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3.31 Diachronic Comparative
-Static Analysis

A diachronic comparative-static display consists of two chronologically successive state descriptions containing theory statements for the same problem defined by the same test design and therefore addressed by the same scientific profession.

State descriptions contain statements and equations that operate as semantical rules displaying the meanings of the constituent descriptive terms and variables. Comparison of the statements and equations in two chronologically separated state descriptions containing the same test design for the same profession exhibits semantical changes resulting from the transition.

In computational philosophy of science this comparison is typically a comparison of a discovery system’s originating input and generated output state descriptions of theory statements for purposes of contrast.

3.32 Diachronic Dynamic Analysis

The dynamic diachronic metalinguistic analysis not only consists of two state descriptions representing two chronologically successive language states sharing a common subset of descriptive terms in their common test design, but also describes a process of linguistic change between the two successive state descriptions.

Such transitions in science are the result of two pragmatic 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 is the development of mechanized discovery systems that can explicitly proceduralize and thus mechanize a transition applied to the current state description of a science, in order to develop a new state description containing one or several new and empirically adequate theories.

The discovery systems created by the computational philosopher of science represent diachronic dynamic metalinguistic analyses.  The systems proceduralize developmental transitions explicitly with a mechanized system design, in order to accelerate the advancement of a contemporary state of a science.  Their various procedural system designs are metalinguistic logics for rational reconstructions of scientific discovery.  By applying the system to the vocabulary in the current state description for the science the systems generate new theories. The discovery systems typically include empirical criteria for selecting a subset of the generated theories for output as tested and nonfalsified theories either for further predictive testing or for use as laws in explanations and test designs.

But presently few philosophy professors have the needed competencies to contribute to computational philosophy of science, because few curricula in university philosophy departments even encourage much less actually prepare students for contributing to this new and emerging area in philosophy of science for their necessarily interdisciplinary Ph.D. dissertations.  Among today’s academic philosophers the mediocrities will simply ignore this new area, while the Luddites will shrilly reject it.  Lethargic and/or reactionary academics that dismiss it are fated to spend their careers denying its merits and evading it, as they are inevitably marginalized.  But the exponentially growing capacities of computer hardware and the proliferation of computer-systems designs have already been enhancing the practices of basic-scientific research in many sciences.

Thus in his Extending Ourselves (2004) University of Virginia philosopher of science and cognitive scientist Paul Humphreys reports that computational science for scientific analysis has already far outstripped natural human capabilities and that it currently plays a central rôle in the development of many physical and life sciences. Neither philosophy of science nor the retarded social sciences can escape such developments.  Computational philosophy of science is already achieving ascendancy in twenty-first-century philosophy of science due to those who are opportunistic enough to master both the necessary computer skills and the requisite working competencies in an empirical science.

In the “Introduction” to their Empirical Model Discovery and Theory Evaluation: Automatic Selection Methods in Econometrics (2014) David F. Hendry and Jurgen A. Doornik of Oxford University’s “Program for Economic Modeling at their Institute for New Economic Thinking” write that automatic modeling has “come of age.” Hendry was head of Oxford’s Economics Department from 2001 to 2007, and is presently Director of the Economic Modeling Program at Oxford University’s Martin School.  These authors have developed a mechanized general-search algorithm that they call AUTOMETRICS for determining the equation specifications for econometric models.

Computational philosophy of science is the future that has arrived, even when it is called by other names as practiced by scientists working in their special fields instead of being called “metascience”, “computational philosophy of science” or “artificial intelligence”.  Our twenty-first century perspective shows that computational philosophy of science has indeed “come of age”, as Hendry and Doornik report.

 Artificial intelligence today is producing an institutional change in the sciences and humanities.  In “MIT Creates a College for Artificial Intelligence, Backed by $1 Billion” The New York Times (16 October 2018) reported that the Massachusetts Institute of Technology will create a new college with fifty new faculty positions and many more fellowships for graduate students, in order to integrate artificial intelligence systems into both its humanities and its science curricula. The article quoted L. Rafael Reif, president of MIT as stating that he wanted artificial intelligence to make a university-wide impact and to be used by everyone in every discipline [presumably including philosophy of science].  And the article also quoted Melissa Nobles, dean of MIT’s School of Humanities and Sciences, as stating that the new college will enable the humanities to survive, not by running from the future, but by embracing it.  So, there is hope that the next generation of journal editors with their favorite referees, whose peer-reviewed publications now operate as a refuge for reactionaries, Luddites and hacks, will stop running from the future and belatedly embrace artificial intelligence.

