3.17 Pragmatist Semantics Illustrated

Our linguistic system is analogous to a mathematical simultaneous-equation system. The equations of the system are a constraining context that determines the numerical values of the variables in a solution set for the equation system. If the system is mathematically underdetermined, there is an infinitely large number of numerical solution sets for the system. In pure mathematics this mathematical underdetermination of the equation system can be eliminated and the system can be made uniquely determinate by adding equations until there are just as many variables as there are equations. Then there is only one unique solution set of numerical values for the system.

When applying such a mathematically uniquely determined equation system to reality as in science or engineering, the pure mathematics is made to function as the syntax for a descriptive language, when the numerical values of the descriptive variables are measurements. But the measurement values make the mathematically uniquely determined equation system empirically underdetermined due to measurement errors, which can be reduced indefinitely but never completely eliminated. Then even for a mathematically uniquely determined equation system there is still an infinitely large number of possible valid numerical solution sets falling within even a narrow range of measurement errors.

Analogously the statements consisting of universally quantified statements believed to be true are a constraining context that determines the semantics of the descriptive terms in the belief system. The semantics of the descriptive terms in any semantical “solution set”, as it were, are relativized to one another by the system of universal statements believed to be true. But the semantics acquired from sense stimuli always contains some vagueness. Due to the vagueness the system is empirically underdetermined and admits to an indefinitely large number of relativized semantical sets for the system. Adding more statements to the belief system reduces this empirical underdetermination by adding clarity, but the residual vagueness can never be completely eliminated. Our semantics captures determinate mind-independent reality, but the cognitive capture with our semantics can never be exhaustive. There is always residual vagueness in our semantics. Vagueness and measurement error are both manifestations of empirical underdetermination.

The relativized semantics in turn produces relativized ontology, because ontology is the determinate features of reality that are described by the relativized semantics. Mind-independent reality imposes the empirical constraint on our falsifiable belief systems, while our access to mind-independent reality is by language-dependent relativized semantics. Thus ontology is not absolute and there are no referentially fixed terms. Descriptive terms are always referentially fuzzy, since their semantics always has residual vagueness.

Three notable consequences of the artifactual thesis of relativized semantics are firstly the rejection of the positivist observation-theory dichotomy, secondly the rejection of the positivist thesis of meaning invariance for the descriptive terms in language used for reporting observations, and thirdly the rejection of the positivist analytic-synthetic dichotomy.


3.18 Rejection of the Observation-Theory Dichotomy

One of the motivations for the positivists’ accepting the observation-theory dichotomy is the survival of the ancient belief that science in one respect or another has a permanent, incorrigible and objective foundation. In the positivists’ version of this foundational agenda observational description is presumed to deliver this certitude, while theory language is subject to revision sometimes revolutionary in scope. The positivists were among the last to believe in any such eternal verities.

More than a quarter of a century after Heisenberg said he could observe the electron in the Wilson cloud chamber, philosophers began to reconsider the concept of observation, a concept that had previously seemed prima facie obvious. On the pragmatist view there are no observation terms that receive isolated meanings merely by simple ostension, and there is no distinctive semantics for identifying language used for observational reporting. Instead every descriptive term is embedded in an interconnected system of beliefs, which Quine calls the “web of belief”, some part of which constitutes a relevant context for determining any given descriptive term’s meaning. A unilingual dictionary is a minimal listing of a subset of relevant beliefs for each univocal lexical entry.


3.19 Rejection of Meaning Invariance

When the observation-theory dichotomy is rejected, the language that reports observations becomes subject to semantical change or what Feyerabend called “meaning variance”. The statements of theory contribute meaning parts to the semantics of descriptive language used to report observations, such that a theory revision changes the semantics of the relevant observational description.

The semantics of every descriptive term is determined by the term’s linguistic context consisting of universally quantified statements believed to be true, such that a change in any of those beliefs changes some parts of the constituent terms’ meanings.

In science the linguistic context consisting of universally quantified statements believed to be true may include both theory and test-design statements, which jointly determine the semantics for particularly quantified statements that report observations.


