Chapter 8 explores thought, language and knowledge organization

Chapter 8 Thought and
Language
8.1 The Organization of Knowledge
Concepts and Categories 315
Working the Scientific Literacy Model: Priming and Semantic
Networks
318
Module 8.1a Quiz 319
Memory, Culture, and Categories 319
Module 8.1b Quiz 323
Module 8.1 Summary 323
8.2 Problem Solving, Judgment, and Decision Making
Defining and Solving Problems 325
Judgment and Decision Making 328
Working the Scientific Literacy Model: Maximizing and
Satisficing in
Complex Decisions 332

8.3 Language and Communication
What Is Language? 337
The Development of Language 341
Genes, Evolution, and Language 344
Working the Scientific Literacy Model: Genes and Language
344
Module 8.3c Quiz 348
Module 8.1 The Organization of
Knowledge
Dmitry Vereshchagin/Fotolia
Learning Objectives
Know . . . the key terminology associated with concepts and
categories.
Understand . . . theories of how people organize their

knowledge about
the world.
Understand . . . how experience and culture can shape the way
we
organize our knowledge.
Apply . . . your knowledge to identify prototypical examples.
8.1a
8.1b
8.1c
8.1d
When Edward regained consciousness in the hospital, his family
immediately noticed that something was wrong. The most
obvious
problem was that he had difficulty recognizing faces, a
relatively common
disorder known as prosopagosia. As the doctors performed more
testing,
it became apparent that Edward had other cognitive problems as
well.
Edward had difficulty recognizing objects—but not all objects.
Instead, he
couldn’t distinguish between different vegetables even though
he could
use language to describe their appearance. His ability to
recognize most
other types of objects seemed normal.
Neurological patients like Edward may seem unrelated to your
own life.
However, for specific categories of visual information to be

lost, they must
have been stored in similar areas of the brain before brain
damage
occurred. Therefore, these cases give us some insight into how
the brain
stores and organizes the information that we have encoded into
memory.
Focus Questions
1. How do people form easily recognizable categories from
complex
information?
2. How does culture influence the ways in which we categorize
information?
Each of us has amassed a tremendous amount of knowledge in
the course of
our lifetime. Indeed, it is impossible to put a number on just
how many facts each
of us knows. Imagine trying to record everything you ever
learned about the
world—how many books could you fill? Instead of asking how
much we know,
psychologists are interested in how we keep track of it all. In
this module, we will
explore what those processes are like and how they work. We
will start by
learning about the key terminology before presenting theories
about how
Analyze . . . the claim that the language we speak determines
how we
think.

8.1e
knowledge is stored over the long term.
Concepts and Categories
A concept is the mental representation of an object, event, or
idea. Although
it seems as though different concepts should be distinct from
each other, there
are actually very few independent concepts. You do not have
just one concept
for chair, one for table, and one for sofa. Instead, each of these
concepts can be
divided into smaller groups with more precise labels, such as
arm chair or coffee
table. Similarly, all of these items can be lumped together under
the single label,
furniture. Psychologists use the term categories to refer to
these clusters of
interrelated concepts. We form these groups using a process
called
categorization.
Classical Categories: Definitions and Rules
Categorization is difficult to define in that it involves elements
of perception
(Chapter 4 ), memory (Chapter 7 ), and “higher-order”
processes like
decision making (Module 8.2 ) and language (Module 8.3 ). The
earliest

approach to the study of categories is referred to as classical
categorization ; this theory claims that objects or events are
categorized
according to a certain set of rules or by a specific set of
features—something
similar to a dictionary definition (Lakoff & Johnson, 1999;
Rouder & Ratcliffe,
2006). Definitions do a fine job of explaining how people
categorize items, at
least in certain situations. For example, a triangle can be
defined as “a figure
(usually, a plane rectilinear figure) having three angles and
three sides” (Oxford
English Dictionary, 2011). Using this definition, you should
find it easy to
categorize the triangles in Figure 8.1 .
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Figure 8.1 Using the Definition of a Triangle to Categorize
Shapes
Classical categorization does not tell the full story of how
categorization works,
however. We use a variety of cognitive processes in determining
which objects fit