3.34 An Interpretation Issue

There is ambiguity in the literature as to what a state description represents and how the discovery system’s processes are to be interpreted.  The phrase “artificial intelligence” has been used in both interpretations but with slightly different meanings.

On the linguistic analysis interpretation, which is the view taken herein the state description represents the language state for a language community constituting a single scientific profession identified by a test design.  Like the diverse members of a profession, the system produces a diversity of new theories. But no psychological claims are made about intuitive thinking processes. 

Computer discovery systems are generative grammars that generate and test theories.

The computer discovery systems are mechanized generative grammars that construct and test theories.  The system inputs and outputs are both object-language state descriptions.  The instructional code of the computer system is in the metalinguistic perspective, and exhibits diachronic dynamic procedures for theory development. As such the linguistic analysis interpretation is neither a separate philosophy of science nor a psychologistic agenda.  It is compatible with the contemporary pragmatism and its use of generative grammars makes it closely related to computational linguistics.

On the cognitive-psychology interpretation the state description represents a scientist’s cognitive state consisting of mental representations and the discovery system represents the scientist’s cognitive processes. 

Computer discovery systems are psychological hypotheses about intuitive human problem-solving processes.

The originator of the cognitive-psychology interpretation is Simon.  In his Scientific Discovery: Computational Explorations of the Creative Processes (1987) and other works Simon writes 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.  There 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 nothing by way of comparison with human performance. And in discussions of particular applications involving particular historic discoveries, he also admits that in some cases the historical scientists actually performed their discoveries differently than the way the systems performed the rediscoveries.

The academic philosopher Paul Thagard, who also follows Simon’s interpretation, originated the name “computational philosophy of science” in his Computational Philosophy of Science (1988).   Hickey admits that it is more descriptive than the name “metascience” that Hickey had proposed in his Introduction to Metascience a decade earlier.  Thagard defines computational philosophy of science as “normative cognitive psychology”.  His 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 unexamined.  And their outputted theories to date have not yet proposed any new contributions to the current state of any science.

In “A Split in Thinking among Keepers of Artificial Intelligence”(AI)  The New York Times (18 July 1993) reported that scientists attending the annual meeting of the American Association of Artificial Intelligence expressed disagreement about the goals of artificial intelligence.  Some maintained the traditional view that artificial-intelligence systems should be designed to simulate intuitive human intelligence, while others maintained that the phrase “artificial intelligence” is merely a metaphor that has become an impediment, and that AI systems should be designed to exceed the limitations of intuitive human intelligence.

So, is artificial intelligence computerized psychology or computerized linguistics? There is no unanimity. To date the phrase “computational philosophy of science” need not commit one to either interpretation.  Which interpretation prevails in academia will likely depend on which academic department productively takes up the movement.  If the psychologists develop new and useful systems, the psychologistic interpretation will prevail. If the philosophers take it up successfully, their linguistic-analysis interpretation will prevail.

In their “Processes and Constraints in Explanatory Scientific Discovery” in Proceedings of the Thirteenth Annual Meeting of the Cognitive Science Society (2008) Langley and Bridewell, who advocate Simon’s cognitive-psychology interpretation, appear to depart from the cognitive-psychology interpretation. They state that they have not aimed to “mimic” the detailed behavior of human researchers, but that instead their systems address the same tasks as scientists and carry out search through similar problem spaces.  This much might also be said of the linguistic-analysis approach. 

For more about Simon, Langley, and Thagard and about discovery systems and computational philosophy of science readers are referred to BOOK VIII at the free web site or in the e-book Twentieth-Century Philosophy of Science: A History, which is available from most Internet booksellers.


