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The Generalist’s Corner

The Assessment of Rational Thinking: IQ ≠ RQ

Keith E. Stanovich1 and Richard F. West2

Variation in intelligence has been one of the most studied

topics in psychology for many decades (Geary, 2005; Hunt,

2011; Lubinski, 2004). Because people frequently assume that

assessments of intelligence (and similar tests of cognitive abil-

ity) are the quintessence of good thinking, one might assume

that such measures would serve as proxies for judgment and

decision-making skills. It is important to understand why such

an assumption would be misplaced.

Judgment and decision making are more properly regarded

as components of rational thinking, and people often fail to

recognize that rationality and intelligence (as traditionally

defined) are two different things. In scientific psychology,

intelligence definitions derive from performance on established

tests and cognitive ability indicators. Statistical study of this

performance yields a scientific concept of general intelligence,

usually symbolized by g; a concept of fluid intelligence (Gf);

and a concept of crystallized intelligence (Gc). The latter two

concepts refer to the Cattell/Horn/Carroll (CHC) theory of

intelligence—as close as there is to a consensus view in the

field of intelligence research (Carroll, 1993; Horn & Cattell,

1967). Sometimes called the theory of fluid and crystallized

intelligence (symbolized Gf/Gc theory), this theory posits that

tests of mental ability tap a small number of broad factors, of

which two are dominant. Gf reflects reasoning abilities operat-

ing across of variety of domains—in particular, novel ones. Gf

is measured by tasks of abstract reasoning such as figural ana-

logies, Raven Matrices, and series completion (e.g., What is the

next number in the series 1, 4, 5, 8, 9, 12, __?). Gc reflects

declarative knowledge acquired from acculturated learning

experiences and is measured by vocabulary tasks, verbal com-

prehension, and general knowledge measures. The two domi-

nant factors in the CHC theory reflect a long history of

considering two aspects of intelligence: intelligence as process

(Gf) and intelligence as knowledge (Gc). The IQ-test compo-

nents that measure Gf do not assess judgment and decision

making and neither do the IQ-test components that measure

Gc. In short, no components of currently popular IQ tests mea-

sure aspects of rationality.

Distinguishing between rationality and intelligence thus

helps explain how people can be, at the same time, intelligent

and irrational (Stanovich, 2009). As such, researchers need to

study separately the individual differences in cognitive skills

that underlie intelligence and the individual differences in

cognitive skills that underlie rational thinking because they are

conceptually and empirically different.

What IQ Tests Miss: Rational Thinking

Cognitive scientist Daniel Kahneman of Princeton University

won the 2002 Nobel Prize in Economics for research he con-

ducted with his longtime collaborator Amos Tversky (who died

in 1996). The press release for the award from the Royal Swed-

ish Academy of Sciences drew attention to the roots of their

award-winning work in ‘‘the analysis of human judgment and

decision-making by cognitive psychologists’’ (The Royal

Swedish Academy of Sciences, 2002a, 2002b). Kahneman was

cited for discovering:

how human judgment may take heuristic shortcuts that system-

atically depart from basic principles of probability. His work

has inspired a new generation of researchers in economics and

finance to enrich economic theory using insights from cognitive

psychology into intrinsic human motivation. (The Royal Swed-

ish Academy of Sciences, 2002a, 2002b)

One reason Kahneman and Tversky’s (1973, 1979, 2000) work

was so influential was because it addressed deep issues con-

cerning human rationality. As the Nobel announcement noted,

‘‘Kahneman and Tversky discovered how judgment under

uncertainty systematically departs from the kind of rationality

postulated in traditional economic theory’’ (The Royal Swedish

Academy of Sciences, 2002a, 2002b). The thinking errors

uncovered by Kahneman and Tversky are thus not trivial errors

in a parlor game. Rather, because being rational means acting

to achieve one’s own life goals using the best means possible,

making thinking errors has the practical consequence that

1 Department of Applied Psychology and Human Development, University of

Toronto, Toronto, Canada 2 James Madison University, Harrisonburg, VA, USA

Corresponding Author:

Keith E. Stanovich, Department of Applied Psychology and Human Develop-

ment, University of Toronto, 252 Bloor St. West, Toronto, Ontario Canada,

M5S 1V6.