which category. One of the major problems we confront in this
process is graded
membership —the observation that some concepts appear to
make better
category members than others. For example, see if the definition
in Table 8.1
fits your definition of bird and then categorize the items in the
table.
Table 8.1 Categorizing Objects According to the Definition of
Bird
Definition: “Any of the class Aves of warm-blooded, egg-
laying, feathered vertebrates
with forelimbs modified to form wings.” (American Heritage
Dictionary, 2016)
Now categorize a set of items by answering yes or no regarding
the truth of the
following sentences.
1. A sparrow is a bird.
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2. An apple is a bird.
3. A penguin is a bird.
Ideally, you said yes to the sparrow and penguin, and no to the
apple. But did
you notice any difference in how you responded to the sparrow
and penguin?
Psychologists have researched classical categorization using a
behavioural
measure known as the sentence-verification technique, in which
volunteers wait
for a sentence to appear in front of them on a computer screen
and respond as
quickly as they can with a yes or no answer to statements such
as “A sparrow is
a bird,” or, “A penguin is a bird.” The choice the participant
makes, as well as her
reaction time to respond, is measured by the researcher.
Sentence-verification
shows us that some members of a category are recognized faster
than others
(Olson et al., 2004; Rosch & Mervis, 1975). In other words,
subjects almost
always answer “yes” faster to sparrow than to penguin. This
seems to go against
a classical, rule-based categorization system because both
sparrows and
penguins are equally good fits for the definition, but sparrows
are somehow

perceived as being more bird-like than penguins. Thus, a
modern approach to
categorization must explain how “best examples” influence how
we categorize
items.
Prototypes: Categorization by Comparison
When you hear the word bird, what mental image comes to
mind? Does it
resemble an ostrich? Or is your image closer to a robin,
sparrow, or blue jay?
The likely image that comes to mind when you imagine a bird is
what
psychologists call a prototype (see Figure 8.2 ). Prototypes are
mental
representations of an average category member (Rosch, 1973).
If you took an
average of the three most familiar birds, you would get a
prototypical bird.
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Figure 8.2 A Prototypical Bird
Left: chatursunil/Shutterstock; centre: Al Mueller/Shutterstock;
right:
Leo/Shutterstock
Prototypes allow for classification by resemblance. When you
encounter a little
creature you have never seen before, its basic shape—maybe
just its silhouette
—can be compared to your prototype of a bird. A match will
then be made and
you can classify the creature as a bird. Notice how different this
process is from
classical categorization: No rules or definitions are involved,
just a set of
similarities in overall shape and function.
The main advantage of prototypes is that they help explain why
some category
members make better examples than others. Ostriches are birds
just as much as
blue jays are, but they do not resemble the rest of the family
very well. In other
words, blue jays are closer to the prototypical bird.
Now that you have read about categories based on a set of rules
or
characteristics (classical categories) and as a general
comparison based on
resemblances (prototypes), you might wonder which approach is
correct.

Research says that we can follow either approach—the choice
really depends on
how complicated a category or a specific example might be. If
there are a few
major distinctions between items, we use resemblance; if there
are
complications, we switch to rules (Feldman, 2003; Rouder &
Ratcliff, 2004,
2006). For example, in the case of seeing a bat dart by, your
first impression
might be “bird” because it resembles a bird. But if you
investigated further, you
will see that a bat fits the classical description of a mammal,
not a bird. In other
words, it has hair, gives live birth rather than laying eggs, and
so on.
Networks and Hierarchies
Classical categorization and prototypes only explain part of how
we organize
information. Each concept that we learn about has similarities
to other concepts.
A sparrow has physical similarities to a bat (e.g., size and
shape); a sparrow will
have even more in common with a robin because they are both
birds (e.g., size,
shape, laying eggs, etc.). These connections among ideas can be
represented in
a network diagram known as a semantic network , an
interconnected set of
nodes (or concepts) and the links that join them to form a

category (see Figure
8.3 ). Nodes are circles that represent concepts, and links
connect them
together to represent the structure of a category as well as the
relationships
among different categories (Collins & Loftus, 1975). In these
networks, similar
items have more, and stronger, connections than unrelated
items.
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Figure 8.3 A Semantic Network Diagram for the Category
“Animal”
The nodes include the basic-level categories, Bird and Fish.