3.20 Rejection of the Analytic-Synthetic Dichotomy

On the positivist view the truth of analytic sentences can be known a priori, i.e., by reflection on the meanings of the constituent descriptive terms, while synthetic sentences require empirical investigation to determine their truth status, such that their truth can only be known a posteriori. Thus to know the truth status of the analytic sentence “All bachelors are unmarried”, it is unnecessary to take a survey of bachelors to determine whether or not any such men are married. However, determining the truth status of the sentence “All ravens are black” requires an empirical investigation of the raven bird population.

On the alternative pragmatist view the semantics of all descriptive terms are contextually determined, such that all universally quantified affirmations believed to be true are analytic statements. But their truth status is not thereby known a priori, because they are also synthetic, i.e., known by experience. This dualism implies that when any universally quantified affirmation is accepted as empirically true, the sentence can be used analytically such that the meaning of its predicate displays a partial analysis of the meaning of its subject term. To express this analytic-empirical dualism Quine used the phrase “analytical hypotheses”, although he was a nominalist and restricted the phrase to translation hypotheses. Such a restriction is unnecessary.

Thus “All ravens are black” is as analytic as “All bachelors are unmarried”. The meaning of “bachelor” includes the idea of being unmarried and makes the phrase “unmarried bachelor” redundant. Similarly so long as one believes that all ravens are in fact black, the meaning of “raven” includes the idea of being black, as evidenced by the fact that the belief makes the phrase “black raven” redundant. In science the reason for belief is often empirical adequacy demonstrated by a nonfalsifying empirical test outcome.

All universally quantified affirmations believed to be true are both analytic and synthetic.


3.21 Semantical Rules

The above discussion leads immediately to the idea of “semantical rules”, a phrase borrowed from Carnap but with a new meaning. In the contemporary pragmatist philosophy semantical rules are statements in the metalinguistic perspective, because they are about language. And their constituent terms are in logical supposition, because the statements are about meanings. Each semantical rule describes part of the descriptive subject term’s meaning complex by exploiting the analytic-synthetic dualism in universally quantified affirmations believed to be true.

For example if it is believed that all ravens are in fact black, then in the metalinguistic perspective the statement “All ravens are black” is a semantical rule describing part of the meaning of the term “raven”, as indicated (to repeat) by the redundancy in the phrase “black raven”. The component parts of a meaning complex in a semantical rule are always understood by the user, because he must have previously understood and believed the universal statement that makes the complex include the component part. Thus the user understands the meaning component “black” in the meaning complex for “raven”, because he had previously understood and accepted the statement “Every raven is black”. Otherwise there is no question of understanding the component, because “black” would not be a component of “raven” for that user.

Hickey had firstly set forth his thesis of componential semantics in 1976 in his Introduction to Metascience: An Information Science Approach to Methodology of Scientific Research.

A semantical rule is a universally quantified affirmation accepted as true and viewed in logical supposition in the metalinguistic perspective, such that the meaning of the predicate term displays some component parts of the meaning of the subject term.


3.22 Componential vs. Wholistic Semantics

Semantical change was vexing to the contemporary pragmatists, when they first accepted the artifactual thesis of the semantics of language. When they rejected a priori analytic truth, many of them mistakenly also rejected analyticity altogether. And when they accepted the contextual determination of meaning, they mistakenly took an indefinitely large context as the elemental unit of language for consideration. This elemental context was typically construed either as consisting of a explicitly stated whole theory with no criteria for individuating theories, or even more inclusively as a “paradigm” consisting of a whole theory together with many associated pre-articulate skills and tacit beliefs. This is the wholistic (or “holistic”) semantical thesis.

On this wholistic view therefore a new theory that succeeds an alternative older one must completely replace the older theory including all its observational semantics and ontology, because its semantics is viewed as an indivisible unit. In his Patterns of Discovery Russell Hanson attempted to explain such wholism in terms of Gestalt psychology. And the historian of science Thomas Kuhn, who wrote a popular monograph titled Structure of Scientific Revolutions, explained the complete replacement of an old theory by a newer one as a “Gestalt switch”. The philosopher of science Paul Feyerabend also tenaciously maintained wholism, but attempted to explain it by his own understanding of Benjamin Lee Whorf’s thesis of linguistic relativity also known as the “Sapir-Whorf hypothesis”. In his Against Method Feyerabend proposes semantic “incommensurability”, which he says is evident when an alternative theory is not recognized to be an alternative. He cites the transition from Newtonian to Einstein’s relativity physics as an example of such incommensurability.