3.35 Ontological Dimension 

Ontology is the aspects of mind-independent reality revealed by relativized semantics. 

Semantics is description of reality; ontology is reality as described by semantics. 

Ontology is the metalinguistic dimension after syntax and semantics, and it presumes both of them.  It is the reality that is signified by semantics.  Semantically interpreted syntax describes ontology most realistically, when the statement is warranted empirically by independently repeated nonfalsifying test outcomes.  Thus in science ontology is more adequately realistic, when described by the semantics of either a scientific law or an observation report having its semantics defined by a law.  The semantics of falsified theories display ontology less realistically due to the falsified theories’ demonstrated less empirical adequacy.

3.36 Metaphysical and Scientific Realism

Metaphysical realism is the thesis that there exists mind-independent reality, which is accessible to and accessed by human cognition.

Few scientists will deny that their explanations describe reality; indeed the belief is integral to their motivation to practice basic research.  Yet traditional philosophers have spilt much wasted ink arguing over realism and its alternatives.  The above statement of metaphysical realism is disarmingly simple. It is simply the affirmation of reality and its accessibility with human knowledge. Most importantly “metaphysical realism” does not mean any characterization of reality like some super ontology that can be described by any transcendental, all-encompassing or (to use Hilary Putnam’s phrase) “God’s-Eye View”.  It is recognition that there exists mind-independent reality responsible for both recalcitrantly falsifying empirical tests and everyday surprises. 

In the section titled “Is There Any Justification for External Realism” in his Mind, Language and Society: Philosophy in the Real World (1995) University of California realist philosopher John R. Searle (1932) refers to metaphysical realism as “external realism”, by which he means that the world exists independently of our representations of it.  He says that realism does not say how things are, but only that there is a way that they are. The way that they are would include Heisenberg’s “potentia” as the quantum theory describes reality with its indeterminacy relations.  The theory describes microphysical reality as being that certain way and not otherwise, such that the theory is testable and falsifiable although not yet falsified.

Searle denies that external realism can be justified, because any attempt at justification presupposes what it attempts to justify.  In other words all arguments for metaphysical realism are circular, because realism must firstly be accepted.  Any attempt to find out about the real world presupposes that there is a way that things are.  He goes on to affirm the picture of science as giving us knowledge of independently existing reality, and that this picture is taken for granted in the sciences.

Similarly in “Scope and Language of Science” in Ways of Paradox (1976) Harvard University realist philosopher Quine writes that we cannot significantly question the reality of the external world or deny that there is evidence of external objects in the testimony of our senses, because to do so is to dissociate the terms “reality” and “evidence” from the very application that originally did most to invest these terms with whatever intelligibility they may have for us.  And to emphasize the primal origin of realism Quine writes that we imbibe this primordial awareness “with our mother’s milk”.  He thus affirms what he calls his “unregenerate realism”.  These statements by Searle, Quine and others of their ilk are not logical arguments or inferences; they are simply affirmations.

And Heidegger too recognized that the problem of the reality of the external world is a pseudo problem.  He notes that while for Kant the scandal of philosophy is that no proof has yet been given of the existence of things outside of us, for Heidegger the scandal is not that this proof has yet to be given, but that any such proof is expected and that it is often attempted. 

Hickey joins these contemporary realist philosophers.  He maintains that metaphysical realism, the thesis that there exists self-evident mind-independent reality accessible to and accessed by cognition, is the “primal prejudice” that cannot be proved or disproved but can only be affirmed or denied. Mind-independent reality is not Kant’s ineffable reality, but rather is the very effable reality revealed by our perspectivist semantics as ontologiesAnd he affirms that the primal prejudice is a correct and universal prejudice, even though there are delusional psychotics and sophistic academics that are in denial. 