Another node
represents the broader category of Animal, while the lowest
three nodes
represent the more specific categories of Robin, Emu, and
Trout.
Source: Based on Collins, A. M., & Quillian, M. R. (1969).
Retrieval time from semantic memory. Journal of Verbal
Learning
and Verbal Behavior, 8, 240–248.
Something you may notice about Figure 8.3 is that it is
arranged in a
hierarchy—that is, it consists of a structure moving from
general to very specific.
This organization is important because different levels of the
category are useful
in different situations. The most frequently used level, in both
thought and
language, is the basic-level category, which is located in the
middle row of the
diagram (where birds and fish are) (Johnson & Mervis, 1997;
Rosch et al.,
1976). A number of qualities make the basic-level category
unique:
Basic-level categories are the terms used most often in
conversation.
They are the easiest to pronounce.
They are the level at which prototypes exist.
They are the level at which most thinking occurs.
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To get a sense for how different category levels influence our
thinking, we can
compare sentences referring to an object at different levels.
Consider what would
happen if someone approached you and made any one of the
following
statements:
There’s an animal in your yard.
There’s a bird in your yard.
There’s a robin in your yard.
The second sentence—”There’s a bird in your yard”—is
probably the one you
are most likely to hear, and it makes reference to a basic level
of a category
(birds). Many people would respond that the choice of animal as
a label indicates
confusion, claiming that if the speaker knew it was a bird, he
should have said
so; otherwise, it sounds like he is trying to figure out which
kind of animal he is
looking at. Indeed, superordinate categories like “animal” are

generally used
when someone is uncertain about an object or when he or she
wishes to group
together a number of different examples from the basic-level
category (e.g.,
birds, cats, dogs). In contrast, when the speaker identifies a
subordinate-level
category like robin, it suggests that there is something special
about this
particular type of bird. It may also indicate that the speaker has
expert-level
knowledge of the basic category and that using the more
specific level is
necessary to get her point across in the intended way.
In order to demonstrate the usefulness of semantic networks in
our attempt to
explain how we organize knowledge, complete this easy test
based on the
animal network in Figure 8.3 . If you were asked to react to
dozens of
sentences, and the following two sentences were included
among them, which
do you think you would mark as “true” the fastest?
A robin is a bird.
A robin is an animal.
As you can see in the network diagram, robin and bird are
closer together; in
fact, to connect robin to animal, you must first go through bird.
Sure enough,

people regard the sentence “A robin is a bird” as a true
statement faster than “A
robin is an animal.”
Now consider another set of examples. Which trait do you think
you would verify
faster?
A robin has wings.
A robin eats.
Using the connecting lines as we did before, we can predict that
it would be the
first statement about wings. As research shows, our guess would
be correct.
These results demonstrate that how concepts are arranged in
semantic networks
can influence how quickly we can access information about
them.
Working the Scientific Literacy Model Priming
and Semantic Networks
The thousands of concepts and categories in long-term memory
are not isolated, but connected in a number of ways. What are
the consequences of forming all the connections in semantic
networks?
What do we know about semantic networks?
In your daily life, you notice the connections within semantic
networks anytime you encounter one aspect of a category and
other related concepts seem to come to mind. Hearing the word
“fruit,” for example, might lead you to think of an apple, and
the
apple may lead you to think of a computer, which may lead you

to
think of a paper that is due tomorrow. These associations
illustrate the concept of priming —the activation of individual
concepts in long-term memory. Interestingly, research has
shown
that priming can also occur without your awareness; “fruit” may
not have brought the image of a watermelon to mind, but the
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concept of a watermelon may have been primed nonetheless.
How can science explain priming effects?
Psychologists can test for priming through reaction time
measurements, such as those in the sentence verification tasks
discussed earlier or through a method called the lexical decision
task. With the lexical decision method, a volunteer sits at a
computer and stares at a focal point. Next, a string of letters
flashes on the screen. The volunteer responds yes or no as
quickly as possible to indicate whether the letters spell a word
(see Figure 8.4 ). Using this method, a volunteer should
respond faster that “apple” is a word if it follows the word
“fruit”
(which is semantically related) than if it follows the word “bus”
(which is not semantically related).
Figure 8.4 A Lexical Decision Task