Any wholistic semantical thesis such as notably Feyerabend’s semantic incommensurability thesis creates a pseudo problem for the decidability of empirical testing in science. It implies complete replacement of the semantics of the descriptive terms used for test design and observation. And complete replacement deprives the two alternative theories of any semantical continuity, such that their language cannot even describe the same phenomena or address the same problem. In fact the new theory cannot even be said to be an alternative to the old one, much less a more empirically adequate one. Such empirical undecidability due to alleged semantical wholism would deny the history of science both production and recognition of progress.

But the thesis of componential semantics resolves the wholistic semantical muddle in the linguistic theses proffered by Hanson, Kuhn and Feyerabend. It is not necessary to accept the wholistic view of semantics, because the pragmatists’ rejection of the analytic-synthetic dichotomy with its a priori truth claim need not imply the rejection of analyticity as such. The contextual determination of meaning implies only that the analytic-synthetic dichotomy need be rejected, not analyticity itself.

Therefore when there is a semantical change in the descriptive terms in a system of beliefs due to a revision of some of the beliefs, some component parts of the terms’ complex meanings remain unaffected, while other parts are dropped and new ones are added. For empirical testing in science the component meaning parts that remain unaffected by the change from one theory to a later alternative one include those parts determined in the statements of test design. Therein lies the semantical continuity that enables empirical testing to be decidable.

Thus a revolutionary change in scientific theory, such as the replacement of Newton’s theory of gravitation with Einstein’s, has the effect of changing only part of the semantics of the terms common to both the old and new theories. It leaves the semantics supplied by test design language unaffected, so it was possible for Arthur Eddington to test both Newton’s and Einstein’s theories of gravitation simultaneously with the same celestial photographic observations in his 1919 eclipse test. Thus contrary to Feyerabend there is no semantic incommensurability between these theories. Furthermore there is no historical evidence that the advocates of Einstein’s relativity theory had failed to recognize that Einstein’s theory is an alternative to Newton’s.


3.23 Componential Artifactual Semantics Illustrated

The set of affirmations believed to be true and predicating characteristics universally and univocally of ravens are semantical rules describing component parts of the complex meaning of the term “raven”. But if a field ornithologist captures a red bird specimen that exhibits all the characteristics of a raven except its black color, he must make a decision. He must decide whether he will continue to believe “All ravens are black” and that he holds in his birdcage some kind of red nonraven bird, or whether he will no longer believe “All ravens are black” and that the red bird in his birdcage is a red raven. Thus a semantical decision must be made. Color could be made a criterion for species identification instead of the ability to interbreed, although many other beliefs would also then be affected, an inconvenience that is typically avoided as a disturbing violation of the linguistic preference that Quine calls the principle of “minimum mutilation” of the web of belief.

Use of statements like “All ravens are black” may seem simplistic for science, if not quite bird-brained. But as it happens, a noteworthy revision in the semantics and ontology of birds has occurred recently due to a five-year genetic study launched by the Field Museum of Natural History in Chicago, the results of which were reported in the journal Science in June 2008. An extensive computer analysis of 30,000 pieces of nineteen bird genes revealed that contrary to previously held belief falcons are genetically more closely related to parrots than to hawks, and furthermore that falcons should no longer be classified in the biological order originally named for them. As a result of the new genetic basis for classification, the American Ornithologists Union has revised its official organization of bird species. And the bird watchers’ field guide has also been revised accordingly. Now well-informed bird watchers will classify, conceptualize and observe falcon sightings differently, because some parts of the meaning complex for the term “falcon” have been replaced with others, namely the genetic description.

Our semantical decisions alone neither create, annihilate nor change mind-independent reality. But semantical decisions change our mind-dependent linguistic characterizations of mind-independent reality and thus the ontological realities the semantics reveals.


3.24 Semantic Values

For every descriptive term there are several semantical rules with each one’s predicate describing a component part of the common subject term’s meaning complex. A linguistic system therefore contains elementary components of meaning complexes that are shared by many descriptive terms, but are not uniquely associated with any single term. These may be called “semantic values”. Semantic values describe the most elementary ontological features of the real world that are distinguished by a language at a given point in time, and are the smallest elements in any meaning complex at the given point in time. What the language user’s conventionalized semantics is unable to capture at that time constitutes the empirical underdetermination of the language.

