a linguistics research paper

Drawn into the Fray 1

Running head: DRAWN INTO THE FRAY

Drawn into the Fray of Scientific Battle:

Computational Theory, Modularity in the Mind, and Scientific Inquiry

11 April 2023

Darin L. Hammond

Idaho State University


Table of Contents

Introduction and

Methodology...................................................................................................................

3

Genesis of the Computational

Model.........................................................................................................

4

Chomsky’s Generative Grammar: A First

Step...........................................................................

5

Deconstructing Behaviorist Models of

Language.........................................................

5

Towards a Universal

Grammar........................................................................................

5

Generative Building

Blocks...............................................................................................

6

Language

Innateness..........................................................................................................

7

The Cognitive Machinery of Language: Generative Grammar and Binary

Code....

8

Fast Forward to Computation and Modularity in Cognition: Fodor and

Pinker................................

9

Cognitive

Computation...................................................................................................................

10

Cognitive

Modularity.......................................................................................................................

11

Pinker Versus Fodor Round One--The Basics of

Modularity..................................................

12

Pinker Versus Fodor Round Two—Homunculi and

Demons................................................

19

Pinker Versus Fodor Final Round—Hunger and 20


Thirst...........................................................

Discussion: Assessing the Debate, Entering the Fray as a New

Researcher........................................

21

Conclusions: The Way

Forward..................................................................................................................

24.

References...........................................................................................................................

............................

25

List of Illustrations

Figure

1...........................................................................................................................................

.................

9


Introduction and Methodology

I suspect that most teachers in public schools and community colleges

are like me and were not aware that there has been a cognitive revolution.

However, beginning with Noam Chomsky’s(1957;1959;1965) refutation of

Skinner’s 1957 explication of the behaviorist view of language acquisition

and then his publications in the 1950’s and ‘60’s the world of cognition

began to open up as a relative domain of knowledge, proliferating more

specific disciplines that focused more narrowly on interrelated but distinct

studies of mental processes. New departments were popping up on

campuses across the United States and Europe, thriving upon Chomsky’s

having opened up the black treasure box of the brain, at least as far as

language is an entry point into the workings of the mind. He broke

language apart and put the pieces back together again, analyzing how they

separated and then came back together, meticulously studying and

observing language as the means of acquiring empirical data,

hypothesizing, and experimenting. With the means provided by his

concepts of generative and universal grammar, scientists had the tools, the

binary code of sorts, that would help others put together the theories of the

computational and modular mind.

The present study asks several critical questions as a means of

assessing the current status of computational and modular models. How did

theorists first make the leap from Chomsky’s generative and universal

grammar to computational and modular mind? What are the different


debates that researchers are arguing and grappling with and where will

they go from there?

Through a close review of several key authors in the fields of syntax,

psycholinguistics, cognitive science, and evolutionary psychology, this study

illustrates that generative and universal grammar were key in the genesis of

the cognitive sciences because 1) the grammars provide an entry point into

the brain through an examination of language processing and production, 2)

the grammars predict an inheritable system of modules that innately

prepare the brain to acquire a language, and 3) the grammars led to the x’

bar which clearly demonstrated how, with discrete pieces in the lexicon,

humans produce and combine phrase structures with infinite variety and

that an infinite variety of grammatical sentences can be parsed and

processed by another speaker of the language. These discrete pieces

helped scientists to conceive the brain thinking and processing as a

machine or computer might, though by analogy only rather than literally.

The current status of the field of study is an environment of heated debate

and relative stagnation compared to preceding decades. The debate is how

the mind operates using modules that are specific to certain functions. In

the conclusion, I suggest that while the arguing is frustrating at times, the

independent and courageous voices within the sciences who resist easy

answers and push other thinkers to analyze their own assumptions are

essential to the progress of sciences in general, and modularity in the mind

specifically. The path for the future is to follow the unique voices within the


sciences while actively questioning the veracity of our own assumptions and

those of other scholars. Given the current, immature status of these

cognitive sciences, I speculate that the individual, specialized disciplines

will remain un-integrated with the whole (the cognitive sciences

collectively) until they gain a firm grasp on their narrow scope and as

theorists continue to contest competing models of computation and

modularity. So, fields like L2 acquisition and eye tracking that have not yet

influenced one another significantly will do so more as the fields mature. I

judge this to be healthy for new fields of study.

Genesis of the Computational Model

For a new theory to take hold in linguistics or any other science, a

scholar must first create a need for new explanations based upon the

inadequacies of the current models. When Noam Chomsky began publishing

in the field of syntax, B.F. Skinner’s behaviorist model of language was in

the spotlight, a natural extension from his studies in operant conditioning

with pigeons. Skinner’s behaviorist view popularity gained prominence

because it was so intuitive, and his ideas breathed life into a stagnating

discipline that had no place to go since Saussure’s arbitrary signs demoted

linguistics from a science to a pseudo-empirical investigation of the

subjective nature of language. Skinner’s ideas were tangible and provided

a simple explanation of language that could be tested empirically. While

Chomsky was not the only linguist to attack Skinner, he was the most

effective in large part because he had an alternative. His transformational


grammar not only filled the void left after blowing Skinner out of the water,

it described the complexity of human language, a complexity that mocked

Skinner’s simple behaviorist explanation.

Chomsky’s Generative Grammar: A First Step

Deconstructing behaviorist models of language.

In 1957, Chomsky wrote a scathing review of B. F. Skinner’s (1992,

1957) most important work on language, Verbal Behavior. In his short

review Chomsky (2008) dismantled Skinner’s argument deftly, labeling the

idea of language “through reinforcement ... quite empty” (p. 12), and then

expounded his critique into book length two years later (Chomsky, 1959).

The importance of Chomsky’s (1957) review work was to create room for

the more impressive Syntactic Structures published the same year as

Skinner’s work. His transformational and generative grammar was the real

crushing blow for the behaviorists because this new model accounted so

well for the complexity of human language. Chomsky’s work in the late

1950’s established the transformational mechanisms that could manipulate

words, phrases, and clauses into an indefinite number of structures that a

normal speaker can both produce and process. The theoretical implications

of this transformational system laid the foundation for Chomsky (1965) to

elaborate his ideas of generative and universal grammars, especially in

Aspects of the Theory of Syntax.

