5. Developing an Alternative 209
hearer. The speaker’s and hearer’s processes of production and comprehension, however, are grounded in context.
Another difference between revolutionary and code model-based approaches to discourse is that, rather that seeing the text as being composed of coded segments with
gaps, revolutionary linguists see the text as being related to a conceptual unit, rather than simply a unit which would have been more traditionally been considered “linguistic.” For
example, cognitivists envision the text as being related to and organized via schema. The speaker’s goal in producing the text then, is to stimulate the hearer to conceive of a
particular scheme. Within such a view, the fact that gaps exist between respective sen- tential strings may then be comparatively insignificant, since the manner in which the
strings relate to the schema may be more significant than how the strings are supposedly related to one another.
This notion of schema is, of course, related to the idea of notional structure. For the revolutionary linguist, however, the schema exist in the mind of the speaker and hearer.
They are not in the text. The notion of schema may also seem to bear resemblance to the notion of shared
knowledge. The two notions are not equivalent, however, in that it is not presumed that speaker and hearer will necessarily comprehend the text according to the same schema.
In this way, the revolutionary linguist emphasizes the process of comprehension, rather than the “meaning” of the text.
5.3. Other models
As was addressed briefly in chapters 3
and 4
, the code model and its constituent models are not the only models or metaphors of communication recorded in the literature;
however, they are the most pervasive within linguistic literature. This section provides a cursory review of additional models and metaphors. It should be noted that some of them
depend upon the code model or are otherwise related to it in some way.
The study examines these models from the perspective of linguistic concerns and the present study of the code model. Where relevant, the study address how the models
would handle particular code model anomalies.
5.3.1. Mechanistic models
Ronald Langacker has provided some discussion of metaphors in linguistic metatheory, including the container and conduit metaphors as addressed by Reddy and
reviewed by Lakoff and Johnson 1980
; also see Johnson 1987
; Lakoff 1987
; Moore and
Carling 1982 . Langacker also mentions the dictionary view and the building-block
metaphor see Langacker 1987
:161, 1991
:507–508:
The conduit metaphor dovetails with the dictionary view of lexical semantics, which holds that a word’s linguistic meaning is strictly limited and distinct from general knowledge, and
also with the building-block metaphor, wherein the meaning of a complex expression is
210 5. Developing an Alternative
constructed just by stacking together the meanings of its parts in accordance with general combinatory rules.
Langacker 1991 :508
Langacker continues, adding that, “This way of thinking and talking is so ingrained that there is no point trying to avoid it. We will be well advised, however, to remember
that it represents a blatantly inaccurate folk model capable of leading us into serious error to the extent that we tacitly adopt it for theoretical purposes”
Langacker 1991 :508.
In addition to these common metaphors, the origins of which may be found in folk theory, Langacker suggests that the generative tradition has contributed to the use of
several additional metaphors. These include the machine or assembly line metaphor, electronic device metaphors i.e., language as black box, components, device, and
modular system, and mathematical metaphors i.e., language as algorithm, computer program, and formal deductive system.
Of the latter three types, Langacker comments: “These three classes of metaphors— based on machines, electronics and mathematics—all manifest an overarching metaphor
that construes the mind as being analogous to a serial digital computer” 1991
:509. Highlighting the role of such metaphors in the structure of tacit knowledge, Langacker
continues:
The power of such a metaphorical system should not be underestimated. Far from being merely heuristic, it can be recognized as the source of tacit but nonetheless pervasive attitudes,
working assumptions, and methodological stances. Although perhaps nobody would defend it as being fully appropriate, still it offers conceptual coherence for views explicitly held, biases
research towards certain kinds of approaches and subject matter, and determines whether an idea will be adopted by default or accepted only reluctantly even when supported by over-
whelming evidence. Let us note just a few examples. The attitude that a linguistic description ought to be as brief and economical as possible consistent with generating the right forms
coheres with the standard conception of optimality for machines which are supposed to be efficient, computer programs quick-running, and mathematical proofs sparse and elegant.
The analogy to formal logic and digital computers engenders the expectation that linguistic expressions should be describable in terms of well-defined operations on strings of discrete
symbols or other discrete representations, such as phrase trees and feature bundles. Also, the fundamental notation that a phenomenon has a single “right” analysis, and that the proper
description of languages must conform to a specific kind of formal theory, is reinforced by the knowledge that a mechanical or electronic device operates in a particular way, and that a
computer does what it does because a specific program tells it to.
Langacker 1991 :509
Langacker also comments on the relationship such metaphors may have to the idealized notion of the “hard sciences.” He warns that these metaphors may have
attractive qualities that are disproportionate to their actual value in guiding analytical investigation:
In addition to their metaphorical coherence, such notions resonate with our idealized cognitive model of “hard science.” Hence they are generally considered self-evident and
uncontroversial, so obvious that they are simply taken for granted. Yet they are all subject to legitimate question, as is the appropriateness to natural language of the metaphorical system
they reflect. Langacker 1991
:509–510
5. Developing an Alternative 211
In an illuminating footnote he adds: “It is no doubt incidental that they [the meta- phors] have the further advantage of defining the task of linguistic investigation in terms
that correspond to what most linguistic theorists are best equipped to do” Langacker
1991 :509.
While Langacker does provide a good review of these metaphors and their use in linguistics, showing special concern over metaphors that build upon the idea of a “digital
computer,” it is unfortunate that he does not address the code model of communication, for some of these lesser metaphors have their origin in the code model. The mechanical,
electronic, and computer metaphors are directly related to use of the code model and related information theory in psychology and linguistics. As has been discussed, infor-
mation theory was initially developed in the context of electrical engineering and some of its earliest points of entry into linguistics were through psychology.
Langacker’s attribution of these “digital computer” models to the generative tradition is also somewhat misdirected. It is true that the generative tradition has emphasized some
of these metaphors, but as has been shown, use of the code model upon which they are based far exceeds the generative tradition.
5.3.2. Motor theory
