explication as follows:
Explication consists in transforming a given more or less inexact concept into an exact
one or, rather, in replacing the first by the second. We call the given concept [...]
the explicandum, and the exact concept proposed to take the place of the first [...]
the explicatum. The explicandum may belong to everyday language or to a previous
stage in the development of scientific language. The explicatum must be given by
explicit rules for its use, for example, by a definition which incorporates it into a
well-constructed system of scientific either logicomathematical or empirical concepts.
Carnap distinguishes explication from “the procedure of analysis” and emphasizes that the
former, unlike the latter, does not require a relation of “complete coincidence” between the con2 But
see (Boniolo, 2003, pp. 293-294) for an intriguing discussion of some “historical oversights” that Carnap made
when citing Kant and Husserl in this regard.
3
cept being clarified and that which does the clarifying (i.e., in explication, the explicandum and
explicatum). In fact, Carnap notes that such a relationship cannot be required of a successful
explication given that the explicandum is imprecise (in virtue of the fact that we are aiming to
explicate it) while the explicatum is required to be more precise – “Since the explicandum is more
or less vague and certainly more so than the explicatum, it is obvious that we cannot require the
correspondence between the two concepts to be a complete coincidence” (Carnap, 1950, p. 5).
Because of this, there is no decisive criterion for deciding whether or not a particular explication is a success. Instead, Carnap asserts that explications are adequate or not to varying degrees
depending on the extent to which they satisfy several desiderata. First, the explicatum ought to be
similar to the explicandum; i.e., “in most cases in which the explicandum has so far been used, the
explicatum can be used” (p. 7). Second, the explicatum must be more exact than the explicandum;
ideally, the explicatum should be stated in the precise terms of some logic or scientific theory.
Third, the explicatum ought to be fruitful in the sense of being “useful for the formulation of [...]
empirical laws [or] logical theorems.” And last, the explicatum should be simple.
As an example of an explicatum stated in scientific terms, Carnap (1950, pp. 12-15) mentions
the concept Temperature, corresponding to inexact “prescientific” explicanda such as Warm and
Warmer.3 The latter concepts, being “based on the heat sensations of the skin,” are relatively
vague and lack precise boundaries of application. The concept Warm, for example, may be applied in very different ways by different people; even the same person may, as we all recognize,
judge the same room to be warm or not depending on whether she is coming from a hot attic
or the cold outdoors. By contrast, the concept Temperature is exceedingly precise and simple.4
Given Temperature’s exactness (and its measurability), conflicting judgments about which of two
rooms is warmer can be quickly resolved once one explicates Warmer with the concept Greater
Temperature. Even with the great increase in precision affected by this explication, Carnap notes
that the explicatum also maintains a nontrivial similarity to the explicandum: “in most cases, if x
is warmer than y [...] then the temperature of x is higher than that of y.” Finally, the explicatum
Temperature has clearly proved its fruitfulness over time, it having a crucial part in the historical
development, statement, and explanation of many scientific laws.
As examples of attempted logical explications, Carnap (1950, pp. 16-18; 1947, pp. 7-8) mentions
Frege and Russell’s accounts of “the elementary concepts of arithmetic” – concepts like One, Two,
Plus, etc. “as they are used [...] for counting things and for calculating with numbers applied to
3 Following
Carnap, I denote concepts by capitalizing the words that standardly designate those concepts. For example,
to refer to the concept standardly designated by the word “bicycle,” I write “the concept Bicycle” or simply “Bicycle”.
4 Carnap relies on an operationalist conception of Temperature, “defined with reference to the thermometer.” Accordingly, he points to Temperature’s straightforward “method of measurement” as constituting its great simplicity (p. 13).
4
things.” Both Frege and Russell explicate numbers with the more precise notion of equivalence
classes, where the relevant equivalence is one of numerosity. Thus, Two is explicated simply as
the set of all pairs, Three as the set of all triples, and so on. Carnap defends this explicatum as
both sufficiently similar to the explicandum and as fruitful by pointing to the theorems provable
“on the basis of this interpretation of the arithmetical [concepts].” As Carnap asserts, a host of
formal statements describing the intuitive structure of numbers along with rules of calculation
(viz., Peano’s Axioms and consequent theorems) are theorems of Frege’s and Russell’s explicata.
The result is “an explication for the terms ‘one’, ‘two’, etc., as they are meant when we apply them
in everyday life.”
Elsewhere, Carnap (1958, p. 2) suggests that the whole project of symbolic logic essentially
involves a series of explications. This is true when it comes to metalogical concepts like Entailment
– thus, Carnap defines a formally precise concept of L-Implication (Logical Implication) and then
he writes: “L-Implication is our explication for the traditional concept which is usually called
‘implication’ or ‘logical implication’ or ‘entailment’, and whose inverse is ordinarily referred to by
such terms as ‘logical consequence’, ‘deducibility’ and the like” (p. 20). But the formal concepts
defined as part of the logic itself may also be seen as explications. Accordingly, one might interpret
the formal concepts designated by the connectives ∼, ∧, ∨, and → as explications of the concepts
of Negation, Conjunction, Disjunction, and Conditionality as used in ordinary language.
1.2
Balancing the Desiderata
An explicatum is adequate to the extent that it is simple, precise, similar to the explicandum, and
fruitful to our search for laws and theorems. Unfortunately, these desiderata do not always play
nicely together. Inevitably, there comes a point at which gains in one desideratum can only be
purchased at the expense of others. One might, for example, be able to introduce ever simpler
explicata but only by trading off increasing degrees of similarity to the explicandum. In any such
event, the explicator eventually must make a crucial decision on what constitutes the best balance
between the desiderata.
Carnap gives us some, but not much, explicit guidance on how properly to balance the desiderata. He notes that simplicity is of secondary importance to similarity, exactness, and fruitfulness.
The simplicity requirement thus effectively mandates that our explicatum be “as simple as the
more important requirements [similarity, exactness, and fruitfulness] permit” (p. 7). He does not,
however, make any parallel statements about the relative importance of the first three desiderata.
It is tempting to interpret Carnap’s silence on this matter as an indication that he places similarity, precision, and fruitfulness all on equal footing, in the sense that no one of these desiderata
5
is always to be preferred over and above the others. However, Carnap’s uses and examples of
explication, taken together with his general philosophical inclinations, rule out this interpretation.
Regarding the case of Temperature and Warmer, Carnap (p. 13) points out that we readily forgo
potential gains in similarity in order to improve our explicatum’s fruitfulness (and simplicity):
It would be possible but highly inadvisable to define a concept Temperature in such a
way that x and y are said to have the same temperature whenever our sensations do
not show a difference. This concept would be in closer agreement with [more similar
to] the explicandum than the concept Temperature actually used. But the latter has the
advantage of much greater simplicity both in its definition – in other words its method
of measurement – and in the laws formulated with its help.
In another example, Carnap (1950, p. 6) discusses the explication of the prescientific concept Fish
(generally encompassing all water-dwelling animals) with the scientific concept of Fish – which
Carnap refers to as “Piscis” in order to distinguish the two. Again in this case, scientists are happy
to trade off great amounts of similarity in order to gain fruitfulness. Despite the fact that Piscis
is “far remote from any concept in the prescientific language,” zoologists replace Fish with this
explanans, which “allows more general statements than any concept defined so as to be more
similar to Fish.”
In these examples, Carnap thus subordinates similarity to fruitfulness. Of course, this does not
imply that similarity just falls by the wayside. In Carnap’s example of Frege’s explication of arithmetical concepts, for example, the explicata arguably retain a great similarity to the explicanda.
Importantly, however, the explicata also score very highly on fruitfulness. Similarity can have a
great influence on one’s choice of explicata, so long as gains in similarity are not purchased at
the expense of fruitfulness. In short, Carnap’s discussions of these examples suggest that one’s
explicatum is satisfactory to the extent that it is as similar to the exlicandum as fruitfulness allows.
This reading of Carnap coheres well not only with his discussion of example explications, but
more importantly with his general methodological pragmatism. Carnap’s motivation for introducing explication was his longstanding dissatisfaction with prevailing concepts; he believed that
such concepts tend to be vague, confused, and inexact. This is problematic because these concepts, in virtue of such inherent imprecision, ultimately hinder epistemic progress in philosophy
and science. Whatever the means by which our prevailing concepts were instilled in us, it was
evidently not via an active, intentional attempt to optimize their effectiveness toward the pursuit
of knowledge. Our working concepts thus are generally not tailored to the search for scientific
laws and logical theorems. We would do much better at representing the world, Carnap believed,
by taking an active role in developing and optimizing the conceptual schemes that we apply in
6
thinking about the world. Explication is the philosophical method that Carnap develops to guide
us to improved concepts; it allows us to construct more exact concepts for the purpose of improving
their epistemic fruitfulness. Many philosophers – (Jeffrey, 1994; Loomis and Juhl, 2006; Carus, 2007;
Kitcher, 2008; Justus, 2012) – accordingly describe Carnap’s general project as one of “concept
engineering.”
Based on the above considerations, it seems that Carnap plays favorites with regards to his
desiderata, prioritizing fruitfulness over similarity. Carnap aside, however, one might wonder
whether other ways of balancing the desiderata are worth considering. So long as one is interested in concept engineering, the balance that Carnap seeks seems uniquely appropriate. So the
question boils down to whether explication can be usefully applied in philosophical projects other
than concept engineering.
In fact, soon after Carnap introduced the method of explication as a tool for concept engineering, John Kemeny and Paul Oppenheim (1952) proposed an alternative use for explication. In their
particular project, Kemeny and Oppenheim focus on the prevailing “intuitive concept” of Factual
Support, a concept which scientists commonly apply – as Kemeny and Oppenheim argue – when
weighing the evidence for and against a theory. Their explicative goal is to “clarify” this concept
by “making it precise.” As Kemeny and Oppenheim themselves emphasize, this constitutes an
important departure from what we might call “Carnapian explication” – the use of explication
for concept engineering. In “Oppenheimian explication,” we are not primarily interested in engineering fruitful new concepts to take the place of our explicanda. Rather, we place our focus on
a prevailing concept (the explicandum) and the overarching goal is to illuminate rather than to
replace this concept.5
How should one balance Carnap’s desiderata when pursuing an Oppenheimian explication?
