Recovering Inquiry: An Epistemological Approach to Argument

Mark Weinstein, Montclair State University

My goal in this paper is to present an alternative to the traditional concern among

argument theorists with particular arguments and dialogical exchanges. The alternative offers an

image of how argumentation about significant issues in science and social policy may be

recovered and their reasonableness ascertained. The core theoretic contribution is an account of

warrant strength in terms of a logically differentiated network of support based on a

metamathematical model of emerging truth (MET), which permits the epistemological basis of

argumentation within inquiry, seen over time, to be understood and assessed (Weinstein, 2013). I

see this as broader and deeper than the usual concern with argument reconstruction, which

focuses on particular arguments presented or engaged in, and is often concerned with unstated

assumptions and other gaps in the argument structure seen in light of formal or informal

standards of argument adequacy, for example, deductive validity, inductive soundness, premise

adequacy and relevance.

I take recovering inquiry to require something that is overlooked in the logical and

dialogical perspectives. For me recovering an argument is bringing forth the reasons that in

retrospect can be seen to be compelling. Recovery, then, is seen by me to require the uncovering

of the supporting epistemological structure of the argument, how the shifting availability of

evidence and theory over time yields the epistemological power of a prevailing point of view.

The key epistemological properties seen in retrospect by recovering the structure of successful

inquiry enable us to look prospectively at ongoing debates, attempting to identify the properties

that support the likelihood of epistemological adequacy in the future.

Recovery in my sense requires that we look at the ongoing argumentation within inquiry

for epistemic power, rather than for rhetorical effectiveness, or logical soundness. We look for

structural properties that point to the power of the warrants of an argument as they come to be

better understood over time The perspective advanced here looks to the long-term epistemic

outcome of an inquiry process, which often includes multiple arguments, reflects alternative

perspectives and includes changes in relevant empirical evidence and theoretic understanding.

The MET enables us to recover the epistemological structures that warrant the acceptance or

rejection of arguments put forward as inquiry progresses.

The MET was developed in response to the apparent epistemological adequacy of

chemistry as a prototype of effective inquiry. It is based on three intuitive epistemological

principles of theory adequacy abstracted from physical science: consilience, that is, the increase

of empirical evidence over time; breadth, the range of phenomena to which a theory increasingly

applies; and depth, the ability of the theory to be reinterpreted in terms of broad ranging and

abstract explanatory theories (theoretic reduction). Successful reductions, for example, the

atomic theory as applied to known chemical processes, increase the level of detail of empirical

generalizations (consilience), as in the enormous increase in detailed understanding of chemical

processes characteristic of modern chemistry. They reach out to new areas to which the theory

can be applied (breadth), for example, the extension of chemical principles to organic substances.

And they offer a unifying explanatory account that shows an increasing field of generalizations

to be interpretable in terms of more abstract principles (depth), for example, the application of

quantum theory to chemical phenomena.

The MET addresses argument in the large, showing how complex disputes in inquiry can

be understood in terms of the strength of warrants seen within a network of support that changes

over time. The construction admits approximate models of theories in light of the prevailing

standards in the field, but requires that models be increasingly adequate, and that sequences of

such models form chains of increasing length. Such progressive model chains (consilience) and

the increase in the number of such chains (breadth) are the hallmark of an epistemologically

effective line of inquiry. Similar constructions reflect theoretic reinterpretations, that when

resulting in progressive sequences of reducing theories, mark an approach as ontologically

significant. Argumentation is adaptive and essentially convergent. Successful inquiry is seen as

large-scale convergence over time. Truth is defined in terms of the maximally successful inquiry.

These key desiderata are reflecting in the formalism in the MET, presented in abbreviated

form in the Technical Appendix, below. The three basic epistemological terms are formally

characterized in MET part I: Consilience: the increase of empirical evidence over time (MET,

1.2). Breadth: the range of phenomena to which a theory increasingly applies (MET, 1.3). Depth:

the ability of the theory to be reinterpreted in terms of broad ranging and abstract explanatory

theories, theoretic reduction) (MET, 2 through 2.4). A dialogical model of warrant strength based

on the MET is part II in the appendix. The relation between MET and truth through ontological

commitment is part III.

The MET was initially applied to the development of the Periodic Table and the

persistence of Prout’s hypothesis in the face of counter-evidence (Weinstein, 2011). The

application of the MET to physical science is relatively non-controversial; more controversial is

its application to other sorts of inquiry. In what follows I will briefly sketch out two applications:

multi-theoretic arguments in response to scientific racism and speculative claims in cognitive

science.

Scientific Racism

The efforts of Franz Boas and his followers to reject the racism endemic after WWI are

well documented (Barkan, 1992). What is salient for the discussion here is the commitment by

Boas and his followers to historical particularism (Harris, 2001, pp. 250ff). This raises deep

problems for the perspective that that MET affords, for the MET is based on a clearly nomothetic

science, physical chemistry, and the notion of warrant strength that is at the core of its

application to argumentation requires just what an ideographic approach to anthropology

eschews.

As Harris and others have indicated, although the focus in anthropology was on rich

descriptions of cultural practices, such descriptions are not immune to a theoretic overlay.