Email: [email protected]

Teaching of Psychology 2014, Vol. 41(3) 265-271 ª The Author(s) 2014 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0098628314537988 top.sagepub.com

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people may be less satisfied with their lives than they might

otherwise be.

The work of Kahneman and Tversky, along with that of many

other investigators, has shown how the basic architecture of

human cognition makes everyone prone to these errors of judg-

ment and decision making. But being prone to these errors does

not mean that people always make them. Every person, at least

on some occasions, overrides the tendency to make these reason-

ing errors and instead makes a rational response. Even more

importantly, our research group has shown that there are systema-

tic differences among individuals in the tendency to make errors

of judgment and decision making (Stanovich, 2009, 2011; Stano-

vich & West, 2000; West, Toplak, & Stanovich, 2008).

The fact that there are systematic individual differences in

the judgment and decision-making situations studied by Kah-

neman and Tversky means that there are variations in important

attributes of human cognition related to rationality (Mankte-

low, 2004; Stanovich, 2009, 2011). It is a curious fact that none

of these critical attributes of human thinking are assessed on IQ

tests (or in proxies such as academic ability tests). This fact is

curious because most laypeople think that IQ tests measure

‘‘good’’ thinking (to put it colloquially). Moreover, scientists

and laypeople alike tend to agree that good thinking encom-

passes good judgment and decision making—the type of think-

ing that helps people achieve their goals. As such, one might

assume that IQ tests would include assessements of good think-

ing. Yet they do not.

To think rationally means taking appropriate action, given

one’s goals and beliefs (instrumental rationality); it also entails

holding beliefs that are commensurate with available evidence

(epistemic rationality). Collectively, the many tasks that mea-

sure heuristics (a mental shortcut) and biases (a tendency to

think a certain way) comprise the operational definition of

rationality found in much of modern cognitive science (Stano-

vich, 2011). Psychologists have extensively studied (see Baron,

2008) many aspects of instrumental rationality and irrational-

ity, including:

� the ability to display disjunctive reasoning in decision making;

� the tendency to show inconsistent preferences because of framing effects;

� the tendency to show a default bias; � the tendency to substitute affect for difficult evaluations; � the tendency to overweight short-term rewards at the

expense of long-term well-being;

� the tendency to have choices affected by vivid stimuli; � the tendency for decisions to be affected by irrelevant

context.

Likewise, psychologists have studied (see Baron, 2008)

aspects of epistemic rationality and irrationality, such as:

� the tendency to show incoherent probability assessments; � the tendency toward overconfidence in knowledge

judgments;

� the tendency to ignore base rates; � the tendency not to seek to falsify hypotheses; � the tendency to try to explain chance events; � the tendency toward self-serving personal judgments; � the tendency to evaluate evidence with a myside bias; � the tendency to ignore the alternative hypothesis.

In short, there is an extensive and rich set of operationaliza-

tions for the concept of rationality in modern cognitive science.

But, as noted previously, IQ tests do not include these mea-

sures, even though many people (including scientists) often talk

as if they do.