Kemeny and Oppenheim criticize Carnap for defending his C ∗ as an adequate explication of
Confirmation “by showing that C ∗ has satisfactory consequences.” When fruitfulness is favored as
the primary desideratum in this way, according to Kemeny and Oppenheim, explication “becomes
a tool for grinding an ax,” because explicata are forced to have certain desirable consequences from
the get-go.6 Instead, Kemeny and Oppenheim want to set a new precedent for constructing and
5 Carus
(2007, p. 286) and Maher (2007, p. 333) suggest similar concept clarifying uses for explication.
given the distinction between Carnapian explication (as concept engineering) and Oppenheimian expli-
6 Incidentally,
cation (as concept clarification), Kemeny and Oppenheim’s criticism seems misguided when directed at Carnap. It is
arguably only illegitimate in their sense to require that one’s explicatum have desirable, fruitful consequences if one uses
explication for concept clarification. For example, one might rightly object if a scientific realist requires from the start that
any good explication of Explanatoriness must imply that best explanations are true. But given that Carnap is interested in
engineering new concepts primarily to improve fruitfulness, it hardly makes sense to criticize him for requiring that any
acceptable explicatum have fruitful consequences. As we will see in the next section of the paper, Carnap’s commitment
7
evaluating explications. The idea is to ensure similarity in the construction of the explicata (by
requiring that our clear intuitions about the explicandum are satisfied by any resulting explicatum)
and only to inquire about the consequences of our explicatum post-explication: “We feel that we
must first put down clearly all that our intuition tells us about the explicandum, and then find the
precise [explicata] that satisfy our intuitive requirements. In this sense we hope to set a standard
for explications.”
In other words, Kemeny and Oppenheim recommend that we prize similarity over fruitfulness.
This makes sense in Oppenheimian explication, where the goal is concept clarification rather than
concept engineering. Any explication only has a chance of illuminating the nature, implications,
etc. of some target concept (i.e., the explicandum) to the extent that the end result of the explication (i.e., the explicatum) retains a significant enough similarity to that concept. An explicatum
may be as precise and fruitful as you like, but if this comes at the cost of disconnecting it from
the target concept, then it will not likely teach us anything new about that concept. One might
have successfully engineered an eminently fruitful new concept in this case, but that concept will
have little to do with the explicandum. In Oppenheimian explication then, similarity has lexical
priority over fruitfulness; the explicatum is satisfactory to the extent that it is as fruitful as the more
fundamental desideratum similarity allows.7
To summarize, the proper balance between Carnap’s desiderata is determined in part by one’s
explicative goals. In Carnapian explication, we seek fruitful, precise concepts to take the place of
our imprecise concepts, even at the expense of similarity. The focus here is on the improvement of
our concepts in the service of the empirical or logicomathematical sciences, and it ultimately does
not matter much to this project whether our new concepts resemble the old. In Oppenheimian
explication, we instead are willing to sacrifice potential gains in fruitfulness in order to ensure that
our precise explicatum retains a greater similarity to the explicandum. Here, we desire to shed
new light on unclear concepts by introducing corresponding concepts more readily analyzable by
empirical or logical means. What matters most to the success of this project is whether precise
new concepts do not stray too far from the old – not whether they are somehow useful to science.
to concept engineering also absolves him from Strawson’s main line of criticism. The interesting upshot of this is that
Carnap’s particular project seems to have been more misunderstood than criticized by several of his contemporaries.
7 This is not to say that Oppenheimian explication just amounts to conceptual analysis. The distinction Carnap makes
between explication and analysis (see p. 3 above) holds whether explication is used for concept engineering or concept
clarification. While Oppenheimian explication resembles analysis insofar as it prizes similarity over and above any requirement of fruitfulness, it is unlike analysis in that it gives logicomathematical or scientific precision the same priority.
The overarching goal here is not to redescribe the explicandum, but to clarify it by means of a new concept that is both
more precise than, and substantially similar to, the explicandum.
8
1.3
Explication in Contemporary Formal Philosophy
Carnap’s method of explication has had an immense impact on contemporary philosophy. Many
philosophers today are explicit about the fact that they are applying the method of explication
to their respective projects. But even those who do not explicitly frame their projects in this way
often go about their work in a way that fits the mold. Moreover, philosophers today employ
both Carnapian explication (for concept engineering) and Oppenheimian explication (for concept
clarification).
We have seen that Carnap intended explication to be used in the service of the empirical
and mathematical sciences; explication gives us the method by which we engineer new concepts
useful to these fields. Perhaps unsurprisingly then, the most obvious examples of Carnapian
explication come from the areas of philosophy that have the empirical and mathematical sciences
as their subject matter. To focus on one such area, in the philosophy of biology, explications
of biological concepts like Species (Kitcher, 1984; Ereshefsky, 1992), Gene (Kitcher, 1982; Waters,
1994), Organism (Okasha, 2011; Haber, 2013), Population (Millstein, 2009; Stegenga, Forthcoming),
and Fitness (Mills and Beatty, 1979; Sober, 2001) all have as their goal the engineering of new
concepts that would yield a more fruitful biological theory. Thus, echoing Carnap, Kitcher (2008,
p. 119) writes,
There’s no higher standard to which our concepts are to answer than the efficient
satisfaction of the purposes of inquiry [...] The task of projects in philosophy of biology
that focus on concepts like Gene and Species is, then, to provide exact reconstructions
of notions that are useful for the current purposes of inquiry.
A recent, specific example of Carnapian explication in philosophy of biology is provided by
Haber (2013, p. 212). The concept of Organism, Haber argues, can be replaced by the more exact
Lineage-Generating Individual, a concept which is far better suited for doing biology:
[The concept O]rganism is not simply not doing any work, but instead is obfuscating
matters. Rather than worrying about whether a particular grouping, be it of cells,
multicellular individuals, or cellular parts, constitutes an organism or not, the goal is
instead to focus on individuals and features of those individuals. In place of asking
whether an individual is an organism, we instead ask whether that individual is a
lineage-generating individual.
Ereshefsky (1992, p. 677) similarly argues that we are in a better position “to understand how
evolution has occurred on this planet” if we replace the ambiguous concept Species, which has
9
“outlived its usefulness,” with more exact theoretical-biological concepts that are proving more
fruitful in particular areas of biology – concepts like Phylospecies, Ecospecies, and Biospecies.
Similar examples are easy to find in other philosophies of the special sciences. However, if
one looks outside of these areas, things change. Here, philosophers are arguably not interested in
discarding concepts for more fruitful alternatives so much as they are interested in gaining clarity
and exactness about the original concepts. That is, the majority of explications in these areas of
philosophy are Oppenheimian explications. Formal philosophers devote themselves to the explication and clarification of a variety of philosophically rich concepts. To focus again on one area of
philosophy, some recent examples from the general philosophy of science include explications of
Probability (Maher, 2010), Causation (Woodward, 2003; Halpern and Pearl, 2005), Causal Strength
(Fitelson and Hitchcock, 2011), Confirmation (Milne, 1996; Eells and Fitelson, 2002; Crupi et al.,
2007), Coherence (Shogenji, 1999; Bovens and Hartmann, 2003; Schupbach, 2011b), Explanatory
Power (McGrew, 2003; Schupbach and Sprenger, 2011), and many others.
Of course, philosophers putting forward these explications rarely specify that they are aiming for concept clarification as opposed to concept engineering. But their practice betrays their
un-Carnapian intentions. For example, formal philosophers often construct their explicata by first
compiling “criteria of adequacy” for any explicatum. Almost without exception, such criteria express judgments about the exlicandum that we find natural or obvious as opposed to specifying
any desired, fruitful features of the explicatum (Good, 1960; Milne, 1996; Eells and Fitelson, 2002;
Douven and Meijs, 2007; Schupbach and Sprenger, 2011). Such philosophers thus require from the
start that any satisfactory explicatum must agree with (and thereby resemble) the explicandum
in various ways. By contrast, what one does not see very often is an emphasis on constructing
an explicatum in such a way that fruitfulness is ensured from the start. This observation makes
sense if these philosophers are pursuing Oppenheimian explication, but not if they are pursuing
Carnapian explication.
Another example of how common practice betrays non-engineering motivations can be found
by examining a typical pattern of dialectic in formal philosophy. Often, after a new explication
of some target concept is proposed, criticisms by way of counterexamples start flooding in.8 The
point of these counterexamples is to show that the proposed explicatum does not have various
properties that we naturally associate with the explicandum; in other words, such criticisms point
to dissimilarities between the explicatum and explicandum. These mismatches receive great attention and indeed are often treated as sufficient cause for rejecting an explicatum. This is just
8 Examples
abound. Here, as one family of examples, I cite some cases from the ongoing debate over measures of
incremental confirmation: Milne 1996; Christensen 1999; Eells and Fitelson 2002; Fitelson 2006; Crupi et al. 2007.
10
the sort of dialectic that one would expect if an explication is meant to clarify the explicandum.
It makes little sense to argue in this way, however, if an explication is being put forward for engineering purposes (in which case, the success of one’s explication ultimately hinges on fruitfulness
rather than similarity).
One may also argue that formal philosophers are often in the business of Oppenheimian explication by noting the sorts of conclusions such philosophers are apt to draw post-explication. These
conclusions are expressed using the original target concept. Using a probabilistic explication of
Coherence, the formal philosopher might for example argue for or against the idea that Coherence
is truth-conducive. The idea is that we learn something about our original concept by investigating
features of the precise, corresponding explicatum. This move is only convincing to the extent that
the explicatum retains a resemblance to the explicandum. But this will be true far more often of
Oppenheimian explications than Carnapian explications. The fact that a philosopher draws this
sort of conclusion post-explication then is symptomatic of that explication being used for concept
clarification. More generally, in concept engineering, unless an explicatum (in addition to being
fruitful) is shown to be similar to the explicandum, the focus post-explication will remain on the
explicatum.
2 The Strawsonian Challenge
“But ‘glory’ doesn’t mean ‘a nice knock-down argument’,” Alice objected.
“When I use a word,” Humpty Dumpty said, in rather a scornful tone, “it
means just what I choose it to mean – neither more nor less.”
“The question is,” said Alice, “whether you can make words mean so
many different things.”
“The question is,” said Humpty Dumpty, “which is to be master – that’s
all.”
Alice was too much puzzled to say anything.
Lewis Carroll (Through the Looking Glass)
Carnap, of course, sided with Humpty Dumpty.
Richard C. Jeffrey (“Carnap’s Empiricism”)
Clearly Carnap’s method of explication has a sizable following today. Indeed, explication is so
firmly placed into the toolbox of today’s formal philosopher, that its use seems to come second
nature to most of its practitioners. The great majority of philosophers who apply this method
11
show no awareness (in print at least) that explication might stand in need of defense. But this
method is not without its detractors. In philosophy, where every position has its naysayers, this
is the run-of-the-mill. Yet, what may come as a surprise is that the most penetrating objection
put to the method of explication (when it is properly aimed) has not been convincingly answered,
despite the fact that it has been lurking about since as early as 1963.