Towards a universal grammar.


While the three terms are used interchangeably, they differ in

connotations—transformational emphasizing the syntactic operations,

generative stressing the infinite nature of the language possibilities, and

universal emphasizing the (attempted) cross-language description of

language structures. The latter two are recent additions to linguistic

terminology (Generative Grammar, 2000), but universal (or philosophical)

grammar is a concept that goes as far back as 1751, referring to the same

basic idea of creating “a scheme of classification capable of including all the

grammatical categories recognized in actual languages” (Universal

Grammar, 2000). Breaking the syntax of language into finite, fundamental

units allowed Chomsky to push closer to an understanding of how language

might work in the human mind. He hoped that this would lead to the ever

illusive universal grammar (UG), representing the rules of structure that

connect all human languages. In returning to the idea of a UG, Chomsky

(2006) built upon the long forgotten foundation of the concept in the

“rationalist philosophy of language [which] merged with various other

independent developments in the seventeenth century, leading to the first

really significant general theory of linguistic structure” (p. 12). The concept

of a UG suggests a link to L2 acquisition as a common ground in languages

across cultures should inform the way teach grammar to both L1 and L2

learners. UG provides hope in pointing to commonality between languages

and cultures across the globe.

Generative building blocks.


Chomsky still strives describe and understand the UG (now through

minimalism) provides a backdrop to the current study though an in-depth

discussion is beyond the scope of the current research. The generative

aspect of Chomsky’s grammar represents a more explicit precursor to

current computational models of the mind. Prior to Chomsky, no theory had

been able to account for the generative and creative nature of language

(especially not the behaviorism), but in the combinatorial transformations of

discrete language units, Chomsky could parse a sentence into its smallest

components, illustrating cognitive manipulations that had power to build

utterances all the way from the phonological to the syntactic and semantic

levels. Chomsky’s (1965) definition clarifies this:

By a generative grammar I mean simply a system of rules that in some

explicit and well-defined way assigns structural descriptions to

sentences. Obviously, every speaker of a language has mastered and

internalized a generative grammar that expresses his knowledge of

his language. This is not to say that he is aware of the rules of the

grammar or even that he can become aware of them, or that his

statements about his intuitive knowledge of the language are

necessarily accurate. (p. 8)

The system of rules describe the structure of sentences that, on the

syntactic level of noun phrases, verb phrases, and clauses, form the surface

structure of an utterance and correspond to a deep structure that comes

closer to the mental representation of the components. Chomsky hints here


at powerful abstractions that have become some of his most important and

productive concepts.

Language innateness.

The definition of generative grammar above entails that humans are

born with the cognitive machinery of language in place to a certain extent,

suggesting that “every speaker of a language has mastered and internalized

... his intuitive knowledge of the language” (Chomsky, 1965, p. 12). The

innateness of language accounts for the insufficient input feeding the

behaviorist model. Chomsky (2006) breathes new life into Descartes’

concept of innate ideas stating, against strong opposition in some factions

of the linguistic community that “there are certain innate conditions on the

form of grammar that determine what constitutes linguistic experience and

what knowledge will arise on the basis of this experience” (p. 159). The

power in this model lies in the fact that establishes an intimate relationship

between hidden cognition and tangible grammar. In other words,

innateness suggests that by understanding the nature of generative

grammar, linguists can begin to comprehend the workings of the mind.

This grammar to brain connection revolutionized linguistics, but equally

important, Chomsky gave birth to a multiplicity of completely new scientific

disciplines that now held a conceptual link to the human brain:

psycholinguistics, cognitive science, nuerolinguistics, nuerophilosophy,

computer science, artificial intelligence, etc. The generative ability of

language innateness to broaden the scope of science so productively


provides a proof of generative grammar. Few theorists have so positively

affected a human science as Chomsky.

The cognitive machinery of language: generative grammar and binary

code.

With the mind-language connection established, another feature of

generative grammar accelerated an understanding of cognition. Since

linguists could breakdown utterances from the surface structure of syntax

down through phonology, they began to think about language in unique and

productive ways. Looking at grammar through the generative lens made

the pieces look more like code that could be manipulated by the human

brain and by a computer. By analogy, researchers began to think of the

processes of the human mind as a subject for empirical observation and

analysis. This was shocking to the scientific climate of psychology as Barrett

and Kurzban (2006) capture saying:

Prior to the cognitive revolution of the 1960’s, it was popular to view

the mind as a kind of black box and to view conjectures about its

contents as unscientific. The cognitive revolution reversed this

climate, rendering the search the contents of the black box—a

description of its internal structure that could account for the

systematic relationships between information inputs and behavioral

outputs—a key scientific objective of psychologists. (p. 628)

The cognitive revolution initiated by Chomsky began to morph the metaphor

of the black box into the white box of a computer monitor, the brain

XP

Specifier XFigure 1: A representation of the basic, repeatable pattern of Jackendoff’s (1977) x’ theory of phrase structure where x corresponds to a lexical entry such as a noun, verb, or adjective (I created this graphic).


becoming increasingly understandable as linguistics, the new cognitive and

nuero-sciences, biology, and medicine converged on the common target of

the mind. And, the computer metaphor actually became the new framework

for thinking about the mind.