Semantic values are the elemental component parts distributed among the meaning complexes associated with the descriptive terms of a language at a given point in time.


3.25 Univocal and Equivocal Terms

The definitions in a unilingual dictionary function as semantical rules. They are universally quantified logically, and are always presumed to be true. Usually each lexical entry in a dictionary such as the Oxford English Dictionary offers several different meanings for a descriptive term, because terms are routinely equivocal. Even the English language, which has a very large vocabulary, economizes on words by giving them several different meanings, which the fluent English-speaking listener or reader can usually distinguish in context. There is always at least one semantical rule for the meaning complex for each univocal use of a descriptive term, because to be meaningful, the term must be part of the linguistic system of conventional beliefs and eligible for a lexical entry in a dictionary.

A descriptive term’s use is univocal, if no universally quantified negative statement accepted as true can relate any of the predicates in the several universal affirmations functioning as semantical rules for the same subject term. Thus if two semantical rules have the form “Every X is A” and “Every X is B”, and if it is also believed that “No A is B”, then the terms “A” and “B” signify parts of different meanings for the term “X”, and “X” is equivocal. Otherwise “A” and “B” would signify different parts of the one meaning complex associated with the univocal term “X”.

A definition in a unilingual dictionary functions as a semantical rule. But the dictionary definition is only a minimal description of the meaning of a univocal descriptive term, and it is not the whole description. Terms have many semantical rules, when many characteristics apply universally to a given subject. Thus there are multiple predicates that universally characterize ravens, characteristics which are known to the ornithologist, and which may fill a paragraph or more in his ornithological reference book.


3.26 Signification and Supposition

The signification of a descriptive term is its meaning, and terms with two or more alternative significations are equivocal in the sense described immediately above. The concept of supposition enables identifying additional ambiguities that are not due to differences in signification that make equivocations, but instead are due to differences in representing ontology. Univocal terms having the same signification have different supposition, because they describe differences in ontology due to their having different functions in the sentences containing them.

The subject term in the categorical proposition is said to be in “personal” supposition, because it references individual entities, while the predicate term is said to be in “simple” supposition, because the predicate signifies an attribute but does not reference the individual entities having the attribute. For this reason the predicate in the categorical proposition is not logically quantified with any syncategorematic terms such as “all” or “some”. For example in “Every raven is black” the subject term “raven” is in personal supposition, while the predicate “black” is in simple supposition. So too for “No raven is black”.

Unlike semantical rules that describe signification, the supposition of descriptive terms in object language depends only on the role of the terms in a statement containing them and not on the truth of the statement. Thus the suppositions of the subject and predicate terms are the same in the statement “Every raven is orange”, which is believed to be false, as they are in the statement “Every raven is black”, which is believed to be true.

Both personal and simple suppositions are types of “real” supposition, because they are different ways of talking about extralinguistic reality in the object-language perspective. They operate in expressions that are object language and thus describe and reference ontologies as either attributes or the individuals identified by their attributes.

Real supposition is contrasted with “logical” supposition, in which the meaning of the term is referenced in the metalinguistic perspective exclusively as a meaning, i.e., only semantics is referenced and not ontology. The meaning has universality in cognition that it does not have in extralinguistic reality. For example in “Black is a component part of the meaning of raven”, the terms “raven” and “black” in this statement are in logical supposition. Whenever a universally quantified affirmation is used in the metalinguistic perspective as a semantical rule for analysis in the semantical dimension, both the subject and predicate terms are in logical supposition. Similarly to say in explicit metalanguage “’Every raven is black.’ is a semantical rule” to express “Black is a component part of the meaning of raven”, is again to use both “raven” and “black” in logical supposition. Furthermore just to use “Every raven is black” as a semantical rule to exhibit its meaning composition without actually saying it is a semantical rule, is also to use the sentence in the metalinguistic perspective and in logical supposition. The difference between real and logical supposition in such a sentence is not indicated syntactically, and depends on the intent of the writer or speaker. Lexical entries in dictionaries are in the metalinguistic perspective and in logical supposition, because the dictionary’s function is to describe meanings.