Although Boas focused on culture as the major determinant of human understanding and

behavior those that followed offered theoretic overlays that included Freudianism (Benedict and

Mead), functionalism (Malinowski), structuralism (Levi-Strauss) and materialism (Harris). Each

of these adds support to anti-racism by positing theory-based cross-cultural commonalities that

unify rather than differentiate groups. It is such theoretic accounts that support the relevance of

the rich descriptions that Boas’ approach requires, contributing over-arching theoretic constructs

in terms of which the description can be understood. The wealth of descriptive data sets the

standards for the adequacy of theoretic accounts, supporting or challenging the theory as

increasing detail is brought forward. This is captured by the initial insight that the MET affords,

that theory must is supported by a sequence of models that satisfy the theory or are increasingly

adequate to what the theory implies (MET, 1.2).

It is the perspective of the MET that rich descriptions, however essential in the

understanding of human culture, are preliminary and that the adequacy of anthropological

understanding requires that generalizations by put forward and tested by their ability to warrant

increasingly adequate accounts of the phenomena. Such generalizations determine competing

theoretic perspectives. The MET attempts to offer an indication as to how such competing

perspectives may be evaluated. The view put forward is that generalizations take their strength

from the breadth and depth with which they connect networks of explanatory structures (MET,

1.3). This is evident in the large explanatory frameworks, for example, structuralism and

materialism, which are put forward as an overlay on the accepted generalizations in a field

(Harris, 2001, pp. 634ff). It is not surprising that such large frameworks are the subjects of

debate within anthropology, but if we are not to succumb to relativism, the logical appraisal of

such theoretic frameworks is essential. This will be clearer as we move from anthropology to

biology, where the possibility of reduction to deep explanatory theories becomes possible.

The original biological arguments for distinguishing races reflected both the taxonomical

model that would prove a mainstay of biology and a crude mixture of physical and cultural

attributes that signaled the complexity of the attempt to make sense of human diversity. As the

classification morphed into a hierarchical “chain of being,” analogies were sought with the

physical appearance and behavior of animals, especially supposedly man-like apes (Jordan,

1968). But the fundamental distinction based on skin color remained essential, expanded in later

race theorists to include physical measures of the ratio of body parts that supposedly signal both

aesthetic and functional superiority (Gould, 1981, pp. 127ff). The main focus of continuing

research was the measurement of skulls as an indicator of both innate intelligence and

evolutionary status (Gould, pp. 73ff). The underlying theory was that of polygeny, a proto-

biblical doctrine of the separate creation of the various races championed by Louis Agassiz and

reflected in the work of Samuel Morton (ibid., pp. 42ff) . Morton’s work and the work of Paul

Broca have been criticized by Gould, who identified both the empirical and theoretical failing of

the work (Gould, op. cit.) but even if Gould’s work is challenged as to the details the findings

suffer from clear lack of theoretic connection to intelligence, that is with effective cognitive

functioning (Graves, p. 47). The MET points to the underlying problem. Even if we accept such

measurements, whatever their accuracy, it did not result in a continuing and increasingly

effective research programs in craniometry. That is, it did not result in a progressive model chain

(consilience, MET, 1.2). Moreover it did not result in additional chains of models elaborating the

relationship of craniometry to aspects of psychological functioning (breadth, MET, 1.3). The

work of Broca attempting to extend craniometry to, for example, hierarchies of occupational

status and social class resulted in a dead-end (Gould, pp. 82ff).

The issue of polygeny adds additional interest. If polygeny is correct, whether in its

biblical version or in an evolutionary tree which differentiates the races in terms of distinct

evolutionary history, the biological theory of distinct races is at least possible, and possible

supportive of racist interpretations. But that requires that their be some notion of race that is

sufficiently similar to the socially constructed notion, now determined primarily by self-

identification and the evolutionary model. We will briefly explore this in terms of recent work in

the genetic basis of paleoanthropology, below, but for now suffice it to say that the MET shows

why it is a scientific possibility. The reinterpretation of sets of empirical data under an

overarching theory, reduction (MET, 2 through 2.4) offers a warrant potential enormous power,

for its confirmatory yield is potentially a function of the joint confirmation of all of the more

empirical theories that it reduces. The analogy with chemistry is telling. Seeing the chemistry of

gases, the structure of crystals, the electro-chemical properties of substances, the dynamics of

fluids, the tensile strength of solids and the bio-chemistry of living things as all interpretable in

terms of the underlying structure of molecules and atoms is the basis for the priority of physical

chemistry as a paradigm of truth. The improbability of such a grand unification of disparate

sciences, each with their own history, methodology and evidence attests to its enormous

epistemological power on both intuitive and Bayesian grounds. And so we cannot rule out the

potential of a evolutionary version of polygeny despite the failure of the initial research program

in its name.

Before we return to genetics, a development of the late 20th century, we see what the

MET has to say about the central role of psychometrics as the scientific warrant for maintaining

and engineering racial and social difference, the basis for eugenics and social policies that gave

scientific support for segregated schools, sterilization and ultimately genocide. The basic

apparatus for the psychometric support of eugenics was the availability of intelligence tests

beginning with the work of Alfred Binet (Gould, pp. 146ff). The results of intelligence testing

was related to Mendelian genetics by H. H. Goddard, which supported the program in eugenics

to inhibit the reproduction of mentally defectives (ibid., pp. 163ff) and given additional social

relevance by Lewis Terman and especially by R. M. Yerkes in his testing of army recruits during