Fast Forward to Computation and Modularity in Cognition: Fodor and

Pinker

Here my account shifts from Chomsky to several threads that extend

from his ground breaking theoretical work, a necessarily abridged account

as the field quickly became crowded with

researchers following his lead. Historically,

Chomsky shifted as well, moving to language in

the realm of politics and ideologies while still

keeping his finger linguistics (most recently with

minimalism). In the realm of syntax, Ray

Jackendoff (1977) clarified and simplified

Chomsky’s generative/transformational grammar

with the x-bar theory that mapped phrase structure with artistic simplicity

in his seminal X’ Syntax : A Study of Phrase Structure (see figure 1). The

sleekness of the basic phrase structure theory assisted those who were

beginning to see the mind at work in combining finite elements to create

infinite unique utterances. Jackendoff’s x’ theory certainly meets Chomsky’s

(1965) standard “to generate an indefinitely large number of structures”


(pp. 15, 16). The small phrases are easy to manipulate, and the x’ theory

allows for movements such as the “wh” trace. The structure also allows

embedded and relative clauses as well as clauses joined by conjunctions. As

the smallest unit in the grammar moves all the way down to phrases, one

can visualize the relative ease in producing and processing the chunks that

fit together hierarchically which moves the language closer to the language

of computation and computers, the bits of data being combined by a

language user in an infinite variety of ways. Also, Chomsky (1965) and

Jackendoff (1977)both point to the even more discrete studies of phonology

and morphology that are busy analyzing words into their smallest units, and

one can follow the x’ chain up from phonemes to the higher levels of

semantics, pragmatics, and discourse analysis. The important concept here

is that language can be broken down into bits and built up into discourse.

The manipulation of large number of small units closely resemble the binary

1s and 0s of computer code. The x’ theory attracted masses of researchers

who were now able, with Jackendoff’s framework, to visualize how the brain

might be able to manipulate the pieces of data in the way that a computer

processes input.

Cognitive computation.

Jackendoff accelerated the study of syntax and also the proliferation

of original research seeking to understand first the parsing method, and

then what this theory of language revealed about the human brain.

However, scholars had already begun work to think through the nature of


the mind. Specifically, Pinker (1997) refers to Alan Turing’s research

published beginning in 1950, even before scientists mastered the science

that would give birth to computers (pp. 67, 68). Turing (1950) theorized

that a machine could be invented that would “think” through basic

information processing, computations, and information production. He

actually constructed a basic machine drawing from this vision which

succeeded in computing simple data by processing the input and then

computing and producing the response. The machine did not really serve

any useful purpose as it could not do much and computers were on the way,

but the key was that Turing proved that a machine, in a very basic way,

could act like a simple process of computation in the brain (Pinker, 1997 p.

69). Chronologically, the Turing (1950) machine came almost 10 years

before Chomsky started to publish work on generative grammar which

shows that some psychologists were moving in the direction of seeing the

brain as a powerful computational organ even before the analysis of

language became an important body of evidence. When Chomsky, and later

Jackendoff, provided the basic structure, scientists were already waiting to

put it to the test.

For the purpose of this study, I am going to fast forward through the

intermediary stages development of a complex model of the computational

mind in order to assess the current status in what has become the fields of

cognitive science and psycholinguistics. The inner workings of the human

mind had been a tough nut to crack as there were very few scientific


methods available to analyze the brain at work. Even when more

neurophysiologists discovered how neurons fire and transmit signals,

cognitive scientists had to puzzle through the processes involved in

computation. Scholars are still mystified by the complexity and multiplicity

of tasks the human brain can compute its way through to completion, and a

single organ doing all these distinct types of processing seemed beyond the

realm of plausible. With sensory information processing, abstract thinking,

math calculating, muscle stimulating and controlling, and language

production and processing, just to name a few mental processes, a single

organ would have to be miraculous in order to be capable of processing

such specific tasks with such a broad array functions. The answer that

cognitive scientists are clarifying and debating requires that scientists look

at the brain using an entirely different frame.

Cognitive modularity.

Complex tasks, Jerry Fodor (1983) reasoned, require a complex

machinery and architecture, something far more intricate than the Turing

machine or even the most powerful computer. With a background from MIT

in philosophy, psychology, and linguistics prepared him to create a new

vision of the brain at work. By 1981, Fodor had written many in-depth books

on the computational mind and language (Fodor & Katz, 1964; Fodor,

Bever, & Garrett, 1974; Fodor, 1975; Fodor, 1981), and it is likely that this

early work lead him to re-conceptualize the human brain. As he researched

and theorized, he began to re-envision the mind not as a single organ, but


as multiple organs or modules which culminated in the publication of The

Modularity of Mind : An Essay on Faculty Psychology (Fodor, 1983). With

multiple modules that are able to specialize in the various operations

required of the brain, the mind gains processing power exponentially.

Modules in the brain laid the foundational architecture for the extremely

complex multitasking required (to varying degrees), so the brain can, for

example, manage involuntary needs of the human anatomy and physiology,

see a person, and communicate with her through language, all

simultaneously and with ease. Fodor’s vision of modularity quickly caught

hold in cognitive (and all related) sciences, and as he tested and further

developed his theory, other researchers jumped in to explore the

functionality of Fodor’s model. Almost immediately, divisions among the

scholars emerged as they conceived different possibilities for a modular

mind, and to this day they are still arguing and probably will be as the

intricacies of the mind resist interpretation (Barrett & Kurzban, 2006, pp.

628-631).

The initial model Fodor proposed was too small for theorists such as

Pinker (1994; 1997; 2007), Tooby, Cosmides, and Barret1, and Jackendoff

(2003) who have rejected, or rather replaced, what they see as a narrow

scope of modularity. Fodor (1983), in his initial publication qualified the

modularity with nine features that he described as characteristics of

modules. Two of these, “domain specificity, [and] encapsulation” (Barrett &

Kurzban, 2006, p. 629) are the most contentious as the philosophy of the 1 Found in The Innate Mind (Carruthers, Laurence, & Stich, 2005).


mind is virtually inseparable from the cognitive science, and Fodor’s

features, therefore, have profound philosophical implications. Fodor

introduced modularity to handle many processes of the brain that were “of a

very specific kind—reflex like, hardwired devices that process narrow types

of information in highly stereotyped ways” (Barrett & Kurzban, 2006, p.

628). This has been labeled as the narrow conception of modularity, and

despite the fact that Fodor said that these features were not set in stone

when he published, many dominant thinkers in the computational and

modular mind envision a “massive modularity” (Barrett & Kurzban, 2006).