Contrary to Descartes and latter-day rationalists, metaphysical realism is neither a conclusion nor an inference nor an extrapolation.  It cannot be proved logically, established by philosophy or science, validated or justified in any discursive manner including figures of speech such as analogy or metaphor. Its self-evident character makes it antecedent to any such discursive judgments by the mind, and therefore fundamentally prejudicial.  Hickey regards misguided pedantics who say otherwise as “closet Cartesians”, because they never admit they are neo-Cartesians. The imposing, intruding, recalcitrant, obdurate otherness of mind-independent reality is immediately self-evident at the dawn of a person’s consciousness; it is the most rudimentary experience.  Dogs and cats, bats and rats, and all the other sentient creatures that have survived Darwinian predatory reality are infra-articulate and nonreflective realists in their apprehensions of their environments.  To dispute realism is to step through the looking glass into Alice’s labyrinth of logomanchy, of metaphysical jabberwocky where as Schopenhauer believed the world is but a dream.  It is to indulge in the philosophers’ hallucinatory escapist narcotic.

Scientific realism is the thesis that a tested and currently nonfalsified theory describes the most empirically adequate, the truest and thus most realistic ontology at the current time.

After stating that the notion of reality independent of language is in our earliest impressions, Quine adds that it is then carried over into science as a matter of course. He writes that realism is the robust state of mind of the scientist, who has never felt any qualms beyond the negotiable uncertainties internal to his science.

N.B. Contrary to Feyerabend the phrase “scientific realism” does not mean scientism, the thesis that only science describes reality.

3.37 Ontological Relativity Defined

When metaphysical realism is joined with relativized semantics, the result is ontological relativity. 

Ontological relativity in science is the thesis that the perspectivist semantics of a theory or law and its constituent descriptive terms describe aspects of mind-independent reality.  

The ontology of any theory or law is as realistic as it is empirically adequate.

Understanding scientific realism requires consideration of ontological relativity.  Ontological relativity is the subordination of ontology to empiricism.  We cannot separate ontology from semantics, because we cannot step outside of our knowledge and compare our knowledge with reality, in order to validate a correspondence. But we can distinguish our semantics from the ontology it reveals, as we do for example, when we distinguish logical and real suppositions respectively in statements.  We describe mind-independent reality with our perspectivist semantics, and ontology is reality as it is thus revealed empirically more or less adequately by our semantics. Our semantics and thus ontologies cannot be exhaustive, but ontologies are more or less adequately realistic, as the semantics is more or less adequately empirical.

Prior to the evolution of contemporary pragmatism philosophers had identified realism as such with one or another particular ontology, which they erroneously viewed as the only ontology on the assumption that there can be only one ontology. Such is the error made by some physicists who believe that they are defending realism, when they defend the “hidden variable” interpretation of quantum theory. Such too is the error in Popper’s proposal for his propensity interpretation of quantum theory.    Similarly contrary to Einstein’s EPR thesis of a single uniform ontology for physics, Aspect, Dalibard and Roger’s findings from their 1982 nonlocality experiments demonstrated entanglement empirically and thus validated the Copenhagen interpretation’s semantics and ontology.

Advancing science has produced revolutionary changes.  And as the advancement of science has produced new theories with new semantics exhibiting new ontologies, some prepragmatist scientists and philosophers found themselves attacking a new theory and defending an old theory, because they had identified realism with the ontology associated with the older falsified theory. As Feyerabend notes in his Against Method, scientists have criticized a new theory using the semantics and ontology of an earlier theory.  Such a perversion of scientific criticism is still common in the social sciences where romantic ontologies are invoked as criteria for criticism.

With ontological relativity realism is no longer uniquely associated with any one particular ontology. The ontological-relativity thesis does not deny metaphysical realism, but depends on it.  It distinguishes the mind-independent plenitude from the ontologies revealed by the perspectivist semantics of more or less empirically adequate beliefs.  Ontological relativity enables admitting change of ontology without resorting to instrumentalism, idealism, phenomenalism, solipsism, any of the several varieties of antirealism, or any other such denial of metaphysical realism. 

Thus ontological relativity solves the modern problem of reconciling conceptual revision in science with metaphysical realism. Ontological relativity enables acknowledging the creative variability of knowledge operative in the relativized semantics and consequently mind-dependent ontologies that are defined in constructed theories, while at the same time acknowledging the regulative discipline of mind-independent reality operative in the empirical constraint in tests with their possibly falsifying outcomes. 