World War I. Gould sees Terman to have recanted seeing that “mean differences are too small to

provide any predictive information for individuals” (ibid., p. 192) and sees Yerkes to have made

fundamental methodological and statistical errors (ibid., pp. 199ff) and to have disregarded the

plausible interpretations of his findings as evidence of the radically different social and

educational environment that that characterizes the individuals tested (ibid., pp. 217-222). All of

which can be seen as a failure of the psychometricians to develop progressive model chains. But

there is a deeper criticism that Gould employs in challenging the Mendelian interpretation of the

results of testing. Gould asks, “Could the plethora of causes and phenomena grouped under the

rubric of mental deficiency possibly be ordered usefully on a single scale?” (ibid., p. 159). His

answer is that it could not, seeing “mental retardation, specific learning disabilities caused by

neurological damage, environmental disadvantages, cultural differences” as all plausible

contributors to the score on an intelligence test and so making the hypothesis of a single genetic

cause unreasonable (ibid., pp. 159-160). In terms of the MET, the genetic interpretation of the

testing data is not a useful explanatory model for the phenomena. Cyril Burt and his followers

would beg to differ.

Burt, Charles Spearman, Arthur Jensen and the authors of The Bell Curve (Hernstein &

Murray, 1994) now armed with an array of tests that indicate aspects of cognitive competence

rely on the statistical technique of factor analysis to argue for a univocal notion of intelligence, g,

which reduces the correlations among the various test to one major component, and thus

accounts for the apparent variety of abilities in terms of one unifying, possible genetic,

underlying cause. The argument is complex and relies on technical discussions of factor analysis

and the openness of the technique to alternative constructions (ibid., pp. 214-215) but the deep

issue is the reification of factors. Does the statistical fact, whatever it is, have ontological

consequences? This is the problem of reification, are statistical artifacts real properties of the

existent things that they measure? (ibid., pp. 238-239, pp. 250-252; pp. 268-269). Does the

statistical fact, whatever it is, have ontological consequences?

The MET offers a perspective on that issue. The MET gives an account of ontological

commitment internal to a scientific theory (Weinstein, 2002). The technical details are in the

Technical Appendix, part III, but the upshot of the formalism is that we commit ourselves to an

ontology in terms of the domain of the intended model of our most successful theories, where

that commitment is captured by the Quinean aphorism, to be is to be the value of a variable.

Thus, factor analysis can tell us what our theories must account for, that is if g is supported by

the statistical evidence, then an explanatory theory of what g is must be forthcoming. If, for

example, we think human cognitive capacity is a function of the central nervous system the

neurophysiological correlate for g must be discovered. If, in addition, we think the

neurophysiological correlate is genetic, as opposed to the development of the brain under the

impress of environmental stimulation, the underlying genetic structure must be identified. Thus

factor analytic results, not matter how reconstructed, only have ontological significance when

they are cashed out in a theory of increasing empirical adequacy (MET, 1.2) and breadth of

application (MET, 1.3, 2.3) in the best case a theory whose breadth enables it to incorporate and

reinterpret the range of empirical models and explanatory theories in its own terms (MET, 2.4).

The perspective on scientific racism the MET affords is, however, equivocal, for a theory

of racial differences can be seen as supported by a genetic account of human diversity based on

recent work in paleoanthropology (Wade, 2006). Modern genetics is among the broadest and

deepest scientific theories available outside of the physical chemistry, making the contribution to

traditional evolutionary biology that led to the grand synthesis that is modern evolutionary

theory. Genetics satisfies the desiderata of consilience, breadth and depth, and its depth is

profound, furnishing the bridge between biology and physical chemistry. But whatever the

theoretic warrant of the work of paleoanthropologists, concerns with the application of a genetic

based racial theory face the charge of racism, which arise due to socially sensitive social

applications of modern genetics to medicine and criminal justice (Krimsky & Sloan, 2011).

Nevertheless, tracing the genetic variation of human populations subsequent to the migration

from Africa distinguishes groups of people in a fashion that reflects, to some extent, the

traditional division of humans into races. For example the ‘chromosomal tree’ based on the Y

chromosome, passed from father to son, includes the mutation M173 that distinguish populations

in Europe from those that populate the Americas, characterized by M242 as distinguished from

the inhabitants of West Eurasia with M170 and have the parent population in Africa

characterized by M168. This is reflected in the distribution of mutations based on mitochondrial

DNA passed along the female line that include distinct lineages that are geographically

differentiated, albeit in complex ways (Wade, 2006, pp. 56ff).

Genetic theories are powerful potential reducers. They track evidence as diverse as

migrations identified archeologically through settlement ruins, the persistence of tool making

cultures, the dispersion of language families and patterns of resistance to disease. Genetic

theories sit in deep and broad reduction chains. Genetic claims are supported by chemical

analysis and are consistent with known principles of biology and physiology and so fit within a

detailed and comprehensive inquiry project that accommodates a wide range of explanatory

structures independent of their application to the biology of race. But even if the science of

genetics is strongly supported by the theories that surround it, the question still remains as to

whether it is a strong reducing theory in respect of its application to explaining human

differences relevant to notions of race.

The question is whether race as genetically defined explains race as socially constructed,

based on self-attribution in light of traditional racial categories. The first thing to notice is that

race is socially constructed in various ways, particularly in countries in the Western Hemisphere

with a long history of racial mixing. People descended from two different racial classifications

can be grouped in two ways, hypodescent, where the designated race has lower status, as when a

bi-racial individual of African descent is designated as African-American or hyperdescent, which

designates according to the higher status racial designation, common in Brazil (Krinsky and

Sloan, 2011, pp. 246ff). This, in itself, makes it unreasonable to expect genetics based racial

theory to fit the traditional categories of race. The social construction of race is not a coherent

categorical system; it reflects different social histories and encompasses competing distinctions,

including physical characteristics, language use, religion and ethnicity.