In all the above types of supposition the same univocal term has the same signification. But another type of so-called supposition proposed in ancient times is “material supposition”, in which the term is referenced in metalanguage as a linguistic symbol in the syntactical dimension with no reference to a term’s semantics in object language. An example is “’Raven’ is a five-letter word”. In this example “raven” does not refer either to the individual real bird as in real supposition or to the universal concept of it as in logical supposition. Thus material supposition is not supposition properly so called, because the signification is different from the term’s object-language signification in the semantical dimension. It is actually an alternative meaning and thus a type of equivocation.


3.27 Aside on Metaphor

In the last-gasp days of decadent positivism some positivist philosophers invoked the idea of metaphor to explain the semantics of theoretical terms. The theoretical term was the positivist’s favorite hobbyhorse. But the semantics of theories is unproblematic for contemporary pragmatists. In his “Posits and Reality” Quine said that all language is empirically underdetermined, and the only difference between positing microphysical entities (like electrons) and macrophysical enti¬ties (like elephants) is that the statements describing the former are more empirically underdetermined than the latter. Thus contrary to the neopositivists the pragmatists admit no qualitative dichotomy between observation terms and theoretical terms.

As science and technology advance, concepts of microphysical entities like electrons are made less empirically underdetermined, as occurred with the development of the Wilson cloud chamber. While philosophers of science now recognize no need to explain theoretical terms by metaphor or otherwise, metaphor is nevertheless a linguistic phenomenon often involving semantical change and it can be analyzed and explained with componential semantics.

It has been said that metaphors are both true and false. In a speaker's conventional or “literal” linguistic usage the entire meaning complex is associated with the univocal predicate term. But in a speaker's metaphorical linguistic usage only some selected part or parts of the entire meaning complex are associated with the univocal predicate term, and the remaining parts of the meaning complex are intended to be excluded. If the excluded parts were included, then the metaphorical statement would be false. But the speaker implicitly expects the hearer or reader to suspend from consideration the excluded parts of the predicate's conventional semantics, while the speaker or writer uses the component part that he has selected for describing the subject truly.

Consider for example the metaphorical statement “Every man is a wolf.” The selected meaning component associated with “wolf” that is intended to be predicated truly of “man” might describe the wolf’s predatory behaviors, while its fur and tail, which are conventionally associated with “wolf”, are among the excluded meaning components for “wolf” that are not intended to be predicated truly of “man”.

A listener or reader may or may not succeed in understanding the metaphorical predication depending on his ability to select the applicable parts of the predicate's semantics intended by the issuer of the metaphor. But there is nothing arcane or mysterious about metaphors, because they can be explained in literal (i.e., conventional) terms to the uncomprehending listener or reader. To explain the metaphorical predication of a descriptive term to a subject term is to list those affirmations intended to be true of that subject, and which together may substitute for the predicated metaphor, setting forth just those parts of the predicate's meaning that the issuer intends to be applicable.

The explanation may be further elaborated by explicitly listing separately the affirmations that are not viewed as true of the subject, but which are conventionally associated with the predicated term when it is predicated literally. Or these may be stated as universal negations stating what is intended to be excluded from the predicate's meaning complex in the particular metaphorical predication, e.g., “No man has a wolf’s tail.”

A semantical change occurs when the metaphorical predication becomes conventional, and this change to conventionality produces an equivocation. The equivocation consists of two literal meanings, the original one and a new meaning, which is now a dead metaphor. As a dead man is no longer a man, so a dead metaphor is no longer a metaphor. A dead metaphor is a meaning from which the suspended parts in the metaphor have become conventionally excluded to produce a new literal meaning.

A metaphor is a predication to a subject term that includes only selected parts of the meaning complex conventionally associated with the predicate term, so the metaphorical predication is a true statement, while intentionally excluding the remaining parts in the predicate’s meaning complex that would make the metaphorical predication a false statement.


3.28 Clear and Vague Meaning

Terms are either univocal or equivocal, but meanings are more or less clear and vague, such that the greater the clarity, the less the vagueness. Vagueness is empirical underdetermination, and can never be eliminated completely, since our concepts can never grasp any reality exhaustively. But vagueness is reduced by the addition of predicates in both universal affirmations and universal negations accepted as true.