In summary, in contemporary pragmatist philosophy of science metaphysical realism is logically prior to and presumed by all ontologies as the primal prejudice, while the choice of an ontology is based upon the empirically demonstrated adequacy of the theory describing the ontology.  Indulging in futile disputations about metaphysical realism will not enhance achievement of the aims of either science or philosophy of science, nor will dismissing such disputations encumber achieving those aims.  Ontological relativity leaves ontological decisions to the scientist rather than the metaphysician. And the superior empirical adequacy of a new law yields the increased truth of a new law and the increased realism in the ontology that the new law reveals.

3.38 Ontological Relativity Illustrated

There is no semantically interpreted syntax that does not reveal some more or less realistic ontology. 

Since all semantics is relativized, is part of the linguistic system, and ultimately comes from sense stimuli, no semantically interpreted syntax – not even the description of a hallucination – is utterly devoid of ontological significance.

To illustrate ontological relativity consider the semantical decision about white crows mentioned in the above discussion about componential artifactual semantics (See above, Section 3.20 and 3.23).  The decision is ontological as well as semantical.  For the bird watcher who found a white but otherwise crow-looking bird and decides to reject the belief “Every crow is black”, the phrase “white crow” becomes a description for a type of existing birds.  Once that semantical decision is made, white crows suddenly populate many trees in the world, however long ago Darwinian Mother Nature had evolved the observed avian creatures. But if his decision is to persist in believing “Every crow is black”, then there are no white crows in existence, because whatever kind of creature the bird watcher found and that Darwinian Mother Nature had long ago evolved, the white bird is not a crow.  The availability of the choice illustrates the artifactuality of the relativized semantics of language and of the consequently relativized ontology that the relativized semantics reveals about mind-independent reality.

Relativized semantics makes ontology no less relative whether the affirmed entity is an elephant, an electron, or an elf.  Beliefs that enable us routinely to make successful predictions are deemed more empirically adequate and thus more realistic and truer than those less successfully predictive.  And we recognize the reality of the entities, attributes or any other characteristics that enable those routinely successful predicting beliefs.  Thus if positing evil elves conspiring mischievously enabled predicting the collapse of market-price bubbles on Wall Street more accurately and reliably than the postulate of euphoric humans speculating greedily, then we would decide that the ontology of evil elves is as adequately realistic as it was found to be adequately empirical, and we would busy ourselves investigating elves, as we would do with elephants and electrons for successful predictions about elephants and electrons.  On the other hand were our price predictions to fail, then those failures would inform us that our belief in the elves of Wall Street is as empirically inadequate as the discredited belief in the legendary gnomes of Zürich that are reputed to manipulate currency speculations ruinous to the wealth of nations, and we would decide that the ontology of elves is as inadequately realistic, as it was inadequately empirical.

Consider another illustration.  Today we reject an ontology of illnesses due to possessing demons as inadequately realistic, because we do not find ontological claims about possessing demons to be empirically adequate for effective medical practice.  But it could have been like the semantics of “atom”. The semantics and ontology of “atom” have changed greatly since the days of the ancient philosophers Leucippus and Democritus.  The semantics of “atom” has since been revised repeatedly under the regulation of empirical research in physics, as when 1906 Nobel laureate J.J. Thomson discovered that the atom has internal structure, and thus today we still accept a semantics and ontology of atoms. 

Similarly the semantics of “demon” might too have been revised to become as beneficial as the modern meaning of “bacterium”, had empirical testing regulated an evolving semantics and ontology of “demon”.  Both ancient and modern physicians may observe and describe some of the same symptoms for a certain disease in a sick patient and both demons and bacteria are viewed as living agents, thus giving some continuity to the semantics and ontology of “demon” through the ages.  But today’s physicians’ medical understanding, diagnoses and remedies are quite different.  If the semantics and ontology of “demon” had been revised under the regulation of increasing empirical adequacy, then today scientists might materialize (i.e., visualize) demons with microscopes, physicians might write incantations (i.e., prescriptions), and pharmacists might dispense antidemonics (i.e., antibiotics) to exorcise (i.e., to cure) possessed (i.e., infected) sick persons.  But then terms such as “materialize”, “incantation”, “antidemonics”, “exorcise” and “possessed” would also have acquired new semantics in the more empirically adequate modern contexts than those of ancient medical beliefs.  And the descriptive semantics and ontology of “demon” would have been revised to exclude what we now find empirically to be inadequately realistic, such as a demon’s willful malevolence.