In a lexical decision task, an individual watches a computer
screen as strings of letters are presented. The participant must
respond as quickly as possible to indicate whether the letters
spell a word (e.g., “desk”) or are a non-word (e.g., “sekd”).
Given that lexical decision tasks are highly controlled
experiments, we might wonder if they have any impact outside
of
the laboratory. One test by Jennifer Coane suggests that priming
does occur in everyday life (Coane & Balota, 2009). Coane’s
research team invited volunteers to participate in lexical
decision
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tasks about holidays at different times of the year. The words
they chose were based on the holiday season at that time. Sure
enough, without any laboratory priming, words such as
“nutcracker” and “reindeer” showed priming effects at times
when
they were congruent (or “in season”) in December, relative to
other times of the year (see Figure 8.5 ). Similarly, words like
“leprechaun” and “shamrock” showed a priming effect during
the
month of March. Because the researchers did not instigate the
priming, it must have been the holiday spirit at work:
Decorations
and advertisements may serve as constant primes.
Figure 8.5 Priming Affects the Speed of

Responses on a Lexical Decision Task
Average response times were faster when the holiday-themed
words were congruent (in season), as represented by the blue
bars. This finding is consistent for both the first half and the
second half of the list of words.
Source: Republished with permission of Springer, from Priming
the Holiday Spirit: Persistent
Activation due to Extraexperimental Experiences Fig. 1,
Pg.1126, Psychonomic Bulletin & Review, 16
(6), 1124–1128, 2009. Permission conveyed through Copyright
Clearance Center, Inc.
Can we critically evaluate this information?
Priming influences thought and behaviour, but is certainly not
all-
powerful. In fact, it can be very weak at times. Because the
strength of priming can vary a great deal, some published
experiments have been very difficult to replicate—an important
criterion of quality research. So, while most psychologists agree
that priming is an important area of research, there have been
very open debates at academic conferences and in peer-
reviewed journals about the best way to conduct the research
and how to interpret the results (Cesario, 2014; Klatzky &
Creswell, 2014).
Why is this relevant?
Advertisers know all too well that priming is more than just a
curiosity; it can be used in a controlled way to promote specific

behaviours. For example, cigarette advertising is not allowed on
television stations, but large tobacco companies can sponsor
anti-smoking ads. Why would a company advertise against its
own product? Researchers brought a group of smokers into the
lab to complete a study on television programming and subtly
included a specific type of advertisement between segments
(they did not reveal the true purpose of the study until after it
was
completed). Their participants were four times as likely to light
up
after watching a tobacco-company anti-smoking ad than if they
saw the control group ad about supporting a youth sports league
(Harris et al., 2013). It would appear that while the verbal
message is “don’t smoke,” the images actually prime the
behaviour. Fortunately, more healthful behaviours have been
promoted through priming; for example, carefully designed
primes have been shown to reduce mindless snacking (Papies &
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Hamstra, 2010) and binge-drinking in university students
(Goode
et al., 2014).
Module 8.1a Quiz:
Concepts and Categories
Know . . .
1. A is a mental representation of an average member
of a
category.
A. subordinate-level category
B. prototype
C. similarity principle
D. network
2. refer to mental representations of objects, events,
or ideas.
A. Categories
B. Concepts
C. Primings
D. Networks
Understand . . .
3. Classical categorization approaches do not account for
, a type

of categorization that notes some items make better category
members
than others.
A. basic-level categorization
B. prototyping
C. priming
D. graded membership
Memory, Culture, and Categories
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In the first part of this module, we examined how we group
together concepts to
form categories. However, it is important to remember that
these processes are
based, at least in part, on our experiences. In this section of the
module, we
examine the role of experience—both in terms of memory
processes and cultural
influences—on our ability to organize our vast stores of
information.