Adding semantical rules increases clarity by elaboration. Thus if the list of universal statements believed to be true are “Every X is A” and “Every X is B”, then clarification by elaboration with respect to a descriptive term “C” consists in adding to the list either the statement “Every X is C” or the statement “No X is C”. Clarity is thereby added by elaborating the meaning of “X”, and vagueness remains to the extent that such clarification is absent

Adding universal statements believed to be true that relate any of the univocal predicates in the semantical rules for the same subject increases clarity by increasing coherence. Thus if the predicate terms “A” and “B” in the semantical rules “Every X is A” and “Every X is B” are related in the statements “Every A is B” or “Every B is A”, then one of the statements in the list can be logically derived from the others. Awareness of the deductive relationship and the consequent display of structure of the meaning complex associated with the term “X” makes the complex meaning of “X” more coherent, because the deductive relation makes it more semantically integrated. Clarity is thereby added by exhibiting semantic structure in a deductive system, and vagueness remains to the extent that such clarification is absent.

These additional universal statements relating the predicates may be negative as well as affirmative. Additional universal negations offer clarification by separating parts thus exhibiting equivocation. Thus if two semantical rules are “Every X is A” and “Every X is B”, and if it is also believed that “No A is B”, then the terms “A” and “B” signify parts of different meanings for the term “X”, and “X” is equivocal. Clarity is thereby added by the negation, and vagueness remains to the extent that such clarification is absent.


3.29 Semantics of Mathematical Language

Both test designs and theories often involve mathematical expressions. Thus the semantics for the descriptive variables common to a test design and a theory may be supplied by mathematical expressions, such that the structure of their meaning complexes is partly mathematical. The semantics-determining statements in test designs for mathematically expressed theories may include mathematical equations, measurement language describing the subject measured, the measurement procedures, the metric units and any employed apparatus and/or instruments.

Some of these statements may resemble Percy Bridgman’s “operational definitions”, because the statements describing the measurement procedures and apparatus contribute meaning to the descriptive term. But as Carnap says contrary to Bridgman, each operational definition does not as such constitute a separate definition for the measured subject, thereby making the term equivocal. Instead descriptions of different measurement procedures contribute different parts to the univocal meaning of the descriptive term, unless the different procedures produce different measurement values, where the differences are greater than the estimated measurement error. Furthermore pragmatists do not accept Bridgman’s naturalistic philosophy of the semantics of language, nor need they accept his nominalism.

The semantics for a descriptive mathematical variable is determined by its context consisting of universally quantified statements and/or mathematical expressions believed to be true.


3.30 Semantical State Descriptions

The above discussions in philosophy of language have tended to focus on descriptive terms such as words and mathematical variables, and then on statements and equations that are the theories and laws constructed with the terms. For computational philosophy of science there is an even larger unit of language, which is the state description for the object-language inputs and outputs of mechanized discovery systems.

In concept an input state description is a listing of the statements or equations of the several currently untested theories addressing the same unsolved problem at a given point in time and functioning as semantical rules. It represents the frontier of research for the specific problem. The state description is a synchronic semantical display and is thus static. The initial state description is the source of inputs to a discovery system, and the terminal state description contains the output from a discovery system run. Each discovery system and both its input and output state descriptions address only one problem identified by the test design, and thus represent only one scientific profession.

In concept a discovery-system design is a generative grammar that produces sentences or equations from terms or variables. Therefore an input state description for a discovery system may be reduced for system input so that the description consists exclusively of descriptive terms or variables drawn from the untested theories without actually listing the statements or equations containing those terms and variables. Furthermore such a reduced input state description may profitably be supplemented with the descriptive terms and variables from previously falsified theories thus making it a cumulative state description, although it still represents available information at a point in time. Descriptive terms salvaged from falsified theories have scrap value consisting of terms that may profitably be recycled through the theory-developmental process.

Since proponents of theories believe that the theories they advocate are true and do not expect them to be falsified, the statements and/or equations constituting the several theories in the state description are semantical rules. Each alternative theory has its distinctive semantics for its constituent descriptive terms. A term shared by several alternative theories is thus partly equivocal, but it is also partly univocal due to the shared test-design statements, which are also semantical rules.

A state description for a scientific profession is a synchronic display of the semantical composition of the meanings of the descriptive terms in a list of the alternative theories functioning as semantical rules and addressing a single problem defined by a common test design.