This thesis can be found in Quine’s “Two Dogmas of Empiricism” (1952) in his Logical Point of View (1953) even before he came to call it “ontological relativity” sixteen years later.  There he says that physical objects are conceptually imported into the linguistic system as convenient intermedi­aries, as irreducible posits comparable epistemologically to the gods of Homer.  But physical objects are epistemologically superior to other posits including the gods of Homer, because the former have proved to be more effica­cious as a device for working a manageable structure into the flux of experience. And as a realist, he might have added explicitly that experience is experience of something, and that physical objects are more effica­cious than whimsical gods for making correct predictions.

Or consider the tooth-fairy ontology.  In some cultures young children losing their first set of teeth are told that if they place a lost tooth under the pillow at bedtime, an invisible tooth-fairy person having large butterfly wings will exchange the tooth for a coin as they sleep. The boy who does so and routinely finds a coin the next morning, has an empirically warranted belief in the semantics describing an invisible winged person that leaves coins under pillows and is called a “tooth fairy”. This belief is no less empirical than belief in the semantics positing an invisible force (gravitons?) that pulls apples from their trees to the ground and is called “gravity”.  But should the child forget to advise his mother that he placed a recently lost tooth under his pillow, he will rise the next morning to find no coin.  The boy’s situation is complicated, because the concept of tooth fairy is not simply unrealistic; no semantically interpreted syntax is utterly devoid of ontological significance.  In this case the boy has previously seen insects with butterfly wings, and there was definitely someone who swapped coins for the boy’s lost teeth on previous nights. Yet the tooth fairy’s recent nondelivery of a coin has given him reason to be suspicious about the degree of realism in the tooth fairy idea.

Thus like the bird watcher with a white crow-looking bird, the boy has semantical and ontological choices.  He may continue to define “tooth fairy” as a benefactor other than his mother, and reject the tooth-fairy semantics and ontology as inadequately realistic.  Or like the ancient astronomers who concluded that the morning star and the evening star are the same luminary and not stellar ( i.e., the planet Venus), he may revise his semantics of “tooth fairy” to conclude that his mother and the tooth fairy are the same benefactor and not winged.  But later when he publicly calls his mother “tooth fairy”, he will likely be encouraged to revise this semantics of “tooth fairy” again, and to accept the more conventional semantics and ontology that excludes tooth fairies, as modern physicians exclude willfully malevolent demons. This sociology of knowledge and ontology has been insightfully examined by the sociologists of knowledge Peter Berger (1929-2017) and Thomas Luckmann (1927-2016) in The Social Construction of Reality (1966).

Or consider ontological relativity in fictional literature.  “Fictional ontology” is an oxymoron.  But fictional literature resembles metaphor, because its discourse is recognized as having both true and false aspects (See above, Section 3.27). For fictional literature the reader views as true the parts of the text that reveal reality adequately, and the reader excludes as untrue the parts that he views critically and finds to be inadequately realistic.

Readers know that Huckelbery Finn is a fictitious creation of Samuel Clemens (1835-1910), a.k.a. Mark Twain, but they also know that white teenagers with Huck’s racist views existed in early nineteenth-century antebellum Southern United States.   Sympathetic readers, who believe Twain’s portrayal of the slavery ontology, recognize an ontology that is realistic about the injustices of the racist antebellum South. And initially unsympathetic readers who upon reading Twain’s portrayal of Huck’s dawning awareness of fugitive slave Jim’s humanity notwithstanding Huck’s racist upbringing, may thus be led to accept the more realistic ontology of black persons that is without the dehumanizing fallacies of racism.  Ontological relativity enables recognition that such reconceptualization can reveal a more realistic ontology not only in science but in all discourse including even fiction.