Fodor has dug in his heals resisting this shift as you will see.

Pinker versus Fodor round one—the basics of modularity.

The battle began in the academic journals after the publication of

Fodor’s precedent setting 1983 book. Steven Pinker (1997)—then from MIT,

now at Harvard—with his experience in psycholinguistics, cognitive science,

and the relatively new field of evolutionary psychology, sees the processes

of natural selection in the brain as he attempts to reverse engineer the

selections that have been made through evolution in the human brain. By

reverse engineering, evolutionary psychologists like Pinker (Daniel Dannett,

Jared Diamond, John Tooby, and Leda Cosmides are some others)2 look at

natural forces that might have shaped the mind into a modular organ. He

claims that the proper approach would be to look at the “functional

2 The title evolutionary psychologist, it turns out, is currently a malleable job description. Since the science is newly defined by these scholars, their credentials and initial disciplines vary—Pinker, psycholinguistics; Daniel Dennett, philosophy; Jared Diamond, physiology and membrane biophysics; John Tooby, anthropology; Leda Cosmides, psychology.


specialization” (Barrett & Kurzban, 2006, p. 629) that shaped the modules

and attempt to describe the processes at work rather than prescribe

characteristics that the modules must have (referring to Fodor’s list of nine

features).3 The functional specialization that the evolutionary psychologists

look for in the modules are the mental processes that work in a specific way

to accomplish tasks, and so the focus is on possible functions of a module

rather than on delineating the boundaries that define the module (1997).

Using the angle of his perspective in evolutionary psychology, Pinker (1997)

published How the Mind Works as compendium of his view of computation

and modularity (he does not use the label “massive” that Fodor applied to

this model). Though not explicitly stated by Pinker, his book is an extended

response to Fodor’s ideas which Pinker gives him credit for. He criticizes

Fodor for remaining fixed with his initial model while evolutionary and

linguistic evidence suggest that he does not have it quite right. Pinker

claims that scientists should expect to find a huge number of modules

within the brain because each module will be specialized as shaped by

natural selection, a process that leads to specialization (Barrett & Kurzban,

2006, p. 629).

Natural selection, as supposed by the evolutionary psychologists, has

evolved the brain that human beings now possess, and to neglect the

shaping forces of selection over time that create the modules that do the

3 According to Barrett and Kurzban (2006) these are: “domain specificity, encapsulation, mandatory operation (automaticity), inaccessibility to consciousness, speed, shallow outputs, fixed neural localization, and characteristic breakdown patterns” (p. 629).


computing in the brain is to ignore the essence of the function of the mental

organs. Pinker (1997) defends this view:

Natural selection cannot directly endow an organism with

information about its environment, or with the computational

networks, demons, modules, faculties, representations, or mental

organs that process the information. It can only select among genes.

But genes build brains, and different genes build brains that process

information in different ways. The evolution of information processing

has to be accomplished at the nuts-and-bolts level by selection of

genes that affect the brain-assembly process. (p. 176)

Pinker responds here to the criticism by Fodor that he lacks any sort of

proof to justify that natural selection can foster modularity, and that without

evidence, his claim is mere speculation without support (Fodor, 2005).

Pinker counters by dodging the criticism and repeating the claim, “genes

build brains” and natural selection determines genes to be perpetuated. He

provides an unusual support later, based upon artificial intelligence.

Computer scientists have been able to create genetic algorithms that mimic

the natural selection process. So, virtual creatures in the form of software

programs are made to reproduce or duplicate while inserting random

deviations in the programming with each generation. This is analogous to

random gene mutations in organisms as they reproduce over generations.

In these experiments, the reproduction was accelerated so that they could

observe in a short amount of time what would take thousands of years in an


organism. Their objective was to test whether this algorithm would tend

toward more sophistication or intelligence, and they have found that “after

many cycles of computation, selection, mutation, and reproduction, the

surviving programs are often better than anything a human programmer

could have designed” (pp. 176-177). Pinker reports that they have

attempted to create this same type of evolutionary migration by modeling

neural networks on a computer program and accelerating the process of

natural selection by virtual reproduction, merging gene halves (analogous

to the male and female genetic contribution), and causing random

mutations. He claims that the modeling works, that the networks tend

toward complexity and a “higher intelligence” over generations. Oddly, in

the end of his argument Pinker harkens back to the behaviorists that

Chomsky refuted in the infancy of modern linguistics and cognitive science.

He invokes B. F. Skinner to show that learned behaviors can lead to a better

selection potential (p. 180). Retrieving this idea of learned behavior as

inheritable by offspring, I agree is a stretch and smells pseudo-scientific and

pseudo-Darwinian. Natural selection, the evolutionary mechanism that both

Darwin and Pinker champion, operates on the principle of random

mutations that have a selection advantage and are therefore perpetuated.

While peripherally this behaviorist leap might hold true, but it seems that

nature will select the most fit that pass on genes, not the learned behavior,

and the evolutionary migration is effect of random mutation rather than any

mechanism connected with behavior.


In reference to this portion of the argument, despite clever types of

evidence such as the software analogy, I agree that there is a lack of

evolutionary evidence to support the natural selection of modularity in the

human mind. Grasping at Skinner’s failures as a source of evidence seems

misguided. But, on the other hand, what sort of evidence could Pinker

present that what satisfy Fodor’s criteria? Reverse engineering the natural

selection process can, after all, only be a thought (or computer) experiment

unless Fodor wants some sort of old school phrenology study. To say that

More to the heart of the issue, Fodor will not accept any evidence

short of empirical data, observable and repeatable, so he appears to distrust

the methodology used by evolutionary psychologists (the two terms paired,

after all, do seem to be an oxymoron) which may be a valid concern, but he

skirts the issue of defining what methodologies are acceptable in this

science—the study of modularity and computation in the human mind.

Fodor himself can only go so far in his theorizing, yet somehow he has the

power to forward his claims as valid without evidence but nobody can.