P. F. Strawson presents this objection in his contribution to the volume of The Library of Living
Philosophers devoted to Carnap (Strawson, 1963, pp. 504-505):
However much or little [Carnap’s method of explication] is the right means of getting
an idea into shape for use in the formal or empirical sciences, it seems prima facie
evident that to offer formal [explications] of key terms of scientific theories to one who
seeks philosophical illumination of essential concepts of non-scientific discourse, is to
do something utterly irrelevant – is a sheer misunderstanding, like offering a text-book
on physiology to someone who says (with a sigh) that he wished he understood the
workings of the human heart.
Stripped of rhetorical flourish, Strawson’s point is the following: concepts of everyday discourse
have their home (their applications, development, etc.) outside of the natural or mathematical
sciences. The more exact concepts of science have their home in the sciences – and thus outside
of everyday discourse. When we follow Carnap’s advice and introduce a precise version of an
otherwise imprecise concept, we are attempting to illuminate concepts in the former group by
replacing them with concepts in the latter group. However, while the same term may express
concepts in both scientific and non-scientific discourse (e.g., “heart”), these respective concepts
will differ from one another in substantial ways. If we focus our attention on the logical or
scientific explicatum then, we inevitably distance ourselves from the explicandum. Strawson’s
criticism, in sum, has to do with explication’s similarity desideratum. Strawson maintains that
a logically or scientifically precise explicatum can never illuminate an imprecise explicandum
because they are too dissimilar.
The unhappy consequence is that formal philosophers are manufacturing their own concepts,
which have the advantage of being communicable with formal rigor, but which also have the
great disadvantage of not being relevant to any of the concepts humans employ outside of formal
philosophy, mathematics, or science. Drawing upon the above epigraph, Strawson’s point is that
formal philosophers, like Humpty Dumpty, are creating their own language with no apparent
relevance outside of their own discourse. In this case, just as Alice was dumbfounded by Humpty
Dumpty’s antics, so should philosophers be dumbfounded by the self-isolating procedures of
formal philosophy. The Strawsonian challenge put to formalists then is for them to defend their
12
explications as relevant to the study of concepts that are not mathematically precise; to do this,
they must establish that any particular explication of interest can, and indeed does, satisfy the
similarity desideratum.
The first thing to note about Strawson’s criticism is that, when put to Carnap, it is not particularly well-aimed. This criticism only poses a challenge to those who think that explicata, in order
to be satisfactory, must illuminate explicanda. In light of the distinction we made above between
Carnapian and Oppenheimian explication, one might say that the Strawsonian challenge is only
worth taking up for those who pursue Oppenheimian explication. As we have seen, however,
Carnap is a concept engineer. He sides with Humpty Dumpty, as it were, and has no problem
with manufacturing explicata with little connection to explicanda, so long as the explicata are
fruitful; as with Humpty Dumpty, so with Carnap, we are to be the masters of our concepts, not
the other way around. From Carnap’s perspective then, the Strawsonian challenge is mostly just
misguided. Accordingly, in response to Strawson, Carnap effectively just reaffirms his engineering perspective, this time via a simple but helpful analogy with less philosophical, more mundane
tools (1963, pp. 938-939):
A natural language is like a crude, primitive pocketknife, very useful for a hundred different purposes. But for certain specific purposes, special tools are more efficient, e.g.,
chisels, cutting-machines, and finally the microtome. If we find that the pocketknife is
too crude for a given purpose and creates defective products, we shall try to discover
the cause of the failure, and then either use the knife more skillfully, or replace it for
this special purpose by a more suitable tool, or even invent a new one. [Strawson’s]
thesis is like saying that by using a special tool we evade the problem of the correct use
of the cruder tool. But would anyone criticize the bacteriologist for using a microtome,
and assert that he is evading the problem of correctly using a pocketknife?
Strawson mistakenly thinks that his criticism applies to Carnap then, because he fails to recognize that Carnap is doing concept engineering. However, if Strawson can be blamed for misdirecting his criticism at Carnap’s project, so too can Carnap be blamed for underestimating Strawson’s
objection. Carnap fails to recognize that there is another use for explication that is properly targeted by Strawson’s criticism. Because Carnap fails to recognize the explicative project of concept
clarification, he interprets Strawson’s criticism as a challenge to concept engineering; in the foregoing passage, he suggests that Strawson takes issue with the replacement of a less useful concept
for one that is more useful in engineering contexts, where we are purely interested in improving
the usefulness of our conceptual tools. But this ignores Strawson’s own framing of his challenge.
In his criticism of explication, Strawson voices no concerns with the conceptual engineering
13
project of “getting an idea into shape for use in the formal or empirical sciences”; his concerns
are rather with the explicator “who seeks philosophical illumination of essential concepts of nonscientific discourse” – i.e., with Oppenheimian explication. He challenges the formalist to show
just how an exact, formal-scientific concept could shed new light on the nature and implications
of some imprecise, everyday concept. The explicative contexts that Strawson has in mind are ones
in which we have philosophical questions about the everyday concepts themselves. When these
imprecise concepts are the very objects of our inquiry, Strawson’s criticism still has its force. Why,
after all, should we be allowed to replace the concept which is the object of our investigation
with another concept (one more fit for rigorous investigation) unless we have a case in hand that
establishes the close similarity of the two? The upshot is that Strawson’s challenge misfires when
directed at Carnapian explication, but it lands a powerful blow against Oppenheimian explications intended for conceptual clarification. Carnap gives no satisfying answer to the question that
lies at the heart of the Strawsonian challenge: just how can one establish the similarity of explicatum to explicandum that is necessary in cases where one intends for the former to illuminate the
latter?9
3 Experimental Explication
3.1
How to Make a Case for Similarity
In spite of the fact that formal philosophers since Carnap have often used explication for concept
clarification, they have not dealt head-on with the Strawsonian challenge.10 One can, however, investigate how such philosophers at least tacitly attempt to meet the Strawsonian challenge in their
practice. Far and away, formal philosophers most commonly attempt to establish that their explications satisfy the similarity desideratum by appealing to their own intuitive judgments, typically
pumped through thought experiments or historical case studies. For example, as mentioned in
Section 1.3, Kemeny and Oppenheim (1952), Good (1960), Milne (1996), Eells and Fitelson (2002),
Douven and Meijs (2007), and Schupbach and Sprenger (2011) are just a few of those who appeal
to allegedly intuitive “conditions of adequacy” pertaining to their explicandum in order to defend
9 The
idea that Strawson’s objection is best framed as an objection to explication qua concept clarification is also high-
lighted by Loomis and Juhl (2006) and by Justus (2012, p. 166).
10 Maher (2007) and Justus (2012) are two exceptions. Maher’s discussion is quite brief; he suggests that we can meet
Strawson’s challenge by, among other things, “understanding the explicandum well” and providing evidence to show that
explicata “correspond well to their explicanda.” This paper goes some way to filling in the necessary details of how one
might achieve these things. Justus’s response to Strawson is on behalf of the concept engineer. This paper alternatively
aims to respond on behalf of practitioners of Oppenheimian explication.
14
their explicata.
As a simple example of this strategy, consider attempts to clarify the Conditionality concept
that we typically express in natural language with “If..., then...” by explicating it using a truthfunctional connective in classical logic. To defend the material conditional → as illuminative of
Conditionality, one must make a case for the similarity of → to this concept. To this end, one
might first propose the following set of purportedly intuitive judgments pertaining to the latter,
target concept:
1. “If φ, then ψ” is false whenever φ is true, and ψ is false.
2. From “If φ, then ψ” and “ψ”, we cannot validly conclude that ψ.
3. “If φ, then φ” is necessarily true, regardless of whether φ is true or false.
Second, we may point out that none of the 16 binary, bivalent, truth-functional connectives other
than → satisfies all three of these intuitions. So long as one seeks an explication that replaces “If...,
then...” with such a formal connective then, this argument concludes, the material conditional is
a better fit than any other option. In general, nearly all formal philosophers implicitly defend
the similarities of their explications using this style of argument, comparing how well the various
candidate explicata line up with their intuitive judgments about the target concepts.
I do not want to suggest that these sorts of argument are useless when it comes to establishing
the similarity of an explication. Nonetheless, the following considerations tell against the overall
efficacy of this approach. First, these arguments at best provide comparative support for the
conclusion that one’s explication satisfies the similarity desideratum. It may be the case that some
proposed explicatum does a better job than any alternative when it comes to matching certain
intuitive judgments pertaining to the explicandum in question. It may even be possible to prove
that this explicatum is uniquely the best at matching such judgments. But neither of these facts
would directly establish that the explicatum is overall very similar to the explicandum. This is
because the most similar of the considered (or even possible) explicata might still be too dissimilar
to the explicandum. Many philosophers would, of course, want to point to the above example of
material implication as a case in point; far from demonstrating that → is sufficiently similar to the
explicandum, such logicians take this argument to show that no binary, bivalent, truth-functional
connective could be sufficiently similar to the concept typically expressed with “If..., then...” (and
thus, that this concept should not be explicated with a formal explicatum of this type). In more
extreme cases, it may turn out that the explicandum is not susceptible to formal explication at all
– e.g., perhaps the target concept is so internally incoherent that no logicomathematical concept
15
(not even the one that is proven to come uniquely closest to the explicandum) could shed light on
it.
Second, not only does a positive case of this sort only provide comparative support for the
similarity of one’s explication, but a negative result does not conclusively disconfirm any candidate explicatum. A negative result, in such a case, means that the explicatum and explicandum
decidedly do not share all of the same, corresponding properties (e.g., φ → ψ is true whenever
φ is false, but this is not generally the case for the everyday concept of Conditionality). This
sort of finding is exceedingly useful if we desire a conceptual analysis of our target concept. In
such a case, we require “complete coincidence” between analysans and analysandum, and one
counterexample is enough to establish that we do not have it. However, one “counterexample”
is not enough to dismantle a proposed explication. Recall that similarity, according to Carnap
(1950, p. 5), demands that “in most cases in which the explicandum has so far been used, the
explicatum can be used.” But this requirement can be satisfied by an explicatum that fails to
match the explicandum perfectly. Indeed, any satisfactory explicatum that fails to fit perfectly with
its corresponding explicandum will, on account of that fact, have attributes that clash with our
intuitive judgments about the latter.
An additional complication arises independent of the foregoing considerations. Even if an explicatum decidedly matches the relevant judgments very closely, there may remain good reasons
to doubt that it closely matches the explicandum of interest. There are a number of such reasons one
might have in any particular case. Consider cases where our target explicandum is commonly applied in everyday settings, by non-academics and academics alike – i.e., cases in which Strawson’s
challenge most obviously applies. When we test for similarity in such cases, we aim to compare our formal concept to a concept applied by non-philosophers in non-philosophical contexts
(again, the concept of Conditionality seems to be an obvious case in point). But, to get a handle on various features of the explicandum, the standard approach has us attend to the possibly
rather idiosyncratic judgments of philosophers. This is puzzling. Why should we see fit to study
philosophers’ judgments at this point? Philosophers are a unique bunch, and as recent studies
have shown (Livengood and Machery, 2007; Sytsma and Machery, 2010) philosophers’ judgments
can part significantly from those of the philosophically naïve in more ordinary circumstances. But
then, in these cases, it is not our (qua philosophers) intuitive judgments that we need to fit but
those more generally of people (philosophers and non-philosophers alike), as these judgments are
made in more mundane circumstances. These are the judgments that most forthrightly express
the everyday concept of interest.