Categorization and Experience
People integrate new stimuli into categories based on what they
have
experienced before (Jacoby & Brooks, 1984). When we
encounter a new item,
we select its category by retrieving the item(s) that are most
similar to it from
memory (Brooks, 1978). Normally, these procedures lead to fast
and accurate
categorization. If you see an animal with wings and a beak, you
can easily
retrieve from memory a bird that you previously saw; doing so
will lead you to
infer that this new object is a bird, even if it is a type of bird
that you might not
have encountered before.
However, there are also times when our reliance on previ ously
experienced
items can lead us astray. In a series of studies with medical
students and
practising physicians, Geoffrey Norman and colleagues at
McMaster University
found that recent exposure to an example from one category can
bias how
people diagnose new cases (Leblanc et al., 2001; Norman,
Brooks, et al.,
1989; Norman, Rosenthal, et a., 1989). In one experiment,
medical students
were taught to diagnose different skin conditions using written
rules as well as
photographs of these diseases. Some of the photographs were

typical examples
of that disorder whereas other photographs were unusual cases
that resembled
other disorders. When tested later, the participants were more
likely to rely on
the previously viewed photographs than they were on the rules
(a fact that would
surprise most medical schools); in fact, the unusual photographs
viewed during
training even led to wrong diagnoses for test items that were
textbook examples
of that disorder (Allen et al., 1992)! This shows the power that
our memory can
have on how we take in and organize new information. As an
aside, expert
physicians were accurate over 90% of the time in most studies,
so you can still
trust your doctor.
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Categories, Memory, and the Brain
The fact that our ability to make categorical decisions is
influenced by previous
experiences tells us that this process involves memory. Studies
of neurological
patients like the man discussed at the beginning of this module
provide a unique
perspective on how these memories are organized in the brain.
Some patients
with damage to the temporal lobes have trouble identifying
objects such as
pictures of animals or vegetables despite the fact that they were
able to describe
the different shapes that made up those objects (i.e., they could
still see). The
fact that these deficits were for particular categories of objects
was intriguing, as
it suggested that damaging certain parts of the brain could
impair the ability to
recognize some categories while leaving others unaffected

(Warrington &
McCarthy, 1983; Warrington & Shallice, 1979). Because these
problems were
isolated to certain categories, these patients were diagnosed as
having a
disorder known as category specific visual agnosia (or CSVA).
Early attempts to find a pattern in these patients’ deficits
focused on the
distinction between living and non-living categories (see Figure
8.6 ). Several
patients with CSVA had difficulties identifying fruits,
vegetables, and/or animals
but were still able to accurately identify members of categories
such as tools and
furniture (Arguin et al., 1996; Bunn et al., 1998). However,
although CSVA has
been observed in a number of patients, researchers also noted
that it would be
physically impossible for our brains to have specialized regions
for every
category we have encountered. There simply isn’t enough space
for this to
occur. Instead, they proposed that evolutionary pressures led to
the development
of specialized circuits in the brain for a small group of
categories that were
important for our survival. These categories included animals,
fruits and

vegetables, members of our own species, and possibly tools
(Caramazza &
Mahon, 2003). Few, if any, other categories involve such
specialized memory
storage. This theory can explain most, but not all, of the
problems observed in
the patients tested thus far. It is also in agreement with brain-
imaging studies
showing that different parts of the temporal lobes are active
when people view
items from different categories including animals, tools, and
people (Martin et
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al., 1996). Thus, although different people will vary in terms of
the exact location
that these categories are stored, it does appear that some
categories are stored
separately from others.
Figure 8.6 Naming Errors for a CSVA Patient
Patients with CSVA have problems identifying members of
specific categories.
When asked to identify the object depicted by different line
drawings, patient E.
W. showed a marked impairment for the recognition of animals.
Her ability to
name items from other categories demonstrated that her overall
perceptual
abilities were preserved.
Source: Based on data from Caramazza, A., & Mahon, B. Z.
(2003). The organization of conceptual knowledge: the evidence
from category-specific semantic deficits. Trends in Cognitive
Sciences, 7 (8), 354–361.
Biopsychosocial Perspectives Culture and
Categorical Thinking
Animals, relatives, household appliances, colours, and other
entities all
fall into categories. However, people from different cultures
might differ in
how they categorize such objects. In North America, cows ar e
sometimes
referred to as “livestock” or “food animals,” whereas in India,

