Competence and Performance Redescribed

In discussion with Jeff Lidz one morning on the way to getting my cup of tea (this is my favorite time to waylay unsuspecting colleagues for linguist in the street interviews) we fell into discussion of how to explain the C(ompetence)/P(erformance) (C/P) distinction.  One thing I have often found useful is to find alternative descriptions of the same thing. Here’s a version I’ve found helpful. Let’s cast the C/P distinction in terms of Data Structures (DaSt) and the operations (or algorithms (algs)) that operate on them. What’s the difference between these notions and how might this terminology illuminate the C/P distinction?

Chomsky has standardly distinguished what we know (competence) from how we put what we know to use (performance).  He further proposes describing the former as a computational state; initial states describing the capacity for a certain kind of competence and the steady state as describing the actual competence.  Thus, UG describes the initial state of FL and the G attained describes the steady state of the language acquisition device (i.e. yours and your linguistic conspecifics).  How are we to understand these states?  The discussion in Gallistel & King (G&K) on DaSts and the operations/algs that work on them provides a useful handle.  

G&K (149) describe a DaSt as “a complex symbol” whose “constituents are themselves symbols” and whose “referent …is determined by the referents of its constituents and the syntactic…relation between them.”   Thus, “[c]omplex data structures encode the sorts of things that are asserted in what philosophers and logicians call propositions” (150) and what linguists call (sets of) phrase markers. Actually the linguistic notion might be closer as the operations manipulate DaSts exclusively in virtue of their formal syntactic properties. How these are interpreted plays no role in what kinds of things operations on DaSts can do.  This makes them effectively syntactic objects like phrase markers rather than semantic objects like propositions.

Using this terminology, a theory of competence aims to describe the linguistic DaSts that the mind/brain has. The initial state (UG) consists of certain kinds of DaSts, the final state (Gs) with particular instances of such DaSts. A particular G is a recursive specification of the permissible DaSts in a given I-langauge. UG specifies the kinds of DaSts (i.e. Gs) that FL allows by describing the range of permissible generative procedures (rules for recursively specifying Gs/I-language specific DaSts). The theory of UG aims to outline what kinds of features linguistic DaSts can have, what kind of syntactic relations are permissible, what kinds of constituents are possible etc.  The theory of a particular G (e.g. G_E, the grammar of English) will specify which DaSt options that UG provides G_E realizes. Both these accounts specify what the system “knows,” i.e. the kinds of representations it allows, aka the kinds of DaSts it tolerates.  In other words, a theory of linguistic DaSts is a competence theory.

Algs are procedures that use these data structures in various ways. For example, an alg can use DaSts to figure out what someone said or what to say or what rhymes with what or what follows from what. e.g. could operate on the phonological DaSts to determine the set of rhyming pairs. Algorithms can be fast or slow, computationally intensive or not, executable in linear time etc.  None of these predicates apply to DaSts. Different algs for different tasks can use the same DaSts.  Algs are ways of specifying the different things one can do with DaSts. Algs are parts of any performance theory.

G&K emphasize the close connection between DaSts and Algs. As they note:

There is an intimate and unbreakable relation between how information is arranged [viz. the DaSts, N]…and the computational routines that operate on the information [viz. algs, N]…(164).

Consequently, it is quite possible that the computational context can reveal a lot about the nature of the DaSts and vice versa.  I have suggested as much here, when I mooted the possibility that systems that have bounded content addressable memories might guard against the problems such systems are prone to by enforcing something like relativized minimality on the way that DaSts are organized.  In other words, the properties of the users of DaSts can tell us something about properties of the DaSts.

Another way of triangulating on properties of a DaSt D1 is by considering the properties of the other DaSts- D2, D3 – D1 regularly interacts with. A well-designed D1 should be sensitive to how D1 interacts with D2 and D3. How well do they fit together? What would be an optimal fit? As the government learns weekly when it tries to integrate its various databases, some DaSts play together more nicely than others do.

So, the theory of competence can be viewed as the theory of the linguistic DaSts; what are their primitive features? How are the assembled? What kinds of relations do they encode? The theory of performance can be viewed as asking about the algs that operate on these DaSts and the general cognitive architectural environment (e.g. memory) within which these algs operate.  Both DaSts and algs contribute to linguistic performance. In fact, one of minimalism’s bets is that one can learn a lot about linguistic DaSts by carefully considering what a well designed linguistic DaSt might be like given its interactions with other DaSts and how it will be used. So, performance considerations can (at least in principle) significantly inform us about the properties of linguistic DaSts. We want to know both about the properties of linguistic representations and about the operations that use these representations for various ends. However, though closely related, the aim of theory is to disentangle the contributions of each. And that’s why the distinction is important.