These considerations suggest a more promising approach to testing explications for similarity;
16
accordingly, they suggest a better means of responding to Strawson. First, if we are to improve on
the above standard defense, we require a test of overall similarity. Unlike the standard approach,
such a test would not merely perform a comparative evaluation of explicata by assessing their
relative fits with (certain specified attributes of) the explicandum. Second, we require a means
for testing similarity that places a more careful focus on the explicandum by attending to the
groups that most often apply this concept and the circumstances in which they commonly use it.
Often, though certainly not always, the explicandum will be drawn from outside of philosophical
dialogue. In these cases, we will want our method to ensure that our formal concept connects
substantively to the concept employed by non-philosophers. In the remainder of this section, I
argue that both of these requirements are satisfied by incorporating experimental methods into
explication.
To get a sense of the overall fit between explicandum and explicatum, we desire a means of
directly comparing the two. This involves checking the extent to which properties of the explicandum also hold true of a candidate explicatum. But how should we determine the relevant
properties of the explicandum? Given that we have philosophical interests in this concept, we
ourselves must have some sense of its various attributes. However, unless we truly only care to
get more precise about the concept that we individually have in mind, there is no good principled
reason not to look to the judgments of others – in addition to our own – when attempting to
catalogue relevant features of the explicandum. Indeed, there is actually good reason to do this; if
we do not heed the judgments of others, we run the risk of focusing our explication on an explicandum concept that is peculiar to ourselves. To take an extreme but instructive example, imagine
how Humpty Dumpty might explicate the concept of Glory (recall that, by “glory,” he means “a
nice knock-down argument”); plausibly, he might introduce an explicatum that makes use of Carnap’s notion of L-Implication. However, while such an explicatum might shed light on Humpty
Dumpty’s peculiar concept (call it HD-Glory), it would hardly clarify the concept of Glory that
people standardly have in mind. To the extent that Humpty Dumpty would want to explicate the
latter concept, he would do well to investigate judgments that others make when expressing their
concept of Glory. In standard cases, when specifying an explicandum’s properties, we do well to
attend to the judgments of others, in addition to our own.
The relevant judgments that inform us of the explicandum’s attributes are thus things to be
observed out in the world. They are predominantly the judgments of others, to be surveyed and
recorded. Such empirical research provides us with crucial information for assessing more directly
just how well a particular explication does with regards to explication’s similarity desideratum.
By observing and surveying how particular groups of people apply the relevant term(s) in the
17
relevant context(s), we gain a clearer perspective on the underlying explicandum that drives their
behavior. And this information enables us not only to compare how similar various candidate
explicata are to the target concept, relative to one another, but it additionally gives us evidence of
how closely overall (in the contexts tested) any particular formal explicatum corresponds to the
explicandum.
So by relying on empirical research, such “experimental explication” gives us a more direct
means of testing for similarity.11 But it also gives us the desired ability to focus more accurately
on the explicandum of interest. We may, in principle, use it to survey and record the judgments of
any person or group of people – as opposed to relying solely upon our own intuitive judgments
(and occasionally those of other philosophers too). Generally speaking, according to experimental
explication, if we would like our account to shed light on a concept, then we first should clarify
which groups of people most often apply that concept, and in which contexts. We can then ensure
that we have an accurate perspective on the concept in question to the extent that we observe how
that concept affects the behavior and judgments of such people in such contexts. These, more so
than our own intuitions, are the judgments pertaining to the explicandum that we ought to rely
on when we test our explication for similarity.
Clearly, the nature of the experimenter’s task – specifically which groups of people and contexts to observe – will vary depending on the explicandum one aims to study. If one wants to
shed new light on some concept as it gets applied in everyday settings by philosophers and nonphilosophers alike, then one ought to examine the treatment of that concept by people in familiar
settings. If, alternatively, there is less concern with connecting one’s account with the everyday
use of a concept and more interest in shedding light on a specialized use in a specific field, then
it will be right to focus on the intuitions of the relevant specialists – and to ignore the intuitive
judgments of non-specialists. For the formal philosopher who desires to explicate a concept that
philosophers particularly use when doing philosophy, the “relevant intuitive judgments pertain11 Experimental
explication has, as predecessors, experimental approaches to exploring definitions, intensions, and con-
ceptual analyses. Already in 1938, Ness advocated the use of empirical “questionnaires” to compare candidate analyses
of truth with the concept applied by non-philosophers. Carnap (1955) himself promotes an “empirical procedure for
determining intensions.” Mates (1958) takes ordinary language philosophers to task for defending their claims “[...] as
having a factual basis and presumably as refutable by observation of the ordinary folk, magistrates, parents and teachers”
while not accordingly using experimental means of testing their claims. He proposes two experimental methods that both
contribute to “a concrete test for determining the ordinary sense of a given word.” In more recent years, with the rise
of experimental philosophy (particularly the positive program), defenses of so-called “experimental analysis” are multiplying. Two examples are (Nadelhoffer and Nahmias, 2007) and (Sytsma, 2010; cf., Sytsma and Livengood, Forthcoming,
section 2.1.6).
18
ing to the explicandum” will be limited to those in the philosophical community. In any such
case, experimental explication recommends focusing on the communities and contexts in which
the explicandum most typically makes its appearance. As such, experimental explication provides
the means to make the desired comparison between one’s explicatum and the appropriate, target
explicandum.
The most important virtue of experimental explication is that it provides the formal philosopher with a tool for evaluating just how similar one’s formal explicatum is to the otherwise imprecise explicandum of interest. By demanding a fit between explicatum and the observed, surveyed
attributes of the explicandum, this method safeguards the formal philosopher from manufacturing a concept with little or no connection to the target concept of ultimate interest. When
experimental explication is carried out successfully, the formalist’s logicomathematical account is
held accountable to judgments that standardly express the concept of interest in the contexts of
greatest application. Thus, following Strawson, critics may assert, “This formal concept cannot
possibly be sufficiently similar to the target concept, even if it is – in some sense – the most similar
of the formally exact candidate explicata.” But this criticism is dissolved to the extent that the
formal philosopher can adduce empirical results as evidence that the formal concept does align
with the target concept.12 In other words, bringing experimental methods to bear on explication
in this way provides the formal philosopher with a potential response to those who would press
the Strawsonian challenge.
More generally, to the extent that the explicator empirically establishes the relevant similarity
between explicatum and explicandum, the former may be used to illuminate characteristic features of the latter; i.e., we can learn new things about the explicandum by studying the formal
implications of the explicatum. Why think that the explicatum’s formal implications carry over
to the explicandum? Of course, they do not carry over analytically. Explication is not analysis,
and so the explicatum’s implications will not be guaranteed by definition to be true also of the
explicandum. Nonetheless, as Carnap notes, we establish similarity between concepts by showing
that they apply to the same cases. Consequently, if some result necessarily holds in cases where
an explicatum applies, it will also typically hold in cases where the corresponding, relevantly
similar explicandum applies. The degree to which we are licensed in so linking a formal result to
the explicandum will be determined by the extent to which we have established the extensional
similarity of the concepts. Notably, amongst other things, this sense of similarity can thus ground
formal defenses of informal judgments, arguments, and so on. If an informal explicandum is
12 On
the other hand, of course, this criticism is confirmed and strengthened to the extent that the experimental results
show that the explicatum departs from the explicandum.
19
shown to be strongly similar to a mathematically rigorous explicatum which implies some normatively appealing result, then we may point out that this appealing result will typically hold
in cases where we apply the explicandum. For example, in this way we might try to show that
non-probabilistic theoretical virtues have normatively appealing probabilistic upshot.
There is thus a valuable, perhaps crucial, role for experimentation to play in formal philosophy. It is important to note, however, that applying experimental methods to explication in this
way brings new complications as well. For one thing, experimental explication requires us to
develop scenarios in which we can compare theoretical results to human judgments. These scenarios must accordingly be both formally sophisticated enough to allow one to derive theoretical
results from the explicatum, and familiar enough to allow the relevant audience to have and communicate judgments expressing the explicandum. Moreover, at least when our explicandum is
extracted from everyday discourse, the more familiar these scenarios are, the better. After all, in
line with Carnap’s similarity desideratum, we are interested in testing how similar our explicatum
and explicandum will typically be; if they come apart in scenarios that are extremely uncommon
and gerrymandered, this need not worry the formal philosopher. But the desire for scenarios to
be familiar, again, needs to be considered alongside the demand that scenarios be loaded with
sufficient technical details for the explicatum to apply. These complications arise uniquely in
experimental explication on account of the formally precise nature of explicata. In addition, as
other philosophers have discussed in detail, general difficulties arise when it comes to investigating people’s conceptual schema by observing their language behavior.13 To say that such work is
tricky, however, is not to suggest that it is impracticable. Very recently, some philosophers and
psychologists have begun to apply just this sort of experimental work to the evaluation of explications (Crupi et al., 2007; Tentori et al., 2007; Harris and Hahn, 2009; Schupbach, 2011a; Douven
and Verbrugge, 2010, 2013).
3.2
Case Study: Experimental Explication and Explanatory Power
In order to clarify further the nature and advantages of experimental explication, this section
explores one example of this method at work. In recent research, Schupbach and Sprenger (2011)
put forward an Oppenheimian explication of Explanatory Power. They specifically seek, for their
explicatum, a probabilistic measure of the strength of a potential explanation. After introducing
13 Space
does not permit us to go into detail about such complications in this paper. Other philosophers who have
discussed these difficulties – when investigating the potential bearing of experiments on conceptual analyses (see footnote
11) – include Mates (1958, pp. 167-70), Nadelhoffer and Nahmias (2007), and Sytsma and Livengood (Forthcoming, part
II).
20
four “conditions of adequacy,” Schupbach and Sprenger prove that the only such explicatum that
satisfies these conditions is the following (along with any ordinally equivalent measure):
E (e, h) =
Pr (h|e) − Pr (h|¬e)
.