Fodor’s complaint of his is the problem of black box, the metaphor for the

mind discussed previously. The black box, in many ways, will always remain

closed and resistant to certain kinds of observation and analysis. Pinker

says that we can speculate (using reverse engineering for example) with

reasonable assumptions and creative evidence from fields that are not

restricted to linguistics and psychology. Fodor rejoins that this is not


empirical science; that is speculation. In the end, perhaps they both are

right.

Continuing the fight, Fodor (2001) published The Mind Doesn't Work

That Way : The Scope and Limits of Computational Psychology (TMD, the

author’s initialism that I will use from here on) as an obvious rejection of

Pinker’s (1997) How The Mind Works (HTMW , again the author’s

initialism). Fodor, in addition to “massive modularity,” adds a new label to

the faction that supports the function and specialization as shapers of many

modules that merely operate in syntactic language, the modules

hierarchically ordered in some cases, “The New Synthesis” (Fodor, 2001) .

Fodor disparagingly describes the:

Turing architecture of syntactically structured mental representations

and syntactically driven computational operations defined on these

representations. The New Synthesis thus shares with traditional

rationalism its emphasis on innate content; but it has added Turing's

idea that mental architecture is computational in the proprietary

syntactic sense. (p. 19)

Not only is the title of his book polemic, but the argument from the

beginning is disparaging, Fodor labeling Pinker with Turing’s (1950)

machine as if it were a primary piece of evidence. Pinker is obviously giving

a historical overview of computation in HTMW, and he sees as significant

Turing’s step forward conceptually to conceive the mind as operating in a

machine-like fashion (1997). Turing even built the mechanism to prove his


point, and Pinker uses him to trace the history and provide a visual,

concrete example of what he is explaining. After all, if Pinker’s primary aim

with the Turing example was create a realistic model for brain function, he

would have simply chosen a powerful computer which would be a more apt

analogy to processing in the brain. Pinker does look at computers and

electronics throughout HTMW as examples of how the brain might function

in an analogous biological way. Pinker (2005) restates this, perhaps more

clearly in a later article saying “’computation’ in this context does not refer

to what a commercially available digital computer does but to a more

generic notion of mechanical rationality, a concept that Fodor himself has

done much to elucidate (Fodor, 1968; 1975; 1981; 1994)” (p. 2). Fodor

intentionally misreads the function of Pinker’s evidence and overextends it

in hyperbolic fashion in order to deride and discredit Pinker. Such a blatant

attempt to manipulate information and misguide his readers with a biased

appeal to pathos, makes Fodor’s credibility questionable.

Turing after all appears in only three pages of HTMW, while the name

occupies lines 19 times in TNHTMW’s first chapter as he tries to make the

label stick. In the same chapter, he uses variations on syntax 46 times, and

rationalist. New Synthesis (Fodor’s capitalization), by contrast, only appears

13 times (see Fodor, 2001, Ch. 1). The only reason I counted these was

because they stand out so dramatically on the page, distracting visually and

creating the effect in the reader of being beaten over the head with a baton.

They are all similar in the sense that Fodor uses them pejoratively to


characterize and dismiss the kind of research and theory Pinker is working

on. For example, he coins the term New Synthesis to label Pinker’s revival

of the rationalist philosophy or psychology (Fodor actually interchanges all

of these terms as if synonymous) that describes the innate ideas and

concepts in language4 that might be transformed through the mechanism of

mutation and inherited by offspring. Pinker draws from Chomsky’s (1965)

ideas on innateness and syntax in the UG, the tool box for learning language

that all children posses in any culture of the world. Fodor uses Chomsky

(only 16 times) and syntax interchangeable referring to the computational

language or software that the brain runs on in the Turing model of the

mind. From the outset, Fodor attempts to subvert Pinker’s argument by

bombarding him with labels while bludgeoning the reader with the same

rhetorical force. This is the form stereotyping the politicians use to smear

other candidates, a low tactic.

Fodor also errs in ignoring Pinker’s careful linking of pieces throughout

the book as lines of support that are coherent as a whole and merit the term

“evidence” in the realm of empirical science. In “Chapter 4 The Mind’s

Eye,” for example, Pinker meticulously explores in-depth knowledge from

diverse disciplines in an attempt to thoroughly examine and describe the

modules that function to create stereovision, 3D (pp. 211-298). He uses

visual, cognitive, linguistic, anatomical, physiological, nuerophysiological,

4 Pinker’s books The Blank Slate: The Modern Denial of Human Nature (2002) and The Stuff of Thought: Language As a Window into Human Nature (2007) develop in much more detail, the ideas of innate language, concepts, and metaphors (drawing from Lakoff) and the connection to human nature and behavior.


neurophilosophical, etc. research to reason through how stereovision

functions so that he can, in turn describe the modules themselves. Pinker

provides evidence through specific, descriptive, and empirical example

repeatedly in HTMW to illustrate and support his view of computation and

modularity. To ignore these as evidence is an injustice.

Fodor is correct that Pinker advocates the innate language structures

and modules, and this actually becomes a point of departure for Pinker in

his book publications, the next two discussing in great depth this innateness

and human nature (footnote 3). Many other would-be psycholinguists have

jumped ship as well, following the lead of Pinker and perhaps Chomsky in

his radical politics and assessment of human nature of the last 30 years,

migrating toward several connected hotly debated topics grounded in

natural selection and human nature in evolutionary psychology. I’m not

sure that it is Fodor’s harsh rhetoric and territorial behavior that has turned

these scholars away from modularity of the mind, but I am sure the current

climate of the discipline makes psycholinguistics and cognitive science

unappealing which is unfortunate. This is a shame since the more great

minds we have at work to discover and delineate the processes and

structures of the mind, the most complex biological (or mechanical) organ,

the more progress will be made.

Pinker versus Fodor round two—homunculi and demons.