Racial groups can, however, be differentiated by genetic mutations, tracing both male and

female lines, which have geographic distributions that reflect socially constructed racial

distinctions to some extent. An interesting case concerns recent attempts to identify genetic

markers for racially targeted and effective medical interventions. Reliance on racial distinctions

in such contexts becomes more supportable and more capable of resisting social and moral

complaints about their possible misuse. Policy is a negotiation between fact and value, but we do

this at our peril unless we get the facts right. The MET addresses the scientific basis by focusing

on the large-scale structures that warrant the empirical evidence. This is also evident in the

perspective it affords on understanding developing inquiry projects such as cognitive science.

Cognitive Science

Cognitive science, like the chemistry of Dalton, begins with deep theoretic concepts that

serve as potential reducing theories for newly acquired, but relatively impoverished, empirical

data. This is captured in the MET by admitting increasingly adequate approximation relations

among the models rather than requiring exactitude (consilience rather than validity). From the

perspective of the MET it is not surprising that theories are inadequate to their models in many

ways, and that the debates among proponents of competing points of view may remain

unresolved as inquiry progresses. Early chemistry included theoretical constructs that were

inadequate to the phenomena. But the descriptions of the phenomena reflected both empirical

and conceptual flaws (Weinstein, 2011). So, for example, data sets for the relative proportions of

chemical components were subject to the vagaries of inadequate measurement (Scerri, 2007, p.

40). And even as measurements improved, empirical models of chemical reactions could not

possibly be given an adequate theoretical account until the discovery of isotopes (Scerri, 2007, p.

58). When applied to physical chemistry, the MET looks to the developing of the network of

ideas over time and the interplay of empirical evidence and theoretic modeling. This exposes an

essential aspect of inquiry that illuminates the potential of speculations within cognitive science.

Cognitive science exhibits enormous potential breadth and depth. It looks at the wide

range of human cognitive activities and draws its substance from two powerful sources, the

natural sciences that support neurophysiology and the logical basis of computer science. Natural

science increases the evidentiary weight of cognitive science proposals to the extent that they can

be connected to well-established theories, ranging from anatomy to physics. The roots of

cognitive science in logic and computer science offers a level of mathematical construction that

differentiates as needed by particular fields in inquiry. The MET is neutral in terms of the details.

All the MET requires is that there be a comparative assessment of models over time, that

sequences of models are progressive, increasingly adequate to the phenomena over time

(consilience, MET 1.2).

Breadth of concern is perhaps the most apparent characteristic of cognitive science. The

Cambridge Handbook of Cognitive Science lists 8 related research areas that reflect different

aspects of human cognition, standardly construed, and extends the reach of cognitive science to

include animal cognition, socially mediated cognition, evolutionary psychology and, most

essential, the bridge between cognitive science and the rest of physical science, cognitive

neuroscience (Frankish and Ramsey, 2012). Each of these is a going concern, and none of them

is free of difficulties. Yet in all cases there is a sense of advance, of wider and more thoughtful

articulation of theoretical perspectives that address a growing range of concerns. The MET (1.3)

offers a logical account of why breadth is a telling epistemological attribute, crucial for

evaluating the structure of support that warrants confidence in the value of the enterprise and its

ultimate vindication as ontologically significant (MET, part III).

The study of memory serves as an indication of the progressive nature of cognitive

science. The cognitive architecture of memory, the discussion between short and long-term

memory has been understood for some time. With the additional concept of working memory the

model for understanding memory encoding and retrieval was in place. Elaboration and

controversies still abound, but the basic physiological structures though which memory can be

physically impaired have been identified. Additional details and functional analyses have been

postulated, for example the distinction between declarative and episodic memory and the

relationship between recollection and familiarity has been explored both experimentally and

physiologically. More adequate knowledge of brain anatomy connects different levels of

analysis. Such studies include accounts of cognitive deficits as a function of physical

deformation of the brain, as well as explanations of successful cognition in terms of underlying

brain mechanisms. For example, fMRI studies offer detailed accounts of visual memories in

terms of neurophysiological descriptions of the visual cortical areas (Ranganath et. al., 2012). In

terms of the MET, increasingly adequate empirical models of memory (consilience, MET 1.2)

form related sequences of models (breadth, MET 1.3), which reinterpret cognitive processes in

terms of higher-order neurological models (depth, MET, 2).

The MET offers a different perspective on research on reasoning and decision making.

There are a variety of models for understanding reasoning and decision making derived from

empirical and behavioral studies, expanding upon the logic derived paradigms familiar from the

work of Wason and Johnson-Laird (1972), Nisbett and Ross (1980) and others (see Oaksford et.

al., 2012). In contrast to this empirical work, speculative efforts look beyond logic to broader

considerations, offering possibilities of deeper understanding than normative-based empirical

paradigms can afford. Damasio (1995) has resuscitated the connection between reasoning and

emotion and Thagard & Aubie, (2008) see a connection between cognition, emotions and levels

of awareness. If such complex understanding can be connected with underlying structural and

functional models of the brain there is the possibility of significant progress beyond more simple

logic-based models. At the present, such efforts rely on computer simulations using virtual

neurons in the absence of detailed knowledge of the brain. But advances in the understanding of

the brain’s structure and function offer the possibility of deep reductions that have ontological

significance. This explains the pervasive interest in cognitive science as a materialist theory of

mind despite philosophical objections to the contrary. The MET enables us to for the details.