Pr (h|e) + Pr (h|¬e)
Excepting their first “Formal Structure” condition (which guarantees the desired precision of
the explicatum), Schupbach and Sprenger’s other three conditions are meant to ensure that the
explicatum they construct will be similar to the explicandum, by having formal analogs of various
attributes of the latter. So, for example, they start from the judgment (inspired by Peirce) that a
hypothesis has explanatory power over some evidence to the extent that it makes that evidence
less surprising (or more expected). Rephrasing this judgment in probabilistic language, they
require that hypothesis h has explanatory power over evidence e to the extent that it increases the
probability of the evidence – i.e., to the extent that Pr (e|h) > Pr (e). As a further defense of the
similarity of explicatum E to the less precise explicandum of Explanatory Power, Schupbach and
Sprenger prove four theorems, each purportedly showing that E fits well with intuitive judgments
expressing important attributes of Explanatory Power.
As with any logicomathematical explication of a concept applied outside of logicomathematical discourse, one could at this point press the Strawsonian challenge. With Strawson, the critic
might doubt that a formal concept could shed light on a concept applied outside of the formal
sciences. The worry, made particular to this explication, is that a probabilistic explicatum like E
just cannot be similar to an everyday concept like Explanatory Power, and so the former cannot
shed any new light on the latter. And the consequent challenge is for E ’s proponents to somehow
defend the claim that E and Explanatory Power do bear a significant resemblance to one another.
The standard means of dealing with this critic would be for Schupbach and Sprenger to continue in much the same way that they began: by proving more theorems revealing the implications
and properties of E and subsequently arguing, based on these theorems, that E matches intuitive
judgments of Explanatory Power more so than does any other such probabilistic explicatum.
However, we have seen the potential downfalls of such a strategy. In response, the critic may
insist that while E may provide a better fit with Explanatory Power than all of its probabilistic,
rival explicata, still no one of these can hope to provide a good overall fit with the explicandum.
In addition, the critic might point out that the judgments expressing Explanatory Power used
here to gauge similarity may not actually be representative of the explicandum of interest. The
judgments discussed here might seem natural to Schupbach and Sprenger, but that hardly shows
that these judgments reflect clear properties of the explicandum of interest, the one applied by
non-philosophers outside of philosophical debate.
21
For these reasons, Schupbach (2011a) takes a different tack. He performs a study, surveying
non-philosophers’ judgments pertaining to explanatory power, and then uses these judgments to
estimate more accurately the overall similarity of E to Explanatory Power in the experimental
context.14 In more detail (though readers should refer to the original article for a full description
of the experiment), Schupbach makes use of a ball-and-urn, chance setup. Participants were
shown two urns and told the respective contents of the urns (urn A contained 30 black balls and
10 white, urn B contained 15 black and 25 white balls). After seeing that one of these two urns
was randomly chosen (but not knowing which) balls were drawn without replacement from the
chosen urn. Two simple hypotheses were considered as potential explanations for the results of
the draws, h A : “balls are being drawn from urn A” and h B : “balls are being drawn from urn
B,” After each draw, participants wrote down their explanatory judgments with regards to how
well each of the two hypotheses explained the results thus far – we denote any such judgment
J (e, h A/B ). Schupbach then compares these judgments to corresponding theoretical results derived
from a set of particular candidate measures of explanatory power, including E . These results were
calculated both using subjective probabilities collected from the participants and using objective
probabilities implicit in the chance setup.
In order to test which of the candidate, probabilistic explicata is most similar to Explanatory Power, Schupbach analyzes the experimental results in two ways: (1) For each measure, the
Euclidean distance between participant judgments and derived, theoretical results is calculated;
(2) Each measure’s residual distribution (i.e., the distribution of values of J (e, h A/B ) − E(e, h A/B )
corresponding to any measure E) is examined and compared. On the basis of these analyses,
Schupbach argues that the measure of explanatory power E provides the best fit with Explanatory
Power of all candidate measures. That is, results derived from E sit closer, on average, to participant judgments of explanatory power, and the mean residual corresponding to E is closer to the
ideal value of zero than that corresponding to any other measure.
This use of experiments allows Schupbach to go one very important step further however.
Not only do these analyses suggest that E bears a greater similarity to relevant judgments of
explanatory power than any other proposed probabilistic explicatum, but the second analysis
in particular additionally shows that E (and only E ) has a mean residual that does not differ
significantly from the ideal value of zero. In other words, this experiment provides evidence
regarding E ’s overall, direct fit with Explanatory Power as opposed merely to providing evidence
of how well E does compared to other proposed explicata. Figure 1 is one of two graphs displayed
14 The
design of Schupbach’s experiments is based closely on a chance setup previously applied by Phillips and Edwards
(1966) and more recently by Tentori et al. (2007).
22
Figure 1. Participant judgments about h A (black) plotted with values derived from E using subjective probabilities (dark gray) and objective probabilities (light gray).
in Schupbach’s paper representing the fit between E and participant judgments.
This is one experiment, testing similarity in one context using one experimental design. Thus,
the proper conclusion to draw from Schupbach’s study is not that Strawson’s challenge has been
met – not that the similarity between E and Explanatory Power has been sufficiently and generally
established. Further experiments, set up in diverse ways and run under diverse conditions, are
called for before such a conclusion might confidently be drawn. This further experimentation
might also clarify conditions under which E is and is not similar to Explanatory Power – i.e., such
empirical study could distinguish contexts in which E does and does not illuminate the concept
of Explanatory Power.
Still, even if this application of experimental explication does not fully invalidate Strawson’s
criticism, it does go some way to shifting the burden of proof back onto the critic. Strawson’s
challenge is for the explicator to offer up some reason to believe that a formal concept like E is
able to maintain a resemblance to an informal concept like Explanatory Power. The results of this
experiment constitute evidence of this resemblance, even if they do not by themselves establish
it. At this point, if the critic wants to maintain that such similarity is absurd – “like offering a
text-book on physiology to someone who says (with a sigh) that he wished he understood the
workings of the human heart” – he or she will have to say something about why we ought not
trust the results of this experiment.
23
4 A More Defensible Positive Experimental Philosophy
Experimental explication thus has much to offer the formal philosopher. Strawson’s criticism
poses a challenging question to any Oppenheimian explication: Why believe that this logicomathematical explicatum bears a significant enough resemblance to the inexact explicandum used in
everyday discourse? To the extent that well-devised experiments reveal that the formal concept
shares the same properties as the inexact concept, we have evidence to adduce in response to this
question. In this final section, I argue that experimental explication also has much to offer the
experimental philosopher.
In the opening paragraph of this paper, I mentioned the distinction between experimental
philosophy’s negative and positive programs. According to the negative program, experimental
studies raise new skeptical worries for contemporary analytic philosophy, often by raising new
skeptical worries about the intuitive judgments upon which philosophers rely. According to the
positive program, empirical methods constitute a tool to be employed in addition to those of
contemporary analytic philosophy and in the pursuit of answers to philosophical questions. By
now, it should be clear that if experimental explication fits into either of these two programs,
it is an instance of positive experimental philosophy; experimental explication assigns empirical
studies an important role in the construction and evaluation of Oppenheimian explications. Yet,
experimental explication also differs in important ways from other species of positive experimental
philosophy. In fact, I will argue here that the differences are such that the standard lines of
objection put to instances of the positive program, even if otherwise convincing, are unpersuasive
when aimed at experimental explication. This then is the appeal of experimental explication
for experimental philosophers: it constitutes a heretofore unnoticed, more defensible brand of
positive experimental philosophy.
4.1
On the Reliability of Intuitions
Perhaps the most worrying objection put to experimental philosophy’s positive program comes
from its negative counterpart. (As a general challenge to the reliability of philosophically pertinent intuitive judgments, it applies just as well to more traditional philosophical methodology.)
Aimed specifically at experimental explication, the objection goes as follows: Experimental explication instructs us to look to people’s intuitive judgments about some explicandum in order
to gain the desired evidence pertaining to the nature of that concept. This method thus clearly
assigns a positive, evidential role to intuitions. However, an increasing number of recent studies
reveal that philosophically pertinent intuitive judgments are unreliable. The studies in question
24
arguably show that non-alethic factors (factors like age, gender, ethnicity, and socioeconomic status) determine, to a troubling extent, the intuitive judgments that humans make with regards
to philosophical thought experiments (Weinberg et al., 2001; Nichols et al., 2003; Machery et al.,
2004; Nichols and Knobe, 2007; Swain et al., 2008; Mallon et al., 2009). Insofar as reliability has to
do with the connection to truth (and not to any of these non-alethic factors), these results seem
to challenge the reliability of such intuitions. Thus, these intuitions make for poor evidence in
support of philosophical views.15
In order to defend experimental explication’s use of intuitions against such skeptics, it is helpful first to step back and ask what is meant by the claim that intuitions are not reliable.16 The
concept of Reliability is relative and normative. Some thing cannot be reliable full stop; it can only
be reliable relative to some specified norm. A reliable tool is one that actually tends to function in
the way that it is designed to function, a reliable friend is one who tends to behave in the way that
good friends ought to behave, a reliable witness is one who tends to tell the truth about what he
or she witnessed, etc. So what does it mean for an intuitive judgment to be reliable or not? We can
distinguish two important senses in which one might claim that intuitions are reliable, depending
on the norms that one has in mind.
The first and most obvious sense holds up truth as the normative standard; intuitive judgments
are reliable to the extent that they tend to be true. One might, for example, claim that a person has
very reliable mathematical intuitions and mean by this that the off-the-cuff judgments that person
makes about whether or not certain mathematical expressions are true or not tend to be correct.
Or a detective might be said to have reliable sleuthing intuitions if his or her first suspicions,
before considering all of the evidence of a case, tend to be correct in the end. Turning back to
15 The
skeptical worries of the negative program largely have their contemporary roots in Stich’s work throughout the
last few decades. Stich (1988) argues against intuition’s philosophical merits from what he calls the “problem of cognitive
diversity”. See also Stich’s exchange with Sosa (Sosa, 2009; Stich, 2009). Another foundational work grounding these
skeptical worries is (Hintikka, 1999).
16 By “intuitions,” I roughly have in mind the sorts of off-the-cuff judgments that people often put forward, typically
without attempting to defend them, and often in response to prompting via a case and question. This includes the
judgments offered by Schupbach’s (2011a) experimental participants, and also paradigmatic philosophers’ intuitions (like
“Despite the reliability and truth of his beliefs about the temperature, Mr. Truetemp fails to have knowledge of the
temperature”). It should go without saying that I am not attempting anything like a standard definition – or, for that
matter, an explication – of Intuition here. And I do not mean here to be taking any position at all on the important debate
over the nature of intuitions (on this topic, see for example Jenkins 2014). If one wants to interpret the above description
as a definition, then it should be thought of as stipulative. The move I am making here in avoiding this issue is akin to one
also made recently by Hitchcock (2012, pp. 206-207): “My main concern is whether the judgments of naïve subjects about
[paradigmatic philosophical cases] carry evidential weight, or whether the judgments of philosophers are privileged. It
will be helpful to have a simple term ‘intuition’ with which to describe these kinds of judgments.”