This is not Fodor’s only line of argumentation, but it is the most

striking, and establishes a negative precedent in the dialogue between the

two scholars. In contrast, Pinker praises Fodor for the concept of

modularity though he differs with him on some of the details. One hotspot

that Pinker (1997) creates is the need for, what have been called, homunculi

(Pinker likes the term demons) in massive modularity that function as

messengers or processors in the brain. He later adopts the term “access-

consciousness” to give the idea of high level processors a more formal feel

than demons (pp. 138-148), processors of some sort that manage at a higher

level of thought than, say, vision in order to remember, synthesize, and

govern input and output from the nervous system at large (pp. 136-148).

The two scholars have gone the rounds on this issue more than any other

because Fodor (2001) negates Pinker’s “access-consciousness” as

reminiscent of the antique idea variously termed the ghost in the machine,

demons, or homunculi. These terms refer pejoratively to a little being within

the brain that must be necessary in order to make the incredible complexity

of the mind possible (Fodor, 2001), but to be fair, Pinker (1997) explicitly

addresses and satisfactorily resolves this problem, essentially by saying that

it can wait until later (pp. 79-99). He takes on the role of reporting the data

and research available that inform the lower level cognition in the model of

the computational and modular mind (Pinker, 1997, pp. 91-93). In the role

of evolutionary psychologist, his role for the moment is to try and describe

the features of potential module(s) to lay the foundation for work that can


be done later, once modules are better understood (after description has

been accumulated, classified, critiqued, etc.) (Barrett & Kurzban, 2006, pp.

628-647). Essentially, this access-consciousness is an x value, a variable

that can be defined and articulated later.

Pinker versus Fodor final round—hunger and thirst.

The debate that Pinker (1997) ignites in HTMW continues today, but

the flurry of reviews and replies that followed Fodor’s 2001 publication

TMD, dialogues between the two from a distance, make up the heated,

exhausted battle to the end of the fight (Deborah Tannen (1999)could have

a hay-day with the militaristic language of these two). Pinker (2005) first

responds to Fodor’s (2001) blatant mockery in The Mind Doesn’t Work

That Way (emphasis added) with a defense, disguised as a review of the

book, to Fodor’s vicious rhetoric. Pinker (2005) asks the puzzled and

stunned question “So How Does the Mind Work?” (Pinker’s italics). I think

that he is genuinely confused by what he perceives, correctly as Fodor

flipping to argue the other side, in opposition to his ground breaking work

on modularity. “Fodor, more than anyone,” says Pinker (2005) “has

defended the computational theory of mind ... specialization ... [and]

evolution” as a shaping force in the modular mind (p. 2). At this point,

Pinker still argues that Fodor and himself have much in common in their

writing on the computational and modular theories. And yet, with all this


agreement, here is the trail of blood that follows Pinker and Fodor from the

beginning, each written in response to the other (except Fodor’s initial book

on modularity):

1981-- The Modularity of Mind : An Essay on Faculty Psychology

1997—Pinker, How the Mind Works

2001—Fodor, The Mind Doesn't Work That Way: The Scope and

Limits of Computational Psychology

2005—Pinker, “So How Does the Mind Work?”

2005—Fodor, “Reply to Steven Pinker ‘So How Does the Mind

Work?’”

2005—Pinker, “A Reply to Jerry Fodor on How the Mind Works”

2006—Fodor, “How the Mind Works: What We Still Don’t Know”

In these pieces, they are sometimes angry and sometimes humorous. They

rehash the same arguments, make the same claims, provide the same

evidence. However, in the restating and rethinking of argumentation, both

sides begin to become more focused.

In responding to the question at the core of all this debate, Fodor

(2005) reveals a fundamental truth that has been revealed:

So how does the mind work? [author’s bold and italics]

I don’t know. You don’t know. Pinker doesn’t know. And I rather

suspect, such is the current state of the art, that if God were to tell us,

we wouldn’t understand him. (p. 31)


Fodor’s tone is still a bit playful with the question and answer set up, the

short witty response. But his tone is also serious and almost dark. The

anger, perhaps, seeps out of his language in the heat of the debate, and

invoking God seems odd and out of place. Knowing that Pinker is an ardent

atheist, as I’m sure Fodor does, he seems to be provoking Pinker as if

Pinker may be about to quit the fight so Fodor has to fuel the fire again.

Discussion: Assessing the Debate, Entering the Fray as a New

Researcher

Is this polemic rhetoric effective in moving science forward?

Jackendoff (2003) and the research team of Barret and Kurzban(2006) do

not think so. As a novice researcher in the field of psycholinguistics and

cognitive science, I feel as if I have been sucked into the complexity of this

debate against my will. In fact, I have. The researchers I have discussed

subverted my initial methodology for this study, or at least I allowed them

to. Originally I had intended to ground myself in the theories of modularity

and the computational mind so that I could then see how eye tracking

studies and reading fit into the work of the scholars I discuss here. I have

done all the reading and research for that kind of a paper, and I have found

that at this point they fit together very loosely, not at all integrated into a

nice map of the brain module for reading. I have done the research with L2

acquisition (Clahsen, & Felser, 2006a; 2006b; Cook, 1999; Friesen & Jared,

2007; Fukkink, Hulstijn, & Simis, 2005; Koda, 2007) and eye tracking

(Reichle, Liversedge, Pollatsek, & Rayner, 2009; Reichle, Warren, &


McConnell, 2009; Reichle, Rayner, & Pollatsek, 2003; Reichle, 2006; Kliegl,

Nuthmann, & Engbert, 2006; Rayner, 1993; Rayner, Pollatsek, Drieghe,

Slattery, & Reichle, 2007; Rayner, 2009; Rayner, Smith, Malcolm, &

Henderson, 2009) as well, applying eye tracking research to the pedagogy

in this domain and reading closely what few studies there are in L2 reading

that apply eye tracking research (Duyck, Vanderelst, Desmet, & Hartsuiker,

2008; Elston-Güttler & Friederici, 2007; Keating, 2009; Usó & Martínez,

2006; Yamada, 2009). However, these fields are not as interconnected as I

innocently thought they would be. The domains I have studied are new

disciplines tackling perhaps the largest problems ever confronted by

scientists, with the tools necessary for discovery in many instances

withdrawn because, in contrast to the metaphor of the black box, the

container of the human brain holds the living tissue of a sentient being who

would not appreciate their gray matter being poked and prodded. The

domains and disciplines will converge I suppose, based upon the research,

but I discovered that this is a slow process. The individual disciplines such

as L2 acquisition and eye tracking have to figure out precisely the nature of

their science before they integrate and discover how the separate modules

of science operate within the mind of science as a whole. Perhaps, this type

of research on my part is valuable because I am in the trenches and can

apply the bits and pieces I discover and learn and integrate them into my

classroom. After all, looking back over this subject matter I have covered,

what here does not have pedagogical implications for the English and SLA


classrooms? For that matter, this is what all education is about. Figuring

out how to encourage students to discover their mind and how it works.