Thagard and Aubie draw upon both neurophysiology and computer modeling. This

enables both theoretic breadth (MET, 1.3) and the possibility of increasing adequacy (MET, 1.2),

even if the latter is no more that computer simulations of simplified cognitive tasks. They cite

ANDREA, a model which “involves the interaction of at least seven major brain areas that

contribute to evaluation of potential actions: the amygdala, orbitofrontal cortex, anterior

cingulate cortex, dorsolateral pre-frontal cortex, the ventral striatum, midbrain dopaminergic

neurons, and serotonergic neurons centered in the dorsal raphe nucleus of the brainstem”

(Thagard and Aubie, 2008, p. 815). With ANDREA as the empirical basis, they construct

EMOCON, which models emotional appraisals, based on a model of explanatory coherence, in

terms of 5 key dimensions that determine responses: valance, intensity, change, integration and

differentiation (pp. 816ff). EMOCON employs parallel constraint satisfaction based on a

program, NECO, which provide elements needed to construct systems of artificial neural

populations that can perform complex functions (p. 824ff. see pp. 831 ff. for the mathematical

details). This points to the potential power of their approach. Computer models, even if gross

simplifications, permit of ramping up (MET 2.1). A logical basis with a clear mathematical

articulation has enormous potential descriptive power as evidenced by the history of physical

science (MET 1.3).

Damasio (2010) has a similarly ambitious program. He begins with the brain’s ability to

monitor primordial states of the body, for example, the presence of chemical molecules

(interoceptive), physiological awareness, such as the position of the limbs (proprioceptive), and

the external world based on perceptual input (extroceptive). He construes this as the ability to

construct maps and connects these functions with areas of the brain based on current research

(pp. 74ff.). This becomes the basis for his association of maps with images defined in neural

terms, which will ground his theory of the conscious brain.

Given that much he gives an account of emotions elaborating on his earlier work, but

now connecting emotions with perceived feelings. As with the association of maps and images,

Damasio associates emotions with feeling and offers the following account: “Feeling of emotions

are composite perceptions of (1) a particular state of the body, during actual or simulated

emotion, and (2) a state of altered cognitive resources and the deployment of certain mental

scripts” (p. 124). As before he draws upon available knowledge of the physiology of emotional

states but the purpose of the discussion is not an account of emotions per se, but rather to ground

the discussion of memory, which becomes the core of his attempt at a cognitive architecture (pp.

339ff.). The main task is to construct a system of information transfer within the brain and from

the body the brain. The model is, again, mediated by available physiological fact and theory

about brain function and structure and so permits a broad range of models (MET, 1.3). The main

theoretic construct in his discussion of memory is the postulation of ‘convergence-divergence

zones’ (CDZs), which store ‘mental scripts’ (pp. 151ff.). Mental scripts are the basis of the core

notion of stored ‘dispositions,’ which he construes as ‘know-how’ that enables the

‘reconstruction of explicit representation when they are needed” (p. 150). Like maps (images)

and emotions (feelings) memory requires the ability of parts of the brain to store procedures that

reactivate prior internal states when triggered by other parts of the brain or states of the body.

Dispositions, unlike images and feelings are unconscious, ‘abstract records of potentialities’ (p.

154) that enable retrieval of prior images, feelings and words through a process of reconstruction

based in CDZs, what he calls ‘time-locked retroactivation’ (p. 155). CDZs form feedforward

loops with, e.g. sensory information and feedback to the place of origination in accordance with

coordinated input from other CDZs via convergence-divergence regions (CDRegions) by

analogy with airport hubs (pp. 154ff.). Damasio indicates empirical evidence in primate brains

for such regions and zones (p. 155) and offers examples of how the architecture works in

understanding visual imagery and recall (pp. 158ff.), again offering a potentially broad range of

models (MET, 1.3) each of which can, in principle, offer the possibility of increasing articulation

over time (MET, 1.2).

The result of all of this is an attempt, as the title of the book suggests, to construct a

brain-based theory of self, which building on what he has developed so far distinguishes three

stages, the proto-self “a neural description of relatively stable aspects of the organism....

spontaneous feeling of the living body,” the core self, “which connects the body to the external

world through “ a narrative sequence of images, some of which are feelings” and an

autobiographical self “when objects in one’s biography generate pulses of the core self that are,

subsequently, momentarily linked in a large-scale coherent pattern” (p. 192).

Damasio like Thagard and Aubie offer speculative models that reference current

physiological knowledge, rely on concepts from computer science and information theory and

bypass the deep philosophical issues that are seen by many to create an unbridgeable gap

between the mental and the physical short of deep metaphysical reorientation (Chalmers, 1996).

Yet, whatever the ultimate verdict on these two authors, the rich program in cognitive science

persists and has a strong appeal. The reason is the potential strength of the warrants, that is to

say, if such models prove to be correct the epistemic force of the warrants that support them will

be enormous, swamping the force of alternative approaches that rely on, for example,

psychological evidence alone. This requires a more careful look at the perspective that the MET

provides.