25
philosophy, to say that philosophically relevant intuitions are reliable in this sense is to claim that
they provide strong evidence of the truth of philosophically relevant matters. In this case, the
intuition that the length of a flagpole’s shadow (coupled with the angle of elevation of the sun) is
not able to explain the height of that same flagpole reliably indicates that the former truly is not an
explanation of the latter – and this, in turn, reveals that Hempel’s Deductive-Nomological account
of explanation is wrong. The intuition that Truetemp fails to have knowledge of the temperature
provides strong evidence that someone with reliably true beliefs could still fail to have knowledge
– and this, in turn, demonstrates that a simple version of process reliabilism fails. Let us refer to
Reliability meant in this first sense as “truth-tracking reliability”, or “t-reliability” for short.
Note, however, that there are some judgments that are arguably not evaluable with regards
to t-reliability. These are judgments for which there is no truth of the matter to track. Aesthetic
judgments seem to provide fertile ground for examples here. Recently, my daughter and I visited
the zoo, where we discovered that we had greatly differing opinions regarding the “cuteness”
of two red-tailed monkeys. My clear judgment was that the monkeys were very cute (my exact
expression: “I think these are the cutest animals in the zoo!”), but my daughter, without hesitation,
conveyed the judgment that the monkeys were repulsive (her exact expression: “Yuck!”). Of
course, it is doubtful that there is some objective truth of this matter precluding my daughter and
I from both being right. But if the requisite truths are not there in cases like this, then we cannot
sensibly ask whether judgments regarding these topics are t-reliable.
Still, we can discuss whether even these sorts of judgments are reliable in a second sense.
Instead of measuring how reliably judgments track truth, we might measure how reliably they
express the speaker’s meanings and concepts; judgments are reliable in this sense to the extent
that they accurately represent the concepts of the speaker. For example, the reliability of my
daughter’s judgments pertaining to the cuteness of various animals might be measured, not by
how often they get the facts right, but by how accurately they illuminate what she means by an
animal being cute. We can refer to Reliability meant in this second sense as “concept-tracking
reliability”, or “c-reliability” for short. With regards to the philosophical examples referred to
above, one may have reason to doubt that intuitions in the flagpole case reliably track truths about
explanation. Nonetheless, these intuitions might still plausibly be c-reliable so long as they are
accurate indicators of various aspects of what people mean by “explanation.” Similarly, even if
one doubts the t-reliability of intuitions about Truetemp, these intuitions might c-reliably inform
us of the concept(s) that people often express with the word “knowledge.”
C-reliability certainly looks to be a far easier requirement to satisfy than t-reliability. Nonetheless, it is easy to think of situations in which judgments would not be reliable even in this weaker
26
sense. Back to the zoo: perhaps my daughter has secretly and playfully decided that she wants me
to think she believes silly things (“Doesn’t that alligator looks cuddly!”, “Oh, isn’t that elephant
tiny!”), perhaps she is irritated with me and just wants to disagree with any of the things I say, or
perhaps she has secretly decided that it is “opposite day”! In any such case, we can expect that the
judgments she puts forward will not be c-reliable. They will not accurately express the various
concepts that she uses when making judgments about zoo animals; they will not be appropriately
concept-tracking.
The distinction between t-reliability and c-reliability is important for the following reason:
while it is the t-reliability of philosophical intuitions that negative experimental philosophy most
obviously calls into question, it is their c-reliability that experimental explication exploits. Let
us consider the first of these claims with an example in mind: Drawing upon the prior work of
psychologist Richard Nisbett (Nisbett et al., 2001, see also Nisbett 2003), Weinberg et al. (2001,
p. 23) discuss differences in “reasoning and belief-forming strategies” between East Asians and
Westerners. On the one hand, Western thought, in brief, is characterized by an analytic tendency to
separate objects of study from their context and to think more “individualistically”. On the other
hand, East Asians attend to the larger, holistic context of the objects of study, while thinking more
in terms of a “large and complex social organism where behavioral prescriptions must be followed
and role obligations adhered to scrupulously.” Based on these cultural differences, Weinberg et
al. put forward the plausible hypothesis that the intuitive judgments that Westerners make when
presented with cases involving “knowledge” part significantly from those that East Asians make.
Several survey-based experiments that they run support this hypothesis; Western participants and
East Asian participants do respond differently to such cases. For example, in a standard Gettier
case, “a large majority of Westerners give the standard answer in the philosophical literature [i.e.,
that the subject merely has a belief, not knowledge]. But among East Asians this pattern is actually
reversed” (p. 30).
The important thing to realize for present purposes is that results like these are only worrying
if one brings certain, questionable commitments to the table. For example, these results seem to
spell trouble for anyone committed to the idea that the intuitive judgments given by these experimental participants are reliable indicators of the truth about knowledge. This is just to say that
these results call into question the t-reliability of participant judgments; instead of tracking truth
reliably, participant judgments are confounded by non-alethic factors like cultural upbringing.
One might think that these results also call into question the c-reliability of such judgments;
instead of tracking the concept Knowledge reliably, participant judgments are confounded by
other factors. However, this only follows assuming (1) that a single Knowledge concept is shared
27
between Westerners and East Asians, and (2) that this is the concept that the experimental probes
are bringing to participants’ minds, to the same extent regardless of culture. And, in light of the
same body of psychological research (Nisbett et al., 2001; Nisbett, 2003), both of these assumptions
seem very implausible. Instead, it seems that East Asians and Westerners think, to some extent,
through distinct conceptual frameworks. When faced with identical questions having to do with
“knowledge”, East Asians and Westerners likely call distinct (perhaps subtly distinct) concepts to
mind. Such occurrences – what Austin (1957, p. 9) refers to as “snags of loose usage” – would
explain the significant difference between the judgments that the two groups make. And it would
do so without calling into question the c-reliability of participant judgments.17 Interestingly, these
results might even go some way to supporting the c-reliability of these intuitions. The fact (if it
is a fact) that intuitions vary across cultures but are stable within cultures is explained well by
the idea that such judgments are reliably tracking concepts, which in turn vary across cultures.
In other words, intuitions may well vary with culture (or socioeconomic status, etc.), but that is
because conceptual schema vary with culture (or socioeconomic status, etc.).18
Thus, while these experiments may call into question the t-reliability of philosophical intuitions, they do not call into question their c-reliability. But it’s c-reliability, not t-reliability, that is
crucial for experimental explication. Recall that the point of introducing an experimental variation
on explication is to provide us with a more accurate handle on the explicandum concept and to
provide us with a more powerful, direct test of similarity. What is crucial then is that our surveys
of people’s intuitive judgments are reliably giving us an accurate portrayal of their concepts, not
(thank goodness!) that these intuitions are shedding new light on the truth of the philosophical
matter. To put this tersely in the form of a slogan: the important thing is not whether participants
are speaking the truth, but whether they are speaking their minds.
Even if one thinks that the skeptical arguments put forward by experimental philosophy’s
negative program are persuasive when put to the typical instances of positive experimental phi17 Frank
Jackson (2011, p. 476) suggests a similar point when he writes, “The results of impeccably carried out surveys
into which cases [respondents] classify as cases of knowledge are highly relevant to what their concept of Knowledge is.”
18 This line of thought will not explain putative ordering effects in survey responses (e.g., Swain et al. 2008; Schwitzgebel
and Cushman 2012; Feltz and Cokely 2012). However, I think that that is as it should be. This sort of variation is, I
believe, of a different sort; it is symptomatic of poor survey design as opposed to being reflective of interesting conceptual
or cultural differences. In many cases, I side with Kauppinen (2007) who suggests that this variation is often due to
“competence failures, performance failures, and the potential influence of pragmatic factors.” More importantly, however,
Horne and Livengood (Unpublished) provide the decisive critique of these results, showing that the experimental evidence
currently on offer in experimental philosophy actually only “establishes that people are sensitive to evidence effects but
not that they are sensitive to genuine ordering effects.” This is no problem given that “evidence effects” – as described by
Horne and Livengood – merely reflect an appropriate sensitivity to different sets of evidence.
28
losophy (and when put to more traditional philosophical methods), they are misdirected if aimed
at experimental explication. With regards to this objection then, experimental explication constitutes a more defensible brand of positive experimental philosophy.
4.2
A “Properly Circumscribed Skepticism”
This section considers another case, put forward by Machery (2011, pp. 201-206), for skepticism
about the reliability of philosophical intuitions. Unlike the case for skepticism put forward in
negative experimental philosophy, this one potentially leads us to doubt the c-reliability, along
with the t-reliability, of philosophical intuitions. Nonetheless, I will argue that the relevant considerations here in fact support the c-reliability of those intuitive judgments used in experimental
explication.
Machery’s argument specifically targets philosophical intuitions – i.e., the intuitive judgments
that philosophers often rely on when arguing for or against some position. The central points
of his account are as follows. The psychological capacities that underlie our intuitive judgments
have, like any capacity, a “proper domain” in which they are reliable. One will have reason to
doubt the reliability of intuitive judgments then to the extent that they are made in and about
situations that part from those in this domain (assuming that “we have no further information
about their reliability in these circumstances”). The proper domain for intuitive judgments is
plausibly constituted by scenarios involving “everyday circumstances”. But “there are reasons to
suspect that in many philosophical thought experiments the situations described are beyond [this
domain].” Machery (2011, pp. 202-203) enumerates some of these reasons as follows:
Thought experiments in philosophy typically describe fanciful situations that are very
remote from the situations that elicit everyday judgments, and thus we cannot rely on
our memories of tried and true past judgments in everyday situations. Situations are
also often described in vivid terms [...], and their description contains numerous irrelevant narrative elements, features that are known to bias judgments. Most important,
thought experiments typically pull apart the features that go together in everyday life:
for instance, using physical violence and doing more harm than good are pulled apart
in the footbridge case.
Consequently, because they describe situations that stray far from ordinary circumstances, philosophical thought experiments elicit dubious intuitive judgments; “in such circumstances, people’s
judgments tend to be less reliable because [...] the eliciting situations are less typical.” The result is a “properly circumscribed skepticism” that gives us special reason to doubt those intuitive
29
judgments used by philosophers while simultaneously giving us reason to trust the intuitive judgments we make in the course of our everyday lives.