There is an important caveat, however (discussed exten-

sively in Stanovich, 2011). Although IQ tests fail to assess

rational thinking directly, one could argue that the processes

that these tests measure largely overlap with variation in

rational thinking ability. Perhaps intelligence is highly associ-

ated with rationality, although tasks measuring the latter are not

assessed directly on the tests. Here is where empirical research

comes in, some of which our research group has generated. We

have found that many rational thinking tasks show surprising

degrees of dissociation from intelligence in samples of college

students. Myside bias (processing information from an overly

egocentric perspective), for example, is virtually independent

of intelligence (Stanovich, West, & Toplak, 2013). Individuals

with higher IQs are no less likely to process information from

an egocentric perspective than individuals with relatively lower

IQs. Many classic effects from the heuristics and biases litera-

ture—base-rate neglect, framing effects, conjunction effects,

anchoring biases, and outcome bias—are also quite indepen-

dent of intelligence if analyzed using between-subject designs

(Stanovich & West, 2008). Researchers have also found corre-

lations with intelligence to be roughly (in absolute magnitude)

in the range of .20–.35 for probabilistic reasoning tasks and sci-

entific reasoning tasks measuring a variety of rational princi-

ples (covariation detection, hypothesis testing, four-card

selection task, disjunctive reasoning tasks, denominator

neglect, and various indices of Bayesian reasoning; see Bruine

de Bruin, Parker, & Fischhoff, 2007; Stanovich, 2009, 2011;

Stanovich & West, 1998, 2000, 2008). In fact, even after cor-

rections for reliability and range restriction, this magnitude of

correlation allows for substantial discrepancies between intelli-

gence and rationality. In short, high intelligence is no inocula-

tion against many of the sources of irrational thought.

Steps Toward an RQ Test: An Assessment Framework

To summarize, rationality is a mental quality that is theoreti-

cally and empirically separable from intelligence, and individ-

ual differences on IQ tests are not proxies for individual

differences in rational thinking. Thus, if one wants to assess

differences in rational thinking, one needs specifically to assess

the components of rational thought directly because an intelli-

gence quotient does not provide a RQ. At present, of course,

there is no IQ-type test for rationality—that is, there is not a test

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of one’s RQ. But researchers know the types of thinking pro-

cesses that such an instrument would assess, and they have in

hand prototypes of the kinds of tasks that would be used in the

domains of both instrumental rationality and epistemic ration-

ality. Thus, there are no major roadblocks preventing the devel-

opment of an RQ test. Indeed, this is what our research lab is

doing with the help of a 3-year grant from the John Templeton

Foundation. Specifically, we are attempting to construct the

first assessment instrument that will comprehensively measure

individual differences in rational thought.

Table 1 shows a conceptual structure for rational thought

that serves as our assessment framework. Specifically, rational

thought can be partitioned into fluid and crystallized compo-

nents by analogy to the fluid-crystallized theory of intelligence

discussed earlier (see Carroll, 1993). Fluid rationality encom-

passes the process part of rational thought—the thinking dispo-

sitions of the reflective mind that lead to rational thought and

action. Crystallized rationality encompasses the knowledge

structures that relate to rational thought.

Unlike fluid intelligence, though, fluid rationality is likely

multifarious—it is composed of a variety of different cognitive

styles and dispositions. As a multifarious concept, fluid ration-

ality cannot be assessed with a single type of item, for example,

in the same way that a more homogeneous test such as the

Raven Progressive Matrices can assess fluid intelligence.

Table 1 illustrates that the concept of crystallized rationality

has two subdivisions: crystallized facilitators, which are knowl-

edge structures that promote rational thought (e.g., knowledge of

probability), and crystallized inhibitors, which are knowledge

structures that impede rational thought (e.g., belief in astrology).

Each of these subcategories of crystallized rationality is, like

fluid rationality, multifarious. Without learning crystallized

faciltators, people will lack declarative knowledge that is neces-

sary in order to act rationally. However, not all crystallized

knowledge is helpful, either to attaining our goals (instrumental

rationality) or to having accurate beliefs (epistemic rational-

ity)—hence the category of crystallized inhibitors.