Helping them to see how developing the modules with their brains will

benefit their communities and societies as they are more productive and

effective in all that they do, showing them through literature or science, or

any other discipline that developing their thinking skills will help them to

live more satisfactory, happier lives.

Chomsky first aroused my interest in the idea of UG and innateness,

the language of human beings reflecting the operations and processes of

the mind. The fact that a UG could be passed on intrigued me because I

could not see initially how that could happen. Unconsciously, I have always

believed the erroneous concept of babies being born with a “blank slate,”

Locke’s “blank slate” (Stuhr, 2000), but as I began to read Jackendoff and

then Pinker, I could see the real complexity of a language and its acquisition

by human beings. The evidence these three scholars who tend to think in

similar veins persuaded me that the process of learning a whole language

and grammar by the age eight (or at least 13) would be an impossible feat

without some sort of jump start (see Pinker, 1994).

As many before me, I became enamored with the eloquence of Pinker,

the simplicity of Jackendoff (in a positive sense), and the radicalism of

Chomsky. I could not hold myself back as pieces of the mysteries that have

always intrigued me were revealed by each of these authors. My view was

utopian in a sense because I believed naively that Pinker could guide me


through all of the unknown, shedding light on sentience, consciousness, and

the mind.

Fodor, however, opened my mind to the complexity and

contentiousness of the matter, the insolvability of some problems. I read the

documents I describe above almost chronologically with the exception of

reading Pinker’s (1997) HTMW before I read Fodor.5 While still moving

through Pinker’s works, I discovered Fodor (1983) as the father of

modularity and jumped back to review his work The Modularity of Mind. All

was well until I moved on to Fodor’s TMD where I felt attacked along with

Pinker, my new ideas feeling threatened. Pinker was my psycholinguistic

hero by this point. At times, Fodor was witty and humorous, but Pinker

(2005) rightly describes his attitude toward the dialogue of academia saying

“at critical junctures, Fodor refuses to offer arguments for his convictions,

opting instead for peremptory sarcasm” (p. 33). However, to understand

Fodor, I have found is to understand the need for resistance to the popular

trends in scientific thought. Knowing our ignorance pushes us towards

discovery, and Fodor (2006) insightfully reveals this in the last of his

exchanges:

One could make a case that the history of cognitive science,

insofar as it’s been any sort of success, has consisted largely of

finding more and more things about cognition that we didn’t know

and didn’t know that we didn’t. “Throwing some light on how much 5 This actually benefited me as a new researcher because Pinker addresses a wider audience and is easier to read. Also, Fodor has a cantankerous relationship with his intended audience which becomes annoying and discouraging.


dark there is,” as I’ve put it elsewhere. The professional cognitive

scientist has a lot of perplexity to endure, but he can be pretty sure

that he’s gotten in on the ground floor. (p. 86)

Whether this is an attempt at reconciliation with Pinker or justification of

his role in the dialogue, Fodor hits on a truth about science and linguistics

in general—there is always more to be done. Language, computational

processes, and modularity are, at best, only vaguely understood, and the

nature of the work in this field is difficult. Researchers must find creative

entries into the black box, meticulously describe functions and processes,

and walk down costly, dark, dead-end paths, but the progress comes with

costs at times as I have found in this study. Not only are scholars hungry

for new knowledge and discovery as they research and publish, they are just

hungry, and dead-end paths, though necessary to the science, do not put

food on the table. Therefore, the rhetoric in our debates is heated and life

threatening, our adrenal causing us to devour research, observation, and,

sometimes, other researchers, as if they were things to be consumed.

Conclusions: The Way Forward

The reality of the battle between Fodor and Pinker is that they are on

the upper crust of academia, the very top of the ivory tower with a sky view,

and a few of the things keeping them on track, keeping them human and

humane (and perhaps sane), are their ethics and integrity as scientists and

scholars. Recognition of their imperfections as they pursue and create

knowledge may be absolutely necessary to maintain the true scientific mind,


and someone who emphasizes what is unknown, while at the same time

entering the fray productively, though perhaps antagonistically, against any

perceived threat or fear, with a willingness to change one’s mind, arguing

at times in opposition to what he once supported, keeps the upper tier in

academia humble and reminds those of us below that those above do not

have perfect careers nor are our careers failures.

References

Barrett, H. C., & Kurzban, R. (2006). Theoretical note--Modularity in

cognition: Framing the debate. Psychological Review, 113(3), 628-647.

Carruthers, P., Laurence, S., & Stich, S. P. (2005). The innate mind. New

York: Oxford University Press.

Chomsky, N. (1957). Syntactic structures. Netherlands: Mouton.

Chomsky, N. (1959). Verbal behavior, by B. F. Skinner. Indianapolis, IN:

Bobbs-Merrill.

Chomsky, N. (1965). Aspects of the theory of syntax. Cambridge, MA: MIT

Press.

Chomsky, N. (2006). Language and mind. New York: Cambridge University

Press.

Chomsky, N., & Arnove, A., (2008). The essential Chomsky. New York: New

Press.

Clahsen, H., & Felser, C. (2006a). Continuity and shallow structures in

language processing. Applied Psycholinguistics, 27, 107-126.


