Cognitive linguistics as a methodological paradigm--论文代写范文精选

然而整个方法应该保持统一分析，如果我们想要达到一个适当的对自然语言的理解。主流认知科学情报主要计算以下方法，聪明的表现被视为某些象征性的过程。这些过程占这种认知、语言处理。在当今认知科学无处不在。下面的essay代写范文进行详述。

Introductory Remarks 
The word cognitive has become very in. We speak of cognitive grammar (Langacker 1987, 1999, Heine 1997), cognitive semantics (Allwood, Gaerdenfors 1999, Talmy 2000), cognitive pragmatics (Nemeth 2001) and, ultimately, cognitive linguistics. How is cognitive linguistics different from simply linguistics? Contemporary literature suggests a variety of possible answers, but common to them all is an understanding that “languaging” is a cognitive activity (Clark 1996, Verschueren 1999), and since cognition is the essential functional feature of a living organism (Maturana 1970), cognitive linguistics is, naturally, concerned with the human factor and with cognitive structures categorized and represented in language (Fox, Jurafsky, Michaelis, 1999). This implies that language as an object of study should be analyzed along the following three dimensions: (i) language and the mind, i. e. knowledge and consciousness (Johnson-Laird 1983, Carruthers 1996, Lycan 1996, Wagman 1998, Brook, Stainton 2000), (ii) knowledge and mental structures, i. e. categorization and conceptualization (Rosch 1977, Smith, Medin 1981, Neisser 1987, Jackendoff 1992, Nolan 1994, Lamberts, Shanks 1997), (iii) information and the sign, i. e. the semiotic problem of meaning (Castañeda 1990, McGregor 1997, Keller 1998). Yet the overall approach should remain holistic (Josephson, Blair, 1982) if we want to achieve an adequate understanding of natural language.

The mainstream cognitive science approach to intelligence is largely computational: intelligent performance is viewed as certain symbolic processes involving representations (Fodor, 1975, 1998; Newell, 1990; Pylyshyn, 1999; Fuchs & Robert, 1999 inter alia). These processes account for such cognitive capacitiesas perception, language acquisition and processing, planning, problem solving, reasoning, learning, and the acquisition, representation, and use of knowledge (Lepore & Pylyshyn, 1999). The computational metaphor in today’s cognitive science pervades everything, from philosophical psychology to applied tasks in natural language processing. This is only to be expected, since man has been under a spell cast by computer technology for quite some time now. Yet I believe it is time we took a more critical look at developmental prospects of computationally clad cognitive science. Does human mind really work like a computer? It is not my intention to open a discussion here trying to find an answer to this rather impertinent question, since it would lead us astray from the topic of our main concern, which is cognitive linguistics as a methodological paradigm. I will only make a few remarks of a very general character, with the sole purpose of justifying, or at least making an attempt to justify, what will follow in the main body of this paper.

The Problem with Computational Metaphor 
The holistic, or metaphysical approach consists in treating language as a natural biological phenomenon uniquely characteristic of the species homo sapiens (Bickerton, 1990; Pinker, 1995). Yet in the predominant cognitive paradigm language is, typically, defined as a sign system for categorizing, storing, retrieving, and processing information. Hence, according to Fodor, “meaning is information” (Fodor, 1998:12). It is not therefore surprising that Alan Turing’s metaphor “thinking is computation” is routinely exploited in cognitively oriented linguistic research, forming the basic tenet of contemporary generativism a la Chomsky - Fodor - Jackendoff and leading to heated discussions about the nature of mental representations, concepts, categories and, ultimately, meaning (Chomsky, 1991; Jackendoff, 1996; Taylor, 1996; Deane, 1996; Garfield, 1997; Croft, 1998; Sandra, 1998; Cole, 1999 inter alia). 

As a result, toquote Devitt & Sterelny (1999:4), “theoretical and conceptual chaos in the theory of meaning is striking”. The basic binary principle that underlies any computational script for intelligent performance is based on a rigid tertium non datur premise, that is, an assumption that human reasoning and decision-making is always of the kind “either or” and is governed by the laws of logic. Epistemologically, this approach is the cornerstone of traditional analytical philosophy with its ontological distinction between mind and body (Priest, 1991; Schlechtman, 1997; Kim, 1998). This distinction has borne methodological fruit whose relevance, it appears, has not yet been fully comprehended: positing different ontologies for mind and body leads to treating humans as physical entities which serve as vehicles for non-physical (mental) entities. However, these mental entities are housed in thenervous system which is part of the body as a physical entity, and this fact has caused a lot of methodological confusion both among philosophers and linguists. 