Importantly, one should not mistake the information in

Table 1 for the lists of ‘‘good thinking styles’’ that often appear

in textbooks on critical thinking. In terms of providing a basis

for a system of rational thinking assessment, it goes consider-

ably beyond such lists in a number of ways. First, unlike the

many committee-like attempts to develop feature lists of criti-

cal thinking skills, our conceptual components are grounded in

tasks that have been extensively researched (see Stanovich,

2011; Stanovich, West, & Toplak, 2011). Second, many text-

book attempts at lists of good thinking styles deal only with

aspects of fluid rationality and give short shrift to the crystal-

lized knowledge bases that are necessary supports for rational

thought and action. In contrast, our framework for rationality

assessment emphasizes that crystallized knowledge underlies

much rational responding (crystallized facilitators) and that

crystallized knowledge can also be the direct cause of irrational

behavior (crystallized inhibitors).

Even more important than these points, and unlike many

such lists of thinking skills in textbooks, the conceptual compo-

nents of the fluid characteristics and crystallized knowledge

bases listed in Table 1 are each grounded in established para-

digms of cognitive science. That is, they are not just potentially

measurable but in fact have been operationalized and measured

at least once in the scientific literature—and in many cases,

they have generated enormous empirical literatures. For exam-

ple, there are many paradigms that researchers have used to

measure resistance to miserly information processing, the first

major dimension of fluid rationality in Table 1. The study of

belief bias—that people have difficulty processing data point-

ing toward conclusions that conflict with what they think they

know about the world—has yielded many such items (e.g.,

Evans & Curtis-Holmes, 2005). Another is Frederick’s

(2005) Cognitive Reflection Test, which measures miserly pro-

cessing and has been studied extensively (Toplak, West, & Sta-

novich, 2011, 2014). The most famous item on this test reads:

A bat and a ball cost $1.10 in total. The bat costs $1 more than

the ball. How much does the ball cost? When they answer this

Table 1. Rational Thinking Skills in the Stanovich and West Framework.

Components of Rationality

Crystallized Rationality

Fluid Rationality Crystallized Facilitators Crystallized Inhibitors

Resistance to miserly information processing Probabilistic and statistical reasoning Belief in the paranormal and in intuition Absence of irrelevant context effects in decision

making Practical numeracy

Sensitivity to expected value Risk knowledge Value placed on ungrounded knowledge sources

Proper knowledge calibration: avoiding overconfidence

Knowledge of scientific reasoning Overreliance on introspection

Avoidance of myside bias Financial literacy and economic thinking

Dysfunctional personal beliefs

Openminded/objective reasoning styles Prudent attitude toward the future Sensitivity to emotions

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problem, many people give the first response that comes to

mind—10 cents—without thinking further and realizing that

this cannot be correct. The bat would then have to cost

$1.10, and the total cost would be US$1.20 rather than the

required $1.10. People often do not think deeply enough to

realize their error, and cognitive ability is no guarantee against

making the error. Frederick (2005) found that large numbers of

highly select university students at Massachusetts Institute of

Technology, Princeton, and Harvard were cognitive misers—

they responded that the cost was 10 cents, rather than the cor-

rect answer: 5 cents.

Good decision making is in part defined by decisions that

are not unduly affected by irrelevant context (the second major

dimension of fluid rationality). Two paradigms that assess this

tendency have each generated enormous literatures. Resistance

to framing has been measured with countless tasks (Maule &

Villejoubert, 2007) as has the resistance to irrelevant anchoring

in decisions (e.g., Epley & Gilovich, 2004, 2006).

As a final example of an area of rational thinking with a

dense history of empirical research and with paradigms that

could serve as assessment devices, consider the tendency to

conform, qualitatively, to the insights of normative decision

theory—the third major dimension of fluid rationality (sensi-

tivity to expected value). Since the early 1950s (see Edwards,

1954), psychologists have studied the tendency to adhere to the

axioms of expected utility theory with a variety of tasks and

paradigms (e.g., Baron, 2008; Kahneman & Tversky, 2000).