3.31 Diachronic Comparative-Static Analysis

A diachronic display consists of two chronologically successive state descriptions for the same problem and therefore addressed by the same scientific profession. Since state descriptions consist of semantical rules, changes in meanings through time are exhibited by comparison between the two chronologically separated state descriptions. The comparison is called a comparative-static semantical analysis, which consists of two state descriptions representing two chronologically successive language states sharing a common subset of descriptive terms. In computational philosophy of science the comparative-static semantical analysis is the comparison of a discovery system’s input and output state descriptions. However after the system is run, the output is of principal interest.


3.32 Dynamic Diachronic Analysis

The above discussions have described the synchronic and comparative-static diachronic perspectives. Both are static, because they refer to points in time. The dynamic diachronic metalinguistic analysis on the other hand consists of two state descriptions representing two chronologically successive language states sharing a common subset of descriptive terms, it exhibits a process of linguistic change over a period of time from one language state to a later one.
Such changes in science are the result of two functions in basic research, namely theory development and theory testing. A change of state description into a new one is produced whenever a new theory is proposed or whenever a theory is eliminated by a falsifying test outcome.


3.33 Computational Philosophy of Science

Computational philosophy of science consists of developing computerized discovery systems that simulate noteworthy scientific advances in the history of science. Its practitioners thus proceduralize explicitly the production of theories by replicating the past results of successful scientists, with the ultimate aim of developing new theories in a contemporary science by applying the mechanized procedures to its current state description. The discovery systems created by computational philosophers of science represent dynamic diachronic metalinguistic analyses. They proceduralize the transitional process explicitly with the system’s computer design, in order ultimately to accelerate the advancement of a science by mechanizing the transition. The systems typically include empirical criteria for selecting a subset of the developed theories for output as tested and nonfalsified theories either for use in explanations as laws or for future predictive testing.

In this computer age computational philosophy of science is inevitable. Notwithstanding dismissive obstructionism by latter-day Luddites computational philosophy of science is the future that has arrived. It is destined to achieve ascendancy in twenty-first-century philosophy of science among those who are opportunistic enough to master the necessary system-development skills and the requisite working competence in an empirical science. The variety of competencies may require collaborative interdisciplinary efforts. By the year 2100 the enhanced capacity of computer hardware and the enhanced capacity of the computer systems designs in computational philosophy of science may be expected to transform the practices of basic research in unimaginable ways.

Computational philosophy of science consists of developing computerized discovery systems that simulate noteworthy scientific advances in the history of science, in order to proceduralize explicitly the past achievements of the successful scientists, and then to apply the mechanized procedures to the current state description of a science for the development of new theories that advance the science.


3.34 An Interpretation Issue

There is ambiguity in the literature as to what a state description represents. On the linguistic analysis interpretation the state description represents the language state for a language community constituting a single scientific profession. Computational philosophy of science so interpreted is a technique for a specialized type of linguistic analysis, and is neither a separate philosophy nor a psychologistic agenda. It is compatible with the contemporary pragmatism and is closely related to computational linguistics.

On the cognitive psychology and artificial intelligence interpretations the state description represents the individual scientist’s cognitive state consisting of mental representations. The originator of the cognitive-psychology interpretation is Herbert Simon, one of the founders of artificial intelligence. In his Scientific Discovery: Computational Explorations of the Creative Processes Simon says that he seeks to investigate the psychology of discovery processes, and to provide an empirically tested theory of the information-processing mechanisms that are implicated in that process. He states that an empirical test of the systems as psychological theories of human discovery processes would involve presenting the computer programs and some human subjects with identical problems, and then comparing their behaviors. But Simon admits that his book provides little in the way of detailed comparison with human performance. And in discussions of particular applications involving particular discoveries, he says that in some cases the historical discoveries were actually performed differently than the way that the systems performed the rediscoveries.

The academic philosopher Paul Thagard, who follows Simon’s interpretation, originated the name “computational philosophy of science” in 1988 in his book Computational Philosophy of Science. Hickey admits that it is a more descriptive name than the name “metascience” that he had proposed in the 1970’s. Thagard defines computational philosophy of science as “normative cognitive psychology”. To date the cognitive-psychology systems have successfully replicated developmental episodes in history of science, but the relation of their system designs to systematically observed human cognitive processes is still speculative. On either interpretation, however, the input represents knowledge available for potential future discovery, and the output sets forth the one or usually several new theories, which may be accepted either as laws or as theories subject to predictive testing.
 

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