Mind, Society, and the Growth of Knowledge--论文代写范文精选

认知科学的研究人员,包括心理学家、计算机科学家,和一些哲学家提出的认知解释,知识的增长来自科学家的精神结构和程序。社会科学家提供社会解释,通过社会利益等因素来解释科学的变化。这些解释充分吗?下面的essay代写范文进行详述。

Abstract
Explanations of the growth of scientific knowledge can be characterized in terms of logical, cognitive, and social schemas. But cognitive and social schemas are complementary rather than competitive, and purely social explanations of scientific change are as inadequate as purely cognitive explanations. For example, cognitive explanations of the chemical revolution must be supplemented by and combined with social explanations, and social explanations of the rise of the mechanical world view must be supplemented by and combined with cognitive explanations. Rational appraisal of cognitive and social strategies for improving knowledge should appreciate the interdependence of mind and society.

Explaining Science
Many philosophers, historians, psychologists, and sociologists of science are concerned to explain the development of scientific knowledge. But the kinds of explanations they propose are very diverse. Some philosophers of science prefer logical explanations, in which new scientific knowledge derives logically (inductively or deductively) from previous knowledge. Researchers in cognitive science, including psychologists, computer scientists, and some philosophers, propose cognitive explanations, in which the growth of knowledge derives from the mental structures and procedures of scientists. Finally, sociologists of science offer social explanations, in which factors such as the organization and social interests of scientists are used to explain scientific change.

Are these explanations competitive or complementary? Over the past two decades, since sociologists of knowledge staked claims to what had been the traditional philosophical territory of explaining the growth of scientific knowledge, there has been conflict between proponents of logical and social explanations (see, for example: Barnes, 1985; Bloor 1991; Brown 1984, 1989; Collins 1985). In the meantime, cognitive approaches have emerged with explanatory resources much richer than those available within the logical tradition, but the relation between cognitive and social accounts is rarely specified. Some sociologists are intensely antagonistic toward psychological and computational explanations, even going so far as to propose a ten-year moratorium on cognitive explanations of science (Latour and Woolgar 1986, p. 280). In a similar vein, Downes (1993) attacks what he calls "cognitive individualism" and defends the claim that scientific knowledge is socially produced.

But from a naturalistic perceptive, we can appreciate science as a product of individual minds and as a product of complex social organizations. Not only can we see cognitive and social explanations as providing complementary accounts of different aspects of science, we can look for ways of integrating those explanations, bringing then together in a common approach. Thagard (1993) attempted to integrate the cognitive and the social by comparing scientific communities to systems of intelligent computers. This paper pursues the same goal more generally, by comparing cognitive and social explanation schemas and showing how they can be brought together to form integrated explanation schemas. After describing the structure of explanation schemas and outlining some of the targets of cognitive and social explanations, I present typical schemas for explaining belief change. I then show how integrated schemas can be produced that capture what a unified cognitive/social account of science might look like. To illustrate the unification of approaches, I show how a cognitive account of the chemical revolution can be socially enriched, and how a social account of the early development of science and mathematics can be cognitively enriched. The social categories of Downes (1993) require similar enrichment. Finally, I sketch how a cognitive/social approach offers new perspectives on the question of scientific rationality.

Explanation Schemas
Science is far too complex to be amenable to simple deductive or statistical explanations. But scientific developments can be explained by identifying them as fitting into common patterns of change, a style of explanation that is common in both the natural and social sciences. Consider simple Darwinian explanations of why members of a species have a certain trait, for example why some finches have large beaks. Our knowledge of the laws and historical conditions of evolution is far too sparse to provide a derivation of the trait to be explained, but understanding can nevertheless come by means of a schema such as the following:
Explanation target:
Why does a given species have a particular trait?
Explanatory pattern:
The species has a set of variable traits.
The species experiences environmental pressures.
The pressures favor members of the species that have a particular trait.
So members of the species with that trait will survive and reproduce better than members of the species that lack the trait.
So eventually most members of the species will have the trait.

This structure is obviously an oversimplification of explanations used by evolutionary biologists, but it will serve here to show what I mean by an explanation schema, which consists of specification of a target to be explained and a pattern that provides the explanation. The terms presented in boldface are variables that can be filled in by many different examples. The importance of such schemas for explanation has been discussed (with varying terminology) by various philosophers and cognitive scientists (e.g. Kitcher 1981, 1993; Leake 1992; Schank 1986; Thagard 1988, 1992).
What are the explanation targets in science studies? The most straightforward is belief change, as when we ask why eighteenth century chemists adopted Lavoisier's oxygen theory or why twentieth century geologists accepted plate tectonics. The general explanation target concerns why scientists abandoned their previously held beliefs. But there is much more to the development of science than belief change, for we can ask why conceptual changes took place involving the introduction and reorganization of whole conceptual systems. (See Thagard 1992 for an argument that conceptual change goes beyond belief change.)

Another legitimate explanation target in science studies involves discovery. Why did Antoine Lavoisier discover the oxygen theory in the 1770s? Why did Harry Hess develop the theory of seafloor spreading in the 1950s? While such questions are not open to logical explanations, they are grist for the mills of cognitive and social theorists. Similarly, cognitive and social explanations can be given for why scientists pursue particular scientific research programs. Pursuit is an intermediate stage between the initial discovery or proposal of concepts and beliefs and their eventual becoming accepted. Within that stage, there are many interesting questions to be answered, such as why scientists did particular experiments in particular ways. The rest of this paper will focus on schemas for explaining belief change, but it should not be forgotten that understanding science requires attention to other important explanation targets such as conceptual change, discovery.（essay代写)

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