The MET determines a hierarchy of epistemic adequacy in terms of models and chains of

models viewed over time. (MET, 1-1.3) Each level of adequacy supports correlative levels of

warrant strength (MET, part II). The level of warrant strength has consequences both for the

acceptance of the theory and for its power to resist counterexamples (see Weinstein, 2013,

chapter 4 for the dialectical details and a related adaptive logic.). For a theory to have sufficient

warrant to be taken seriously it must reflect its intended models in that it either holds in the

models MET, 1.1, a) or is increasingly adequate to the evidence it strives to explain (MET, 1.1,

b). But the models in which it holds, whether exactly or with better approximations over time are

frequently a small set of the available concerns potentially within the scope of the theory.

Looking at the history of the periodic table we find a similar pattern. Theoretic models held for

small subsets of the known chemical elements and theoretic approximations to empirical data

were typical. But as the research program persisted more and more chemicals were brought

under the scope of explanatory models and approximations of empirical data improved as both

theoretical and the experimental understanding was refined.

Given the claims of both Thagard and Aubie and Damasio to base their models on

accepted facts about brain function, if proved correct, the accounts, however speculative meet the

first test and so are warranted at a minimal level. That is their views capture aspects of the brain

or they approximate accepted knowledge to a degree that is close enough to merit consideration.

If they are close enough approximations, we look to their progress as they refine their models

and as knowledge of brain function increases. If the approximations are, in general, progressive

as defined in the MET the speculations are seen as increasingly adequate. Adequacy in light of

neurological facts is compelling and increasing adequacy is a sign of the fecundity of the

theoretic approach as chains of linked models progress (MET, 1.2).

Cognitive scientists who connect cognition with other brain functions, that like cognition,

require and mediate information across systems (for example, physiological control and

emotions) add empirically relevant models of essential brain functions, so the theory is not

merely more adequate to its models, but there is an increasing range of models to which it

applies (MET, 1.3). Again this is typical of the history of the periodic table and was a predictor

of its potential strength as the research program flourished.

Both Thagard and Aubie and Damasio take synoptic approaches and offer models which

cross the boundaries of brain functions, offering generalizable schemes for neural architecture.

This shows enormous potential for breadth. The far-ranging interests of cognitive science lend

prima facie force to any reasonable attempt at articulating a neurophysiological account of core

cognitive functions that might account for increasing aspects of the field. The wide range of

empirical and theoretic studies characteristic of the field points to enormous potential breadth for

anybody who gets it right, mirroring the history of the periodic table. Physical chemistry was

initially concerned with gases; over time, independent areas of studies, ultimately including the

entire range of physical substances, were incorporated under the basic concept of periodicity, as

the basic ideas were reorganized around theoretic advance and more adequate empirical

evidence. The result is a massive unification of the entire field of physical chemistry, arguable

the most successful inquiry project in human history. Whatever the challenges, the epistemic

payoff of a correct cognitive science is enormous, whence the power of the field despite its many

problems

Tying cognitive science to neurophysiology gives an evolving empirical basis with

warrants tied to the underlying structures of physiology. Physiological understanding is

increasingly grounded in foundational sciences such as biochemistry and electro-chemistry. The

empirical basis is necessary but it is the foundational knowledge that ultimately has the more

powerful evidentiary force. Reducing neuroanatomy to a functional neurophysiology is the

pathway to physicalism. Claims within physical science have the most powerful warrants,

supported by networks of evidence at the highest level of articulation and affording enormous

explanatory depth (MET, part II). Speculative talk about c-fibers reflecting what little was

known about the physical correlates for mental episodes (in this case pain) was deemed worthy

of decades of philosophical discussion just because the possibility of reducing the mental to the

array of physical knowledge grounded the mental firmly within the scientific worldview

(Hardcastle, 1997). The MET attempts to capture this in the model of reduction (MET, 2-2.4).

But, unlike much of the discussion of the mind-body problem, which was concerned with

identity, the MET sees reduction through identification. The reduction relation in the MET does

not seek identities, but rather tracks the growing identification of one theory by the replacement

of models, that is it offers reinterpretations of aspects of theories when appropriate model

relations hold (MET, 2). But what is most important is the history of reductions, which using the

model of physical science is often partial and approximate. As we can reinterpret more and more

phenomena in terms of a more basic theory our confidence in the warrants that result increases,

first as a function of the adequacy of the reduction, then the increasing depth of the reduction

(MET, 2.1), the increase in theoretic adequacy in light of the reduction (MET, 2.2), the increases

in theoretical reach as the various reductions mutually reinforcement refinement in theory in

light of symmetries between the various theories in light of the over-arching reducing theory

(MET, 2.3) and finally the increase in scope across large areas of inquiry as the reducing theory

captures networks of theories (MET, 2.4). It is on the basis of such a history of progress that

ontological claims are warranted (MET, part III) and is the basis for the view that scientific

materialism is the most plausible candidate for what the world is really made of.

5. CONCLUSION

If cognitive scientists are successful in modeling cognitive behavior in terms of brain

processes, and if, as is becoming more evident, a wide range of psychological processes are

implicated in cognition, possible co-extensive with the range of phenomena identified with so

called folk psychology, the possibility of a scientific basis for the mind becomes more than

philosophical speculation. Whether cognitive scientists will succeed remains to be seen. Whether

a grounding of the mental in the physical will satisfy philosophers is even more uncertain,

especially as phenomenology becomes a favored perspective among philosophers. But short of a

wholesale disregard of science, perhaps in the name of some heir of post-modernism, cognitive

science has a potential for epistemic adequacy that transcends the arguments that support

particular claims. It is this last point that indicates the importance of the perspective the MET

affords to the theory of argument.