Machery phrases his case for this circumscribed skepticism about intuitions specifically in
terms of t-reliability – he writes about reliability with regards to the “truth of judgments.” But
these considerations also seem to provide good reason to doubt the c-reliability of our intuitive
judgments made outside of their proper domain. Our concepts are naturally suited for the contexts in which they are most often used. When we step outside of ordinary contexts, we thereby
step into circumstances in which we are not well-practiced at applying our concepts. In this unfamiliar territory, whether and how the concept of interest applies may be frustratingly unclear. But
then, to the extent that our concept just does not have a clear application, our forced judgments
will not be able accurately to convey what we mean by various term(s). Our judgments instead
will convey how we think the concept of interest ought to be extended and applied to the case at
hand, or perhaps what we think our interrogator is after, etc. In other words, we have reason to
doubt the c-reliability of our intuitive judgments to the extent that they are made in and about
situations that fall outside of their proper domain.
Machery’s account clearly does point to a salient difference between everyday judgments and
the intuitions to which philosophers typically appeal when constructing and criticizing theories.
The scenarios traditionally imagined by philosophers are of a variety that people simply do not
encounter in real life.19 For the purposes of this paper then, the question is whether this circumscribed form of skepticism (about the t-reliability and c-reliability of philosophical intuitions)
poses a challenge to experimental explication.
I have already gestured above (see the end of Section 3.1) at the answer to this question. The
point of Carnap’s similarity desideratum is to require that our explicatum typically corresponds in
a substantive way to the explicandum – i.e., to show that the the theoretical results derived from
the explicatum track features of the explicandum “in most cases.” Naturally then, when seeking
empirically to establish the similarity of our explication, we will want to compare our explicatum
to the sorts of intuitive judgments that people typically make pertaining to the explicandum. An
explicatum that fails to align with the intuitions we have that are sensitive to us living in the land
of barn façades will not be faulted nearly as much as one that fails in the mundane contexts of
everyday life. The intuitive judgments of interest for experimental explication are by-and-large the
ordinary judgments of everyday life. As far as experimental explication is concerned, the more
19 “Just
think of the Gödel case and Twin Earth in the philosophy of language, Mary the neuroscientist and zombies in
the philosophy of mind, Gettier cases in epistemology, and trolley cases or the Society of Music Lovers in ethics” (Machery,
2011, p. 191).
30
commonplace the intuitions, the better.
Consequently, if Machery is right that the “proper domain” in which intuitive judgments are
more reliable (t-reliable or c-reliable) is constituted by ordinary, everyday circumstances, then this
actually gives us good reason to think that the intuitions sought by experimental explication are
so reliable. Given Machery’s way of circumscribing his skepticism, the intuitions appealed to in
experimental explication fall on the trustworthy side of the line. Accordingly, we may additionally
conclude that the line between trustworthy and dubious intuitions does not coincide with the
line that demarcates philosophically interesting intuitions. Experimental explication clarifies a
philosophically important use for the ordinary intuitions of various groups of people.
4.3
The “Folk” and Philosophical Expertise
We can deal more quickly with two other objections, both of which are commonly put directly to
positive experimental philosophy. The first goes as follows: As an important part of their trade,
many philosophers investigate things like knowledge, causation, reference, free will, and morality;
they strive to illuminate the nature of these things. Consequently, they aim for a normative account
of concepts like Knowledge, Causation, and so on. The goal is to calibrate our concept, e.g., of
Knowledge so that it aligns with knowledge itself, and thereby to reveal how we ought to think
of these things. But, in order to grasp the true nature of such things, it seems like a waste of
time to go and ask philosophically naïve subjects (the “folk”) for their opinions and intuitions.
Philosophers seek to fine-tune our concepts; they do not seek to describe the concepts used by
non-philosophers. A descriptively adequate account of what the folk think may be of use to
psychology, but not to philosophy. Deutsch (2009, pp. 458-459), for example, presents this line of
criticism as follows:
[There is very little] reason to think that philosophers either typically do or must accept
that, if their pet theory is not best supported by the intuitions of competent speakers,
then that theory is false or in serious jeopardy, evidentially speaking. My guess is
that very few philosophers conceive of the truth or evidential basis of their views
as determined by the intuitive judgments of competent speakers. Why should they?
Competence in a language does not buy one insight into the nature of reference, knowledge, moral responsibility, intentional action, or any of the other traditional topics of
philosophy.
When aimed at experimental explication, this objection misfires. It assumes that, when we ask
non-philosophers for their judgments expressing a philosophically interesting concept, we expect
31
their responses to lend us philosophical insight and/or answers to our own philosophical questions. Whether or not this is true of some work done within experimental philosophy’s positive
program, it is not so with experimental explication. In experimental explication, it is not that we
pay special attention to what non-philosophers think about our philosophical questions; people
with no philosophical training, after all, tend to be poor philosophers! At the same time, however,
we as philosophers have a host of important and venerable philosophical questions that involve
concepts employed by non-philosophers and philosophers alike; we want, for example, to investigate the nature of justification, not in some uniquely philosophical sense, but justification as
referred to by philosophers, lawyers, scientists, and non-specialists alike. “The concepts of Cause,
Evidence, Knowledge, Mistake, Ought, Can, etc.,” Ryle (1953, pp. 170-171) emphasizes, ”are not
the perquisites of any particular groups of people.”20 When we ask people for their judgments
expressing concepts of interest, we are taking an important step toward ensuring that the explicatum that we proceed to examine – with all of our philosophical expertise – connects to the proper
object of study, as referred to by philosophers and non-philosophers. In experimental explication,
we are not interested in what non-philosophers think about our philosophical questions; rather,
we are interested in philosophical questions involving concepts via which non-philosophers think.
The above considerations also form the basis of a response to the related “expertise objection” – most famously put forward and defended by Williamson (2007, 2009, 2011). In brief,
this objection claims that the judgments of philosophers ought to be trusted more than those
of non-philosophers when it comes to the examination of philosophically interesting topics, because philosophers are trained to think carefully and rigorously. Like the previous objection,
this criticism misfires when aimed at experimental explication. In experimental explication, nonphilosophers’ intuitive judgments are only introduced to ensure that our explicatum remains
connected to the appropriate explicandum. Such judgments are not taken to be giving us answers
to our philosophical questions. Experimental explication’s proponents are accordingly free to accept (or reject) the idea that philosophers have a special expertise when it comes to studying the
philosophical implications of various concepts.
Regarding the expertise objection, note too that, when pursuing experimental explication, it
may be that one ought to attend especially or even solely to philosophers’ intuitions. But, as mentioned earlier, whether this is true very much depends on the explicandum that one is studying. If
the philosopher desires to explicate a philosophers’ concept (a concept that gets its characteristic
20 Similarly,
Kauppinen (2007, p. 96) writes, “Why should anybody care about what philosophers do if they just argued
about their own inventions? People want to know if they have moral responsibility or knowledge of other minds in the
very sense in which they ordinarily talk about responsibility or knowledge, and to get at that sense one must work with
the folk’s own concepts.”
32
and predominant application within the context of philosophy by philosophers), then observations of non-philosophers judgments related to the appropriate term(s) will only introduce unnecessary confusion into the study. Often, however, we are interested in the philosophical study
of concepts that are understood and used by non-philosophers. And, due to their training and
rigorous modes of thinking, philosophers’ concepts may be too refined by philosophical reflection
to maintain the connection to the concepts of non-philosophers that is necessary if the former is
meant to represent the latter.
5 Conclusion
Carnap’s method of explication is frequently applied in contemporary formal philosophy. And
it is used for at least two different ends; Carnapian explication seeks to engineer fruitful new
concepts and Oppenheimian explication strives to clarify a concept by making it more precise. I
have argued that an important criticism of this method – going back to Strawson – calls much
contemporary explicative work into question. To be sure, philosophers (especially philosophers
of the special sciences) who pursue Carnapian explications need not worry about the Strawsonian
challenge, given that their projects naturally lead them to subordinate the similarity desideratum
to fruitfulness. However, philosophers who attempt Oppenheimian explications must inevitably
face the challenge of establishing that explicata and explicanda maintain enough of a resemblance
for the former to illuminate the latter.
I have introduced experimental explication, an experimentally-informed variation on explication, as a means for formal philosophers to meet this challenge. Empirical methods supply the
formal philosopher with the requisite tools to test just how closely explicata align with explicanda. To the extent that such research shows that the fit between the two is very close, the formal
philosopher gains a line of response to those who would press the Strawsonian challenge. For
this reason, experimental explication should appeal greatly to the many formal philosophers who
apply explication in order to clarify otherwise imprecise concepts.
Experimental explication highlights a philosophically salient role for empirical research surveying people’s intuitive judgments. These judgments are not explored in order to gain direct
philosophical insight or answers to our philosophical questions. Rather, they provide the formal
philosopher with a clearer perspective on the target explicandum, which is necessary for ensuring
that the formal account developed will maintain a relevance to the original, target concept. By
putting intuitions to this positive use, experimental explication steers clear of several skeptical
worries. It thus provides the experimentalist with a more defensible example of how empirical
33
work can have positive philosophical import; experimental explication effectively constitutes a
counterexample to anyone who would argue that empirical research can have no positive philosophical bearing. For this reason, experimental explication should appeal to experimental philosophers (at least those working within the positive program).
Despite appearances then, formal philosophy and experimental philosophy are not only compatible, but they can be mutually supportive. When these are combined in the form of experimental explication, the philosopher gains a powerful method for investigating the nature and
implications of otherwise imprecise concepts. Of course, nothing I have written here should suggest that all philosophical questions are susceptible to experimental explication. Nonetheless, this
method constitutes an effective but so-far largely neglected tool for investigating many important
and venerable philosophical questions.
References
Alexander, J., Mallon, R., and Weinberg, J. M. (2010). Accentuate the negative. Review of Philosophy
and Psychology, 1(2):297–314.
Austin, J. L. (1956 – 1957). A plea for excuses. Proceedings of the Aristotelian Society, 57:1–30.
Boniolo, G. (2003). Kant’s explication and Carnap’s explication: The redde rationem. International
Philosophical Quarterly, 43(3):289–298.
Bovens, L. and Hartmann, S. (2003). Bayesian Epistemology. Oxford University Press, New York.
Carnap, R. (1947). Meaning and Necessity. University of Chicago Press, Chicago.
Carnap, R. (1950). Logical Foundations of Probability. University of Chicago Press, Chicago.
Carnap, R. (1955). Meaning and synonymy in natural languages. Philosophical Studies, 6(3):33–47.
Carnap, R. (1958). Introduction to Symbolic Logic and its Applications. Dover Publications, New York.
Translated by William H. Meyer and John Wilkinson.
Carnap, R. (1963). P. F. Strawson on linguistic naturalism. In Schilpp, P. A., editor, The Philosophy
of Rudolf Carnap, volume XI of The Library of Living Philosophers, pages 933–940. Open Court, La
Salle, IL.
Carus, A. W. (2007). Carnap and Twentieth-Century Thought: Explication as Enlightenment. Cambridge
University Press, Cambridge.