Many crystallized facilitators have been extensively studied

as well. For example, assigning the right probability values to

events is a critical aspect of rational thought. It is involved, for

example, in medical diagnosis. Consider the following problem

on which both medical personnel and laypersons frequently

make a critical thinking error:

Imagine that the XYZ virus causes a serious disease that

occurs in 1 of every 1,000 people. Imagine also that there is

a test to diagnose the disease that always indicates correctly

that a person who has the XYZ virus actually has it. Finally,

imagine that the test has a false-positive rate of 5%—the test wrongly indicates that the XYZ virus is present in 5% of the cases where it is not. Imagine that we choose a person ran-

domly and administer the test and that it yields a positive result

(i.e., it indicates that the person is XYZ positive). What is the

probability that the individual actually has the XYZ virus?

The point is not to get the precise answer; rather, the point is

to see whether a guess is in the right ballpark. The answers of

many people are not. The most common answer given is 95%. Actually, the correct answer is approximately 2%! Why? Of 1,000 people, just one will actually be XYZ positive. If the

other 999 are tested, the test will indicate incorrectly that

approximately 50 of them have the virus (.05 multiplied by

999) because of the 5% false-positive rate. Thus, of the 51 patients testing positive, only 1 (approximately 2%) will actu- ally be XYZ positive. In short, the base rate is such that the vast

majority of people do not have the virus. This fact, combined

with a substantial false-positive rate, ensures that, in absolute

numbers, the majority of positive tests will be of people who

do not have the virus. Rational thinking errors due to such

knowledge gaps can occur in a potentially large set of coherent

knowledge bases in the domains of probabilistic reasoning,

causal reasoning, practical numeracy, financial literacy, and

scientific thinking (e.g., the importance of alternative hypoth-

eses). In other publications (e.g., Stanovich, 2011), we have

provided numerous examples of tasks like this that measure

each of the rational thinking concepts in Table 1.

Future Directions

Our framework illustrates the basis for our position that there is

no conceptual barrier to creating a test of rational thinking.

However, this does not mean that it would be logistically easy.

Quite the contrary, we have stressed that both fluid and crystal-

lized rationality are likely to be more multifarious than their

analogous intelligence constructs. Likewise, we are not claim-

ing that there presently exist comprehensive assessment

devices for each of these components. Indeed, refining and

scaling up many of the small-scale laboratory demonstrations

in the literature will be a main task of our future research. Our

present claim is only that, in virtually every case, laboratory

tasks that have appeared in the published literature give us, at

a minimum, a hint at what comprehensive assessment of the

particular component would look like.

The ability to measure individual differences in rational

thinking could have profound social consequences. For exam-

ple, in a recently published book (Stanovich, 2011), we dis-

cussed how each of the subcomponents of rational thought

has been linked to real-life outcomes of practical importance.

In the absence of space to explicate all of the linkages, let us

just give a few examples: physicians choose less effective med-

ical treatments; people fail to accurately assess risks in their

environment; information is misused in legal proceedings; mil-

lions of dollars are spent on unneeded projects by government

and private industry; parents fail to vaccinate their children;

unnecessary surgery is performed; billions of dollars are

wasted on quack medical remedies; and costly financial mis-

judgments are made (Baron, 2008; Hilton, 2003; Stanovich,

2004, 2009). Moreover, suboptimal investment decisions have

been linked to overconfidence in knowledge judgments, the

tendency to overexplain chance events, and the tendency to

substitute affective valence for thought—all of which are com-

ponents of our rational thinking test. Errors in medical decision

making and legal decision making have also been linked to spe-

cific irrational thinking tendencies that we will assess in our

instrument. And it is critically important to state, once again,

that intelligence provides insufficient inoculation against these

thinking errors and their negative consequences.