Getting back to science, consider the Eddington eclipse test of Einstein’s relativity theory mentioned above in the discussion of componential semantics (See above, Section 3.22).  That historic astronomical test is often said to have “falsified” Newton’s theory.  Yet today the engineers of the U.S. National Aeronautics and Space Administration (NASA) routinely use Newton’s physics to navigate interplanetary rocket flights through our solar system.  Thus it must be said that Newton’s “falsified” theory is not completely false or unrealistic, or neither NASA nor anyone else could ever have used it.  Therefore the Newtonian ontology must be realistic, but it is now known to be less realistic and more empirically underdetermined than the Einsteinian ontology, because the former has been demonstrated to be less empirically adequate. 

3.39 Causality

Cause and effect are ontological categories, which in science can be described by tested and nonfalsified nontruth-functional hypothetical-conditional statements thus having the status of laws.  The nontruth-functional hypothetical-conditional law statement claiming a causal dependency is an empirical universally quantified statement.  It is therefore never proved and is always vulnerable to future falsification.  But ontological relativity means that a statement’s empirical adequacy warrants belief in its ontological claim of causality, even when the relation is stochastic. Nonfalsification does not merely make the statement affirm a Humean constant psychological conjunction.  When in the progress of science an empirically tested causal claim is not empirically falsified, it is made evident thereby that the causality claim is more adequately true and thus more realistic than previously hypothesized.

Tested and nonfalsified correlation indicates causality, until the correlation is later empirically invalidated experimentally or otherwise experientially.

3.40 Ontology of Mathematical Language

In the categorical proposition the logically quantified subject term references individuals and describes the attributes that enable identifying the referenced individuals, while the predicate term describes only attributes without referencing the instantiated individuals manifesting the attributes.  The referenced real entities and their semantically signified real attributes constitute the ontology described by the categorical proposition that is believed to be true due to its experimentally or otherwise experientially demonstrated empirical adequacy. These existential conditions are expressed explicitly by the copula term “is” as in “Every crow is black”.

However, the ontological claim made by the mathematical equation in science is not only about instantiated individuals or their attributes.  The individual instances referenced by the descriptive variables in the empirical mathematical equation are also instances of individual measurement results, which are magnitudes determined by comparison with some standard that are acquired by executing measurement procedures yielding numeric values for the descriptive variables. The individual measurement results are related to the measured reality by nonmathematical language, which includes description of the measured subject, the chosen metric, the measurement procedures, and any employed apparatus, all of which are included in a test design.

Also calculated and predicted values for descriptive variables describing effects in equations with measurement values for other variables describing causal factors, make ontological claims that are tested empirically.  Untested theories make relatively more hypothetical quantitative causal claims.  Tested and nonfalsified empirical equations are quantitative causal laws, unless and until they are eventually falsified.


3.41 Pragmatic Dimension

Pragmatics is the uses or functions of language.  The pragmatics of basic research in science is theory construction and empirical testing, in order to produce laws for explanations and test designs.

Pragmatics is the metalinguistic dimension after syntax, semantics and ontology, and it presupposes all of them.  The regulating pragmatics of basic science is set forth in the statement of the aim of science, namely to create explanations containing scientific laws by development and empirical testing of theories, which are deemed laws when not falsified by the currently most critically empirical test.  Explanations and laws are accomplished science, while theories and tests are work in progress at the frontier of basic research. Understanding the pragmatics of science therefore requires understanding theory development and testing.

3.42 Semantic Definitions of Theory Language

For the extinct neopositivist philosophers the term “theory” referred to universally quantified sentences containing “theoretical terms” that reference unobserved phenomena or entities.

The nineteenth-century positivists such as the physicist Ernst Mach rejected theory, especially the atomic theory of matter in physics, because atoms were deemed unobservable.  These early positivist philosophers’ idea of discovery consisted of induction, which yields empirical generalizations rather than theories containing theoretical terms. 

Later the twentieth-century neopositivists believed that they could validate the meaningfulness of theoretical terms referencing unobserved microphysical particles such as electrons, and thus admit theories as valid science.  For discovery of theories they invoked human creativity but offered no description of the processes of theory creation.