Clahsen, H., & Felser, C. (2006b). Grammatical processing in language

learners. Applied Psycholinguistics, 27(1), 3-42.

Cook, V. (1999). Using SLA research in language teaching. International

Journal of Applied Linguistics, 9(2), 267-84.

Duyck, W., Vanderelst, D., Desmet, T., & Hartsuiker, R. J. (2008). The

frequency effect in second-language visual word recognition.

Psychonomic Bulletin & Review, 15(4), 850.

Elston-Güttler, K. E., & Friederici, A. D. (2007). Ambiguous words in

sentences: Brain indices for native and non-native disambiguation.

Neuroscience Letters, 414(1), 85-89.

Fodor, J. (1975). The language of thought. New York: Crowell.

Fodor, J. (1981). Representations : Philosophical essays on the foundations

of cognitive science. Cambridge, MA: MIT Press.

Fodor, J. (1983). The modularity of mind: An essay on faculty psychology.

Cambridge, MA: MIT Press.

Fodor, J. (2001). The mind doesn't work that way: The scope and limits of

computational psychology. Cambridge, MA: MIT Press.

Fodor, J. (2005). Reply to Steven Pinker ‘So How Does The Mind Work?’

Mind & Language, 20(1), 25-32.

Fodor, J. (2006). How the mind works: What we still don't know. Daedalus,

135(3), 86-94.


Fodor, J., Bever, T. G., & Garrett, M. F. (1974). The psychology of language:

An introduction to psycholinguistics and generative grammar. New

York: McGraw-Hill.

Fodor, J., & Katz, J. (1964). The structure of language: Readings in the

philosophy of language. Englewood Cliffs, NJ: Prentice-Hall.

Friesen, D., & Jared, D. (2007). Cross-language message- and word-level

transfer effects in bilingual text processing. Memory & Cognition, 35(7),

1542-1556.

Fukkink, R. G., Hulstijn, J., & Simis, A. (2005). Does training in second-

language word recognition skills affect reading comprehension? An

experimental study. Modern Language Journal, 89(1), 54-75.

Generative Grammar. (2000). Oxford English dictionary. Retrieved

December 7, 2009, from http://dictionary.oed.com

Jackendoff, R. (2003). Foundations of language: Brain, meaning, grammar,

evolution. New York: Oxford University Press.

Jackendoff, R. (1977). X syntax : A study of phrase structure. Cambridge,

MA: MIT Press.

Keating, G. D. (2009). Sensitivity to violations of gender agreement in native

and nonnative Spanish: An eye-movement investigation. Language

Learning, 59(3), 503-535.

Kliegl, R., Nuthmann, A., & Engbert, R. (2006). Tracking the mind during

reading: The influence of past, present, and future words on fixation

durations. Journal of Experimental Psychology/General, 135(1), 12-35.


Koda, K. (2007). Reading and language learning: Crosslinguistic constraints

on second language reading development. Language Learning,

57(Supplement), 1-44.

Pinker, S. (1994). The language instinct: How the mind creates language.

New York: William Marrow, & Co.

Pinker, S. (1997). How the mind works. New York: Norton.

Pinker, S. (2002). The blank slate: The modern denial of human nature. New

York: Viking Adult.

Pinker, S. (2005). So how does the mind work? Mind and Language, 20(1),

1-24.

Pinker, S. (2007). The stuff of thought: Language as a window into human

nature. New York: Viking.

Pinker, S. (2005). A reply to Jerry Fodor on how the mind works. Mind and

Language, 20(1), 33-38.

Rayner, K. (1993). Eye movements in reading: Recent developments.

Current Directions in Psychological Science, 2(3), 81-85.

Rayner, K. (2009). Eye movements and attention in reading, scene

perception, and visual search. Quarterly Journal of Experimental

Psychology, 62(8), 1457-1506.

Rayner, K., Pollatsek, A., Drieghe, D., Slattery, T. J., & Reichle, E. D. (2007).

Tracking the mind during reading via eye movements: Comments on

Kliegl, Nuthmann, & Engbert (2006). Journal of Experimental

Psychology/General, 136(3), 520-529.


Rayner, K., Smith, T. J., Malcolm, G. L., & Henderson, J. M. (2009). Eye

movements and visual encoding during scene perception. Psychological

Science, 20(1), 6-10.

Reichle, E.D., Liversedge, S.P., Pollatsek, A., & Rayner, K. (2009). Encoding

multiple words simultaneously in reading is implausible. Trends in

Cognitive Sciences, 13(3), 115-119.

Reichle, E.D., Warren, T., & McConnell, K. (2009). Using E-Z reader to

model the effects of higher level language processing on eye movements

during reading. Psychonomic Bulletin and Review, 16(1), 1-21.

Reichle, E., Rayner, K., & Pollatsek, A. (2003). The E-Z reader model of eye-

movement control in reading: Comparisons to other models. Behavioral

and Brain Sciences, 26(4), 445-476.

Reichle, E. D. (2006). Computational models of eye-movement control

during reading: Theories of the eye mind link. Cognitive Systems

Research, 7(1), 2-3.

Skinner, B. F. (1992). Verbal behavior (Reprint, 1957 ed.). Acton, MA:

Copley Publishing Group.

Stuhr, J. J. (2000). Pragmatism and classical American philosophy: Essential

readings and interpretive essays. New York: Oxford University Press.

Tannen, D. (1999). The argument culture : Changing the way we argue and

debate. London: Virago.

Turing, A. M. (1950). Computing machinery and intelligence. Mind: A

Quarterly Review of Psychology and Philosophy, 59(236), 433.


Universal Grammar. (2000). Oxford English dictionary. Retrieved December

7, 2009, from http://dictionary.oed.com

Usó J., E., & Martínez F., A. (2006). Current trends in the development and

teaching of the four language skills. New York: M. de Gruyter.

Yamada, K. (2009). Lexical patterns in L2 textual gist identification

assessment. Language Testing, 26(1), 101-122.

a linguistics research paper

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