As a physical object, a human organism is of interest to us mainly because it is a container for the mind which gives it meaning or signification, but because, presumably, the body and the mind have different ontologies, it remains largely unclear how this signification actually comes about. There is obvious parallelism here between analytical treatment of humans and the concept of sign as it is defined in semiotic, for both are viewed as binary structures incorporating ontologically different constituents: we speak about the body of a sign and its meaning just as we do about humans, analyzing signs into physical entities (for instance, words of natural language as acoustic phenomena) and mental entities (meanings of words). As far as the theory of meaning or linguistic semantics goes, the implication here often is that the body of a linguistic sign is created for the purpose of providing a vehicle for meaning, which leads to an inevitable logical inference that meanings exist before signs. 

If we subscribe to this assumption, we are faced with the problem of defining meaning as a non-physical entity that exists prior to being assigned to a particular physical entity, such as linguistic sign, through which we become aware of its existence. Thus, we find ourselves in a vicious circle. The computational metaphor on which almost all modern theories of cognition are built, is fraught at least with one grave danger of disregarding the problem of emerging signification of signs. Linguistic signs are treated as well-defined binary structures analyzable in terms of form (expression) and content; these structures are routinely used to convey information by making it possible for both the sender (speaker) and receiver (listener) to analyze them following acertain mutually shared procedure into quants of meaning thus extracting semantic values encoded in signs. 

Such analysis, according to the computational theory of cognition and language, consists in a series of decisions sign users have to make in order to process the encoded meanings correctly (these decisions concern encoding on the part of the speaker, and decoding on the part of the listener). I do not claim to have much expertise in artificial intelligence, but it seems to me that the entire concept of AI rests on the premise that, basically, it is possible to develop an algorithmic script that would allow, through application of explicitly formulated logical procedures, to analyze all possible signs into a priori defined sets of values contained in them. No matter how appealing it may seem, such an approach fails to take into account the experiential character of semiosis as a sign generation process. Just in the same manner as mind develops (emerges) simultaneously with the development of the body in the course of its functional interactions with the environment, meaning emerges in the course of an organism’s functionalnteractions with physical entities that constitute this environment. 

It would be wise to remember here that signs in general, and linguistic signs in particular, are epistemologically no different from any other physical entities or phenomena found in an organism’s immediate environment. They may become signs, or they may not, and it all depends on whether in the course of routine encounters with them an organism vests them with signification, which is largely individual rather than social in nature. This significance may become socialized to a high degree as a result of humans’ interactions with particular kinds of entities or phenomena in a perceptually and experientially shared domain, but it will never lose its individual “flavor”. It follows from this that neither the set of all possible signs, nor all possible sets of semantic values can be well and exhaustively defined as long as one major factor has not been brought into the picture — the human experiencer.

It is highly probable that categorized human experience is patterned in a certain organized way predetermined by human biological makeup. However, it would be wishful thinking to believe that all the diverse lifetime experiences which surely cannot be identical to one another, are categorized following a limited well-defined set of categorization patterns, especially in view of the illuminating insights into categorization processes given by the theory of prototypes. This theory casts serious doubts on feasibility of binarism as a fundamental concept in understanding intelligence and how mind works, for this concept precludes the very possibility of considering another option for conceptualizing decision-making as an experience-governed indeterminacy reduction procedure based on an assumption that rather than being “either or”, it may be “both A and B, with C as a possibility”.

The computational idea of thinking and, correspondingly, language is open to criticism. A more comprehensive view of language as a system of signs must also include the human “conceptualizer” and the world as it is experienced by him (Dirven & Verspoor, 1998:14). As soon as such view is accepted, information becomes the product of cognition as a biological function of a living organism (Maturana, 1978), the function of interacting with and adapting to the environment.（essay代写)

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