Enhancement of Rational Thinking

Although the basic architecture of human cognition makes us

all prone to judgment and decision-making errors, knowledge

about the processes that underlie these errors and the situations

that make them likely can serve as a pedagogical guide. There

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is no reason why we must live with this status quo. We can do

better. We can acquire strategies and habits that make our judg-

ments and decisions less error prone. By so doing, we can

increase the likelihood of achieving our goals and improving

the veracity of our beliefs. Insight about the types of errors that

we are likely to make can reduce our natural tendency to be

unduly overconfident about the quality of our judgments. It can

motivate us to cultivate effective habits like that of approaching

problems, particularly problems that are important to us, in a

flexible and reflective fashion.

Our thinking is vulnerable to a variety of irrational fram-

ing effects. For example, many people are willing to pay

more for hamburger meat labeled 94% fat free than for the same meat when labeled 6% fat. Many physicians are more likely to recommend a life-extending surgical procedure for

cancer patients who are described as having a 1-month sur-

vival rate of 90% than the same procedure when it is described as having a 1-month mortality rate of 10%. Knowledge of the extent to which we are susceptible to

being unduly affected by irrelevant framing and context can

motivate the development of the productive habit of routi-

nely examining options from multiple frames or perspec-

tives. Decision making can improve by employing the

simple strategy of reminding yourself to ‘‘think/consider the

opposite.’’

A lack of knowledge of scientific and probabilistic think-

ing accounts for much potentially avoidable irrational think-

ing. Educational experiences that emphasize the importance

of using control groups, exploring and testing alternative

hypotheses, and looking for falsifying information are impor-

tant. Without knowledge of basic probability theory, people

routinely make strikingly poor decisions about probabilistic

situations. Even individuals with substantial sophistication

about probability can slip into a cognitive miserly style of

thinking that results in their being remarkably insensitive to

important factors such as sample size and regression to the

mean. Educational experiences that cultivate a practical

understanding of basic probabilistic thinking can be invalu-

able. It is also important to cultivate an awareness of the need

to avoid miserly thinking about probability and randomness

so that acquired probabilistic knowledge will actually be used

effectively.

Both medical personnel and laypeople often make drama-

tically inaccurate estimations of the likelihood that an indi-

vidual has a disease, when given information about a

diagnostic test’s correct positive rate, its false-positive rate,

and the disease’s incidence (i.e., its base rate). Learning

about the importance of overcoming the tendency to ignore

base-rate information and how to reason in a Bayesian fash-

ion has the potential to dramatically improve the accuracy

of these types of decisions. Augmentation of classroom dis-

cussions with graphical depictions of problems can be very

helpful. Table 2 shows a graphical depiction of the XYZ

problem discussed earlier to demonstrate how the elements

in a diagnostic problem can be made relatively transparent

for Bayesian reasoning.

Teachers can also find a more detailed discussion of ways to

enhance rational thinking in Chapter 10 of Stanovich (2011). In

addition, a chapter by Toplak, West, and Stanovich (2012)

describes a wide variety of efforts to train and improve various

different components of rational thinking. Table 4.1 in Toplak

et al.’s (2012) chapter also includes a list of several relevant

empirical studies.

Conclusions

When a layperson thinks of individual differences in reason-

ing, he or she often thinks of IQ tests. This thinking is quite

natural because IQ tests are among the most publicized

products of psychological research. This association is not

entirely inaccurate either because intelligence is correlated

with performance on a host of reasoning tasks (Carroll,

1993; Deary, 2000; Hunt, 2011). Nonetheless, certain

important classes of individual differences in thinking are

ignored if only intelligence-related variance is the primary

focus. A number of these ignored classes of individual dif-

ferences are those relating to rational thought.

Table 2. A Graphical Depiction of the XYZ Problem Demonstrating How the Elements in Diagnostic Problem Can Be Made Relatively Trans- parent for Bayesian Reasoning.