The MET enables the epistemic structure that supports the potential strength of warrants

to be seen and in doing so indicates a perspective that looks at the large epistemological

structures that give the ultimate strength to ongoing inquiry. Elsewhere I have speculated that the

approach of the MET has relevance beyond science to political, legal and ethical argument

(Weinstein, 2009b, 2013. chapter 5). It seems apparent to me that a number of essential social

and political concerns could benefit from seeing arguments as networks of reinforcing points of

view, networks that give differential support as a function of the breadth and depth of the

warrants that they contain. My attempt here to offer and analysis of the complex arguments

brought forward against the scientific arguments for racism common until WWII is one such

attempt. Arguments concerning global warming seem another obvious arena for my approach.

Sorting out the epistemic force of the scientific, economic and environmental warrants that

characterize competing points of view seems essential if we are to understand the issues and

develop coherent policies.

Whether argument theorists will take my proposals seriously remains to be seen. The

formalism of my approach need not be a barrier. The metamathematics gives formal substance to

the basic concepts, but it can be seen as formal metaphor for the three essential and hopefully

intuitive epistemological desiderata: consilience breadth and depth. But with or without the

formalism, my approach requires a repositioning of the theory of argument. Arguments, on my

view, are not limited to games with winners and losers or even to attempts at persuasion. Rather

they are seen as the ongoing rational process of clarifying essential issues. Such attempts

whether in scientific inquiry or in social policy transcend particular argumentative exchanges and

project backward onto the available evidence and project forward as additional evidence

accumulates and positions are revised. The MET shows how such a network can be envisioned

and how complex substantive arguments can the understood.

TECHNICAL APPENDIX

The Model of Emerging Truth (MET)

Part I:

1. A scientific structure, TT = T, FF, RR (physical chemistry is the paradigmatic example) where

T is a set of sentences that constitute the linguistic statement of TT closed under some

appropriate consequence relation and where FF is a set of functions F, such that for each F in FF,

there is a map f in F, such that f(T) = m, for some model or near model of T. And where RR is a

field of sets of representing functions, R, such that for all R in RR and every r in R, there is some

theory T* and r represents T in T*, in respect of some subset of T.

A scientific structure is first of all, a set of nomic generalizations, the theoretic commitments of

the members of the field in respect of a given body of inquiry. We then include distinguishable

sets of possible models (or appropriately approximate models) and a set of reducing theories (or

near reducers). What we will be interested in is a realization of TT, that is to say a triple T, F,

R where F and R represent choices from FF and RR, respectively. What we look at is the history

of realizations, that is, an ordered n-tuple: T,F1,R1,...,T,Fn,Rn ordered in time. The claim is

that the adequacy of TT as a scientific structure is a complex function of the set of realizations.

1.1. Let T be a subtheory of T in the sense that T is the restriction of the relational symbols

of T to some sub-set of these. Let f be subset of some f in F, in some realization of TT. Let

T1,...,Tn be an ordered n-tuple such that for each i,j (i<j,) Ti reflects a subset of T modeled

under some f at some time earlier than Tj. We say the T is model progressive under f iff:

a) Tk is identical to T for all indices k, or

b) the ordered n-tuple T1,...,Tn is well ordered in time by the subset relation. That is to say, for

each Ti, Tj in T1,…Tn (ij2), if Ti is earlier in time than Tj, Ti is a proper subset of Tj.

1.2. We define a model chain C, for theory, T, as an ordered n-tuple m1,...,mn, such that for each

mi in the chain mi = di, fi, for some domain di, and assignment function fi, and where for each di

and dj in any mi, di = dj; and where for each i and j (ij), mi is an earlier realization (in time) of T

then mj.

Let M be an intended model of T, making sure that f(T) = M for some f in F ( for some

realization T, F, R and T is model progressive under f. We then say that C is a progressive

model chain iff:

a) for every mi in C, mi is isomorphic to M, or

b) there is an ordering of models in C such that for most pairs mi, mj (j i) in C, mj is a nearer

isomorph to M than mi.

This last condition is an idealization, as are all similar conditions that follow. We cannot assume

that all theoretic advances are progressive. Frequently, theories move backwards without being,

thereby, rejected. We are looking for a preponderance of evidence or where possible, a statistic.

Nor can we define this a priori. What counts as an advance is a judgment in respect of a

particular enterprise over time best made pragmatically by members of the field. We are engaged

in rational reconstruction where logically clarity trumps descriptive adequacy, in presentation,

but where descriptive adequacy is still at the heart of the intuition.

1.3. Let C1,...,Cn be a well ordering of the progressive model chains of TT, such that for all i,j

(i > j), Ci is a later model chain than Cj. TT is model chain progressive iff C1,...,Cn is well

ordered in time by the subset relation. That is to say each later model includes and extends the

models antecedent to it in time.

2. We now turn out attention to the members of some R in RR. The members of RR represent T in

T* in respect of some subset of T, k(T). Let k1(T),...,kn(T) be an n-tuple of representations of T

over time, that is, if

i > j, then ki(T) is a representation of T in T* at a time later that kj(T). We say that TT is

reduction progressive iff,

a) k(T) is identical to Con(T) for all indices, or

b) the n-tuple is well ordered by the subset relation.