34
Christensen, D. (1999). Measuring confirmation. The Journal of Philosophy, 96(9):437–461.
Crupi, V., Tentori, K., and Gonzalez, M. (2007). On Bayesian measures of evidential support:
Theoretical and empirical issues. Philosophy of Science, 74:229–252.
Deutsch, M. (2009). Experimental philosophy and the theory of reference. Mind & Language,
24(4):445–466.
Douven, I. and Meijs, W. (2007). Measuring coherence. Synthese, 156:405–425.
Douven, I. and Verbrugge, S. (2010). The Adams family. Cognition, 117(3):302–318.
Douven, I. and Verbrugge, S. (2013). The probabilities of conditionals revisited. Cognitive Science,
37(4):711–730.
Eells, E. and Fitelson, B. (2002). Symmetries and asymmetries in evidential support. Philosophical
Studies, 107(2):129–142.
Ereshefsky, M. (1992). Eliminative pluralism. Philosophy of Science, 59(4):671–690.
Feltz, A. and Cokely, E. (2012). The philosophical personality argument. Philosophical Studies,
161(2):227–246.
Fitelson, B. (2006). Logical foundations of evidential support. Philosophy of Science, 73:500–512.
Fitelson, B. and Hitchcock, C. (2011). Probabilistic measures of causal strength. In Illari, P. M.,
Russo, F., and Williamson, J., editors, Causality in the Sciences, pages 600–627. Oxford University
Press, Oxford.
Good, I. J. (1960). Weight of evidence, corroboration, explanatory power, information and the utility of experiments. Journal of the Royal Statistical Society. Series B (Methodological), 22(2):319–331.
Haber, M. (2013). Colonies are individuals. In Bouchard, F. and Huneman, P., editors, From Groups
to Individuals, chapter 9, pages 195–217. MIT Press, Cambridge, Mass.
Halpern, J. Y. and Pearl, J. (2005). Causes and explanations. British Journal for the Philosophy of
Science, 56(4):843–887.
Harris, A. J. L. and Hahn, U. (2009). Bayesian rationality in evaluating multiple testimonies. Journal
of Experimental Psychology: Learning, Memory and Cognition, 35(5):1366–1373.
Hintikka, J. (1999). The emperor’s new intuitions. The Journal of Philosophy, 96(3):127–147.
35
Hitchcock, C. (2012). Thought experiments, real experiments, and the expertise objection. European
Journal for Philosophy of Science, 2(2):205–218.
Horne, Z. and Livengood, J. (Unpublished). Ordering effects, updating effects, and the specter of
skepticism.
Jackson, F. (2011). On Gettier holdouts. Mind & Language, 26(4):468–481.
Jeffrey, R. (1994). Carnap’s voluntarism. In Dag Prawitz, B. S. and Westerstahl, D., editors, Logic,
Methodology and Philosophy of Science IX, pages 847–866. Elsevier, Amsterdam.
Jeffrey, R. C. (1975). Carnap’s empiricism. Minnesota Studies in the Philosophy of Science, VI: 37–49.
Jenkins, C. S. I. (2014). Intuition, ‘intuition’, concepts and the a priori. In Booth, A. and Rowbottom,
D. P., editors, Intuitions, pages 91-115. Oxford University Press, Oxford.
Justus, J. (2012). Carnap on concept determination. European Journal for Philosophy of Science,
2(2):161–179.
Kauppinen, A. (2007). The rise and fall of experimental philosophy. Philosophical Explorations,
10(2):95–118.
Kemeny, J. G. and Oppenheim, P. (1952).
Degree of factual support.
Philosophy of Science,
19:307–324.
Kitcher, P. (1982). Genes. The British Journal for the Philosophy of Science, 33(4):337–359.
Kitcher, P. (1984). Species. Philosophy of Science, 51(2):308–333.
Kitcher, P. (2008). Carnap and the caterpillar. Philosophical Topics, 36(1):111–127.
Knobe, J. and Nichols, S., editors (2008). Experimental Philosophy. Oxford University Press, Oxford.
Liao, S. M. (2008). A defense of intuitions. Philosophical Studies, 140(2):247–262.
Livengood, J. and Machery, E. (2007). The folk probably don’t think what you think they think.
Midwest Studies in Philosophy, 31:107–127.
Loomis, E. and Juhl, C. (2006). Explication. In Sarkar, S. and Pfeifer, J., editors, The Philosophy of
Science: An Encyclopedia, volume 1, pages 287–294. Routledge, New York.
Machery, E. (2011).
Thought experiments and philosophical knowledge.
42(3):191–214.
36
Metaphilosophy,
Machery, E., Mallon, R., Nichols, S., and Stich, S. P. (2004). Semantics, cross-cultural style. Cognition, 92(3):B1–B12.
Maher, P. (2007). Explication defended. Studia Logica, 86:331–341.
Maher, P. (2010). Explication of inductive probability. Journal of Philosophical Logic, 39(6):593–616.
Mallon, R., Machery, E., Nichols, S., and Stich, S. (2009). Against arguments from reference.
Philosophy and Phenomenological Research, 79(2):332–356.
Mates, B. (1958). On the verification of statements about ordinary language. Inquiry, 1(1):161–171.
McGrew, T. (2003). Confirmation, heuristics, and explanatory reasoning. British Journal for the
Philosophy of Science, 54:553–567.
Mills, S. K. and Beatty, J. H. (1979). The propensity interpretation of fitness. Philosophy of Science,
46(2):263–286.
Millstein, R. (2009). Populations as individuals. Biological Theory, 4:267–273.
Milne, P. (1996). log[ p(h|b)/p(h|b)] is the one true measure of confirmation. Philosophy of Science,
63:21–26.
Nadelhoffer, T. and Nahmias, E. (2007). The past and future of experimental philosophy. Philosophical Explorations, 10(2):123–149.
Ness, A. (1938). “Truth” as Conceived by Those Who are Not Professional Philosophers, volume 4 of
Skrifter utgitt av Det Norske Videnskaps-Akademi i Oslo, 11. Hist.-Filos. Klasse. I Kommisjon Hos
Jacob Dybwad, Oslo.
Nichols, S. and Knobe, J. (2007). Moral responsibility and determinism. Noûs, 41(4):663–685.
Nichols, S., Stich, S., and Weinberg, J. M. (2003).
Metaskepticism: Meditations in ethno-
epistemology. In Luper, S., editor, The Skeptics. Ashgate, Burlington, VT.
Nisbett, R. E. (2003). The Geography of Thought : How Asians and Westerners Think Differently...and
Why. Free Press, New York.
Nisbett, R. E., Peng, K., Choi, I., and Norenzayan, A. (2001). Culture and systems of thought.
Psychological Review, 108(2):291–310.
Okasha, S. (2011). Biological ontology and hierarchical organization. In Calcott, B. and Sterelny, K.,
editors, The Major Transitions in Evolution Revisited, pages 53–64. MIT Press, Cambridge, Mass.
37
Phillips, L. D. and Edwards, W. (1966). Conservatism in a simple probability inference task. Journal
of Experimental Psychology, 72(3):346–354.
Quine, W. V. O. (1960). Word and Object. The Technology Press of the Massachusetts Institute of
Technology, New York.
Ryle, G. (1953). Ordinary language. The Philosophical Review, 62(2):167–186.
Schupbach, J. N. (2011a). Comparing probabilistic measures of explanatory power. Philosophy of
Science, 78(5):813–829.
Schupbach, J. N. (2011b). New hope for Shogenji’s coherence measure. British Journal for the
Philosophy of Science, 62:125–142.
Schupbach, J. N. and Sprenger, J. (2011). The logic of explanatory power. Philosophy of Science,
78(1):105–127.
Schwitzgebel, E. and Cushman, F. (2012). Expertise in moral reasoning?
Mind & Language,
27(2):135–153.
Shogenji, T. (1999). Is coherence truth-conducive? Analysis, 59(4):338–345.
Sober, E. (2001). The two faces of fitness. In Singh, R. S., Krimbas, C. B., Paul, D. B., and Beatty, J.,
editors, Thinking about Evolution, volume 2. Cambridge University Press, Cambridge.
Sosa, E. (2009). A defense of the use of intuitions in philosophy. In Murphy, D. and Bishop, M.,
editors, Stich and His Critics, pages 101–112. Blackwell, Oxford.
Stegenga, J. (Forthcoming). Population pluralism and natural selection. British Journal for the
Philosophy of Science.
Stich, S. (1988). Reflective equilibrium, analytic epistemology and the problem of cognitive diversity. Synthese, 74(3):391–413.
Stich, S. (2009). Reply to Sosa. In Murphy, D. and Bishop, M., editors, Stich and His Critics, pages
228–236. Blackwell, Oxford.
Strawson, P. F. (1963). Carnap’s views on constructed systems versus natural languages in analytic
philosophy. In Schilpp, P. A., editor, The Philosophy of Rudolf Carnap, volume XI of The Library of
Living Philosophers, pages 503–518. Open Court, La Salle, IL.
Swain, S., Alexander, J., and Weinberg, J. M. (2008). The instability of philosophical intuitions.
Philosophy and Phenomenological Research, 76(1):138–155.
38
Sytsma, J. (2010). The proper province of philosophy: Conceptual analysis and empirical investigation. Review of Philosophy and Psychology, 1:427–445.
Sytsma, J. and Livengood, J. (Forthcoming). The Theory and Practice of Experimental Philosophy.
Broadview.
Sytsma, J. and Machery, E. (2010). Two conceptions of subjective experience. Philosophical Studies,
151(2):299–327.
Sytsma, J. and Machery, E. (2013). Experimental philosophy. In Kaldis, B., editor, Encyclopedia of
Philosophy and the Social Sciences, pages 319–321. SAGE Publications, Inc.
Tentori, K., Crupi, V., Bonini, N., and Osherson, D. (2007). Comparison of confirmation measures.
Cognition, 103:107–119.
Waters, C. K. (1994). Genes made molecular. Philosophy of Science, 61(2):163–185.
Weinberg, J. M. (2007). How to challenge intuitions empirically without risking skepticism. Midwest Studies in Philosophy, 31:318–343.
Weinberg, J. M., Nichols, S., and Stich, S. (2001). Normativity and epistemic intuitions. Philosophical
Topics, 29:429–460. Reprinted in (Knobe and Nichols, 2008, pp. 16-45).
Williamson, T. (2007). The Philosophy of Philosophy. Blackwell, Oxford.
Williamson, T. (2009).
Replies to Ichikawa, Martin and Weinberg.
Philosophical Studies,
145(3):465–476.
Williamson, T. (2011).
Philosophical expertise and the burden of proof.
42(3):215–229.
Woodward, J. (2003). Making Things Happen. Oxford University Press, Oxford.
39
Metaphilosophy,