This past summer, I finished and defended my Master’s thesis.  Though my work has moved from linguistics and philosophy of language to causal and statistical reasoning (the Tetrad project), I’m still researching natural-language in my spare time. Therefore, I will be writing a series of posts here on Unwanted Capture concerning my linguistic work, both to get my ideas out there and to encourage myself to continue thinking about linguistic issues.

My research has centered around implicature theory, a topic in the field of pragmatics.  This series will walk through the research I have done and the theory proposed in my thesis.  In doing so, it will start from the absolute basics; the series will be self-contained, presupposing only basic knowledge of logic and naive set theory.

This first post will serve to introduce pragmatics, the study of non-literal meaning.

What is pragmatics?

Pragmatics is the study of language in use. It can also be considered the study of non-literal meaning. Taken in the second sense, pragmatics carves the study of meaning in half with its sister science, semantics. Between characterizing literal and non-literal meaning, the science of linguistic interpretation is (ideally) fully spanned.

Pragmatics may best be understood as the complement of semantics. Semantics is the study of literal, cross-contextual meaning.

Characterizing semantics as the science of “meaning”, however, means nothing if we don’t properly understand the term “meaning”. Any theory of meaning must first pin the meaning of “meaning” if the enterprise is to get off of the ground.

Properly and fully analyzing the word “meaning” in a way that matches our pre-theoretic intuitions about the concept is a philosophical problem that still has no satisfactory solution. Any attempt to flesh out the concept either misses some important component of what we consider meaning or falsely attributes extra, incorrect properties to it. However, a working definition that has worked quite well for systematic scientific study is one promoted by philosopher Donald Davidson; if meaning is viewed as “truth-conditional meaning”, then familiar, rigorous methods in formal semantics (typically reserved for logical, constructed languages) can be used to study natural-language.

Viewing the meaning of a sentence as its truth-conditions (the conditions under which the sentence is true) fails to capture many aspects of meaning. It doesn’t capture shades of meaning, for instance, that separate one poetic statement from another. While other aspects of meaning are still important and worth explaining, there’s something to be said about the truth-conditional viewpoint. If a speaker knows the meaning of a particular statement, then it’s reasonable to say that the speaker knows when the statement is true or false. In other words, knowing the meaning of a sentence means knowing what makes the sentence true; if someone didn’t know what made a sentence true, then debatably the person doesn’t know what it means.

Thus, truth-conditional meaning is a proper subset of meaning at large. To explain and study meaning as a whole, one must explain and study the truth-conditions of sentences and how they are acquired. Though this is but a sub-part of the total problem of meaning, this sub-part is far from being adequately solved; even so, it is the most fruitful and quantified area of investigation into linguistic interpretation.

When we say things such as “Sally had a baby and got married”, semantics’ job is to tell us the truth-conditions of this sentence that are contained solely in the words used (and not in their connotations). Any semantic theory worth its salt will tell us that “Sally had a baby and got married” is true just in case Sally, in fact, had a baby and got married. Nothing shocking here; semantics, viewed in this way, seems like a trivial topic. Needless to say, as we consider general theories of interpretation that must account for the behavior of complicated logical and intensional operators, accurate semantic theorizing gets a lot harder.

Semantics cannot distinguish between the following two sentences:

A: “Sally had a baby and got married.”

B: “Sally got married and had a baby.”

Literally speaking, A and B both say the same thing. A is true just in case Sally, in fact, had a baby and got married. B is true in the exact same conditions, and so A and B have the same semantic content (written ||A|| = ||B||, where “||A||” is read “the interpretation of A”).

A good way to characterize pragmatics is to point out that, from the pragmatic point of view, A and B say quite different things. Sentence A suggests that Sally had a baby before she got married, while sentence B suggests things the other way around. The order of appearance for the conjuncts in these sentences matters; we tend to understand the order of appearance in a list of conjuncts as a temporal ordering, though nothing about the word “and” itself mandates this interpretation.

A pragmatic theory of the behavior of “and” should account for this non-literal difference between the meaning of A and B, whereas a semantic theory isn’t on the hook for such a thing.

Why care?

The difference between A and B above is so natural that it hardly seems to call for an explanation. However, there are plenty of reasons to care about characterizing such linguistic behavior mathematically.

The ease at which human beings incorporate non-literal speech in discourse is a fact worth explaining. Hardly anything humans utter contains purely literal meaning; what we utter doesn’t merely borrow from the words we utter, but also from general facts about human reasoning. In other words, context matters. Where, when, and how we say things play systematically into constructing the meaning of what we say.

Crafting an explanation of how language in use spans nearly every unique cognitive aspect of humankind. It means crafting a model of human reasoning as it applies to language and communication; this bridges what we find salient and what we expect others to find salient in the immediate context, shared knowledge, and other domains of belief. Explaining how we engage in linguistic reasoning involves explaining facts about reasoning at large.

For those with a more practical streak, pragmatics is an essential sub-problem in constructing artificial intelligence. Sophisticated artificial intelligence will require sophisticated communicative ability. Without being able to understand non-literal speech, our artificial agents will have serious trouble communicating reliably with humans. Such limitations necessarily limit their ability to perform; if artificial agents are to serve wider and more useful roles, their ability to converse naturally with laypeople will be absolutely essential.

Pragmatics then, broadly construed, is the attempt to predict natural, systematic linguistic inferences. Along with a good theory of semantics, a complete theory of pragmatics would afford us a truth-conditionally complete theory of meaning. Such a theory would be able to take any utterance and fully decode its meaning-in-context.

The problem in pragmatics that this series will be investigating is that of conversational implicature. The next post will be concerned with defining implicature and some of its sub-phenomena, one in particular to which my theory applies.