2.1. We call an n-tuple of theories RC = T1,...,Tn a reduction chain, and T1,...,Tn a deeper

reduction chain than j-tuple T1,...,Tj, iff n>j and for all i,j there is a ri in Ri such that ri

represents Ti in Ti+1 and similarly for Ti and further for all Tk (k< j) Tk is identical in both

chains Note, the index i must be different from the index j, since if i=j, there is no Ti+1.

2.2. We call a theory reduction chain progressive iff T iff for an n-tuple of reduction chains RC1,...,

RCn and for each RCi (i<n), RCi+1 is a deeper reduction chain than Rci.

2.3. T is a branching reducer iff there is a pair (at least) T and T* such that there is some r and r*

in R’ and R*, respectively, such that r represents T in T and r* represents T* in T and neither T

is represented in T* nor conversely.

2.3.1. B = TT1,TT2,...,TTn = T1, F1, R1,T2, F2,R2,...,Tn, Fn, Rn is a reduction branch of TT1 iff

T1 is a branching reducer in respect of Ti, and Tj (i 2; j 3 for i,j n)

2.4. We say that a branching reducer , T is a progressively branching reducer iff the n-tuple of

reduction branches B1,...,Bn is well ordered in time by the subset relation, that is, for each pair

i,j (i>j) Bi is a later branch than Bj, that is, the number of branching reducers has been increasing

in breadth as inquiry persists.

Part II:

The core construction is where a theory T is confronted with a counterexample, a specific model

of a data set inconsistent with T. The interesting case is where T has prima facie credibility, that

is, where T is at least model progressive, that is, is increasingly confirmed over time (Part I, 1).

A. The basic notion is that a model, cm, is a confirming model of theory T in TT, a model of data, of

some experimental set-up or a set of systematic observations interpreted in light of the prevailing

theory that warrants the data being used. And where

1) cm. is either a model of T or

2) cm is an approximation to a model of T and is the nth member of a sequence of models ordered

in time and T is model progressive (1.1).

B. A model interpretable in T, but not a confirming model of T is an anomalous model.

The definitions of warrant strength from the previous section reflect a natural hierarchy of

theoretic embeddedness: model progressive, (1.1), model chain progressive (1.3) reduction

progressive (2), reduction chain progressive (2.2), branching reducers (2.3) and progressively

branching reducers (2.4). A/O opposition varies with the strength of the theory. This defines

levels of warrant strength, W1 through W6, respectively. Anomalies face a dialectical burden as

a function of the strength of warrants. We require that a warrant be model progressive at least,

that is there is evidence that is either stable or getting better.

So, if T is merely model progressive, W1, an anomalous model is type-1 anomalous, if in

addition, model chain progressive, W2, type-2 anomalous etc. up to type-6 anomalous for

theories that are progressively branching reducers, W6.

P1. The strength of the anomaly is inversely proportional to dialectical resistance, that is,

counter-evidence afforded by an anomaly will be considered as a refutation of T as a function of

strength of T in relation to TT. In terms of dialectical obligation, a claimant is dialectically

responsible to account for type 1 anomalies or reject T and less so as the type of the anomalies

increases.

P2: Strength of an anomaly is directly proportional to dialectical advantage, that is, the

anomalous evidence will be considered as refuting as a function of the power of the explanatory

structure within which it sits.

P*: The dialectical use of refutation is rational to the extent that it is an additive function of P1

and P2

Part III.

3. Let TTT be an n-tuple TT1,...,TTn of scientific structures seriously proposed at a time. Let

T1,F1,R1,...,Tn,Fn,Rn be their respective realizations at a time. We say that a set of models M,

M = {m1, m2,...,mn} is a persistent model set iff

a) M = m1=d1,f1, m2= d2,f2,..., mn = dn,fn and for all i, j di = dj, or

b) M is a model in a set of ordered subsets of TTT, such that the sequence is well ordered in time

by the subset relation.

3.1 M is an ontic set for TTT, that is, M is a set of models that are putative ontologies for M in

that their common domain persists under reduction relations over time.

3.2. We say that an ontic set O is a favored ontic set iff,

a) O is the set of intended models of a theory T is the first member of a progressive

reduction chain. (O is thus the ontic set of all of the theories in the chain.)

b) the members of the reduction chain are themselves reduction progressive.

c) T is a progressively branching reducer.

3.2.1. Notice that the set consisting of an ontic set and the sets that it generates (the set of sets

under the reduction relation), form a persistent model set.

3. TT is progressive if:

a) TT is model chain progressive

b) TT is model progressive

c) TT is reduction progressive.

3.1. We call T a progressive reducer if:

a) T is reduction chain progressive

b) T is a progressively branching reducer.

3.2. We say T is a favored reducer, if:

a) TT is progressive

b) T is a progressive reducer.

3.3. T is a most favored reducer if T is a maximally progressive reducer, that is, T is the nth

member of a reduction chain such that for all Ti, (i<n) Ti is a favored reducer. (Notice, T is not

reduction progressive, since it stands at the head of the longest reduction chain).

3.3.1. The set O, of ontic models of T, is thus, a favored ontic set in respect of every Ti (i<n) in

the reduction chain.

3.3.2. If T is a most favored reducer, and O is its favored ontic set than O*= {m1,...,mn} of

models mi in O is the ontology of scientific structure TT.

3.3.3. A truth predicate for TT can then be constructed in fairly standard Tarskian as ‘s is true’

for s in T and T in TT, iff O*||-s where O* is the ontology of TT.

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