The Rationalism of Generative Grammar

 The theory of mind that Generative Grammar endorses is evidently rationalist. An earlier post gestured (don’t you love that word!) to these philosophical roots. Interestingly (though not surprisingly), the scientific metaphysics is as well. Here’s what I mean.

I was recently reading a fascinating book by Nancy Cartwright -The Dappled World- (highly recommended for philo of science aficionados) in which she contrasts the role of powers/natures/capacities versus regularities in scientific theory.  The classical empiricist/Humean tradition rejected the former as occult residues of an earlier search for Aristotelian essences and insisted on founding all scientific knowledge on “the kinds of qualities that appear to us in experience (79)” (recall the dictum: nothing in the intellect that is not first in the senses!). Modern empiricists/Humeans endorse this antipathy to “powers” by treating the laws of nature as summaries of “what things do (82).” Cartwright contrasts this with the view that laws are about powers/natures/capacities, which is not about what things do but “what it is in their nature to do (82).” Here’s a quote that provides a good feel for what she has in mind:

What we have done in modern science, as I see it, is to break the connection between what the explanatory nature is- what it is in and of itself- and what it does. An atom in an excited state, when agitated, emits photons and produces light. It is, I say, in the nature of an excited atom to produce light. Here the explanatory feature –an atom’s being in an excited state- is a structural feature of the atom…For modern science what something really is -how it is defined and identified- and what it is in its nature to do are separate things.

In short, there is an important metaphysical distinction that divides Empiricists and Rationalists. For the former the laws of nature are in effect summaries (perhaps statistical) of “actually exhibited behaviors”, for the latter they describe abstract “configurations of properties” or “structures.” These latter underlie, but are distinct from, behavior (“what appears on the surface”), these being “the result of the complex interaction of natures (81).”

Cartwright notes the close connection between the Rationalist conception of powers/natures/capacities and the analytic method of inquiry characteristic of the physical sciences, often called “Galilean idealization.” She also provides several interesting reasons for insisting on the distinction between what something is versus what it does. Here are two.

First, given that visible behavior is an interaction effect of complex natures it is often impossible to actually see the contribution of the power one is interested in, even in the very contrived circumstances of controlled experiments. She illustrates this using Coulomb’s law and the interfering effects of gravity. As she points out:

Coulomb’s law tells not what force charged particles experience but rather what it is in their nature, qua charged, to experience…What particles that are both massive and charged actually experience will depend on what tendency they have qua charged and what qua massive (82).

Thus, actual measurable forces are the result of the interaction of several powers and it takes great deal of idealization, experimentation, calculation and inference to (a) simply isolate the effects of just one and segregate it from everything else, viz. to find out how two charged bodies “ ‘would interact if their masses were zero.’ ”[1]  And (b) to use the results from (a) to find out what the actual powers involved are:

The ultimate aim is to find out how the charged bodies interact not when their masses are zero, nor under any other specific set of circumstances, but how they interact qua charged. 

Second, contrary to the accepted wisdom more often than not in the real world the same cause is not followed by the same effect.  In fact, generating stable relations between cause and effect requires very careful contrivance in manufactured artificial experimental settings.  Cartwright refers to these as nomological engines; set-ups that allow for invariant regular connections between what powers/natures/capacities can do and what they actually do. Except in such settings the Humean dictum that effects regularly follow causes is hardly apparent.

Outside the supervision of a laboratory or the closed casement of a factory-made module, what happens in one instance is rarely a guide to what will happen in others.  Situations that lend themselves to generalizations are special…(86).

Now, the punch line: Cartwright’s discussion should sound familiar to generative ears. Chomsky’s important distinction between competence and performance is a rationalist one.  UG is a theory of human linguistic powers/natures/capacities, not a theory of linguistic behavior.  UG is not a summary of behavioral regularities. Indeed, linguistic behavior is a very complex interaction effect with competence being one of many (very poorly understood) factors behind it. The distinction between what a speaker knows (competence) and what a speaker puts this knowledge to use (performance) echoes Cartwright’s rationalist themes. Similarly, the rejection of the idea that linguistic competence is just (a possibly fancy statistical) summary of behavior should be recognized as the linguistic version of the general Rationalist endorsement of the distinction between powers/natures/capacities and their behavioral/phenomenal effects. Lastly, the Rationalist conception buttresses a reasonable skepticism against a currently common (and sadly fashionable) view that language acquisition is largely a statistical exercise where minds track environmental regularities, a view more congenial with the empiricist conception that identifies what something is with what it does. This cannot be true: for there are precious few such regularities in the wild and what there is won't (in fact cannot) alone reveal the powers, capacities and natures of the underlying object of linguistic interest, i.e. the fine structure of UG.

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[1] Cartwright observes that though doing (1) is difficult it is “just a stage; in itself this information is uninteresting.” (83-4), a point not unlike that made in a previous post.