These neopositivists also viewed Newton’s physics as paradigmatic of theoretical science.  They therefore also construed “theory” to mean an axiomatic system, because Kepler’s laws of orbital motion can be derived deductively as theorems from Newton’s inverse-square principle.

For the anachronistic romantic philosophers and romantic social scientists “theory” means language describing intersubjectively experienced mental states such as ideas and motivations.

  Some romantics portray the theory-creation process as consisting firstly of introspection by the theorist upon his own personal intersubjective experiences or imagination.  Then secondly it consists of the theorist imputing his introspectively experienced ideas and motives to the social members under investigation.  The sociologist Max Weber (1864-1920) called this verstehen. When the social scientist can recognize or at least imagine the imputed ideas and motives, then the ideas and motives expressed by his theory are “convincing” to him.

3.43 Pragmatic Definition of Theory Language

Scientific theories are universally quantified language that can be schematized as nontruth-functional conditional statements including mathematical expressions (a.k.a. “models”) that are proposed for empirical testing.

Unlike positivists and romantics pragmatists define theory language pragmatically, i.e., by its function in basic research, instead of syntactically as an axiomatic system or semantically by some distinctive content.  The neopragmatist definition contains the traditional idea that theories are hypotheses, but the reason for their hypothetical status is not due either to the positivist observation-theory dichotomy or to the romantics’ requirement of referencing intersubjective mental states. Theory language is hypothetical because interested scientists agree that in the event of falsification, it is the theory language that is deemed falsified instead of the test-design language. Often theories are deemed to be more hypothetical, because their semantics is believed to be more empirically underdetermined than the test-design language.

Theory is a special function of language – empirical testing – rather than a special type of language.

Scientists decide that proposed theory statements are more likely to be productively revised than presumed test-design statements, if a falsifying test outcome shows that revision is needed.

After a conclusive test outcome, the tested theory is no longer a theory, because the conclusive test makes the theory either a scientific law or falsified discourse.

Pragmatically after a theory is tested, it ceases to be a theory, because it is either scientific law or rejected language, except for the skeptical scientist who can describe further predictive testing.  Designing empirical tests can tax the ingenuity of the most brilliant scientist, and theories may have lives lasting many years due to difficult problems in formulating or implementing decisive test designs.  Or as in a computerized discovery system with an empirical decision procedure, theories may have lives measured in milliseconds.

Romantic social scientists adamantly distinguish theory from “models”.  Many alternative supplemental speculations about motives, which they call “theory”, can be appended to an empirical model that has been tested.  But it is the model that is empirically tested statistically and/or predictively.   Pragmatically the language that is proposed for empirical testing is theory, such that when a model is proposed for testing, the model has the status of theory.

Sometime after initial testing and acceptance, a scientific law may revert to theory status to be tested again.  Centuries after Newton’s law of gravitation had been accepted as scientific law; it was tested in 1919 in the historic Eddington eclipse test of Einstein’s alternative relativity theory.  Thus for a time early in the twentieth century Newton’s theory was pragmatically speaking actually a theory again.

On the pragmatic definition “theory” identifies the transient status of language that is proposed for testing.

On the archival definition “theory” identifies a permanent status of accepted language as in an historical archive.

The term “theory” is ambiguous; archival and pragmatic meanings can be distinguished.  In the archival sense philosophers and scientists still may speak of Newton’s “theory” of gravitation, as is often done herein.  The archival meaning is what in his Patterns of Discovery Hanson calls “completed science” or “catalogue science” as opposed to “research science”.  The archival sense has long-standing usage and will be in circulation for a long time to come. 

The mummifying archival sense is not the meaning needed to understand the research practices and historical progress of basic science.  Research scientists seeking to advance their science using theory in the archival sense instead of the functional concept are misdirected away from advancement of science. They resemble archivists and antiquarians.

Philosophers of science today recognize the pragmatic meaning of “theory”, which describes it as a transitional phase in the history of science.  Pragmatically Newton’s “theory” is now falsified physics in basic science and is no longer proposed for testing, although it is still used by aerospace engineers and others who can exploit its lesser realism and lesser truth.


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NOTE: Pages do not corresponds with the actual pages from the book