Base Rate of XYZ Virus 1 in 1,000 People

1 Has Virus 999 Do Not Have Virus

Correct Positives False Negative False Positives Correct Negatives

100% of 1 0% of 1 5% of 999 95% of 999 1 Correct positives (0 False negatives) * 50 False positives (* 950 Correct negatives)

You know that the test result is positive. Is this positive a correct positive or a false positive? How many correct positives and false positives you would expect if 1,000 people were tested? 1 Correct positive (has virus) þ 50 False positives (not have virus) 51 Total positives 1 Correct positive/51 total positives ¼ .02 or 2% chance a correct positive (has XYZ virus)

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We tend not to notice the mental processes that are missing

from IQ tests because many theorists have adopted a permissive

conceptualization of what intelligence is rather than a grounded

conceptualization. Permissive theories include aspects of func-

tioning that are captured by the vernacular term ‘‘intelligence’’

(e.g., adaptation to the environment, showing wisdom, creativity,

and so on), despite the fact that existing tests of intelligence do not

measure these aspects. Grounded theories, in contrast, confine the

concept of intelligence to the set of mental abilities actually tested

on extant IQ tests. Adopting permissive definitions of the concept

of intelligence serves to obscure what is missing from extant IQ

tests. Instead, in order to highlight the missing elements in IQ

tests, we adopt a thoroughly grounded notion of the intelligence

concept.

Grounded theories adopt the operationalization of the

term that is used in psychometric studies of intelligence,

neurophysiological studies using brain imaging, and studies

of brain disorder. This definition involves a statistical

abstraction from performance on established tests and cog-

nitive ability indicators. The grounded view of intelligence

then takes the operationally defined construct and validates

it in studies of brain injury, educational attainment, cogni-

tive neuroscience, developmental trends, and information

processing.

The operationalization of rationality is different from that

of intelligence and thus, as every introductory psychology

student is taught, the concepts must be treated differently.

Our comprehensive test of rational thinking will go a long

way toward grounding the rationality concept—a concept

that captures aspects of thought that have heretofore gone

unmeasured.

In summary, we have coherent and well-operationalized

concepts of rational action and belief formation. We also have

a coherent and well-operationalized concept of intelligence.

No scientific purpose is served by fusing these concepts

because they are very different. To the contrary, differentiat-

ing the concepts will result in scientific progress. We have a

decade-long history of measuring the intelligence concept.

It is high time we put equal energy, as a discipline, into the

measurement of a mental quality that is just as important—

rationality.

Authors’ Note

The opinions expressed in this publication are those of the authors and

do not necessarily reflect the views of the John Templeton Foundation.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to

the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for

the research, authorship, and/or publication of this article: Prepara-

tion of this article was supported by a grant from the John Templeton

Foundation.

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Author Biographies

Keith Stanovich is an emer-

itus professor of applied

psychology and human devel-

opment at the University of

Toronto. He is the author of

over 200 scientific articles

and seven books. Stanovich’s

book, What Intelligence Tests

Miss, received the 2010 Gra-

wemeyer Award in Education.

His introductory textbook, How

to Think Straight About Psy-

chology, published by Allyn &

Bacon, is in its 10th edition and

has been adopted by over 400

institutions of higher education.

He is the recipient of the 2012 E. L. Thorndike Career Achievement

Award from the American Psychological Association.

Richard F. West is an emeritus

professor in the Department of

Graduate Psychology at James

Madison University. He has

been collaborating with Keith

Stanovich continuously since

1974. He is the author of over

80 scientific articles in various

areas of psychology and cogni-

tive science. Thirty-three of his

articles have received over 50

citations, 19 have received over

100 citations, and 9 articles have

been cited over 200 times. He is

the coauthor of a target article in

Behavioral and Brain Sciences that has been cited over 700 times in ISI

Web of Knowledge and over 1,700 times in Google Scholar. West is one

of only two faculty at James Madison University to have received the uni-

versity’s Madison Scholar Award twice. He has served on various editorial

boards and has reviewed for dozens of journals and granting agencies. His

current research is supported by a grant from the John Templeton

Foundation.

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