where cows
are regarded as sacred, neither category would apply.
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In addition, how objects are related to each other differs
considerably
across cultures. Which of the two photos in Figure 8.7 a do you
think
someone from North America took? Researchers asked both
American
and Japanese university students to take a picture of someone,
from
whatever angle or degree of focus they chose. American
students were
more likely to take close-up pictures, whereas Japanese students
typically included surrounding objects (Nisbett & Masuda,
2003). When
asked which two objects go together in Figure 8.7 b, American
college
students tend to group cows with chickens—because both are
animals.
In contrast, Japanese students coupled cows with grass, because
grass
is what cows eat (Gutchess et al., 2010; Nisbett & Masuda,
2003).
These examples demonstrate cross-cultural differences in
perceiving
how objects are related to their environments. People raised in
North

America tend to focus on a single characteristic, whereas
Japanese
people tend to view objects in relation to their environment.
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Figure 8.7 Your Culture and Your Point of View
(a) Which of these two pictures do you think a North American
would be
more likely to take? (b) Which two go together?
Top photos: Blend Images/Shutterstock
Source, bottom: Adapted from Nisbett, R. E., & Masuda, T.
(2003). Culture and point of view. Proceedings of the
National Academy of Sciences, 100 (19), 11163–11170.
Copyright © 2003. Reprinted by permission of National
Academy of Sciences.
Researchers have even found differences in brain function when
people
of different cultural backgrounds view and categorize objects

(Park &
Huang, 2010). Figure 8.8 reveals differences in brain activity
when
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Westerners and East Asians view photos of objects, such as an
animal,
against a background of grass and trees. Areas of the brain
devoted to
processing both objects (lateral parts of the occipital lobes) and
background (the parahippocampal gyrus, an area underneath the
hippocampus) become activated when Westerners view these
photos,
whereas only areas devoted to background processes become
activated
in East Asians (Goh et al., 2007). These findings demonstrate
that a
complete understanding of how humans categorize objects
requires
application of the biopsychosocial model.
Figure 8.8 Brain Activity Varies by Culture
Brain regions that are involved in object recognition and
processing are
activated differently in people from Western and Eastern
cultures. Brain

regions that are involved in processing individual objects are
more highly
activated when Westerners view focal objects against
background
scenery, whereas people from East Asian countries appear to
attend to
background scenery more closely than focal objects.
Source: Park, D. C. & Huang, C.-M. (2010). Culture wires the
brain: A cognitive neuroscience perspective.
Perspectives on Psychological Science, 5 (4), 391–400.
Reprinted by permission of SAGE Publications.
Myths in Mind How Many Words for Snow?
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Cultural differences in how people think and categorize items
have led to
the idea of linguistic relativity (or the Whorfian hypothesis )—
the
theory that the language we use determines how we understand
(and
categorize) the world. One often-cited example is about the
Inuit in
Canada’s Arctic regions, who are thought to have many words
for snow,
each with a different meaning. For example, aput means snow
that is on
the ground, and gana means falling snow. This observation,

which was
made in the early 19th century by anthropologist Franz Boas,
was often
repeated and exaggerated, with claims that Inuit people had
dozens of
words for different types of snow. With so many words for
snow, it was
thought that perhaps the Inuit people perceive snow differently
than
someone who does not live near it almost year-round. Scholars
used the
example to argue that language determines how people
categorize the
world.
Research tells us that we must be careful in over-generalizing
the
influence of language on categorization. The reality is that the
Inuit seem
to categorize snow the same way a person from the rest of
Canada does.
Someone from balmy Winnipeg can tell the difference between
falling
snow, blowing snow, sticky snow, drifting snow, and “oh-sweet-
God-it’s-
snowing-in-May-snow,” just as well as an Inuit who lives with
snow for
most of the year (Martin, 1986). Therefore, we see that the
linguistic
relativity hypothesis is incorrect in this case: The difference in
vocabulary
for snow does not lead to differences in perception.
Categories and Culture

The human brain is wired to perceive similarities and
differences and, as we
learned from prototypes, the end result of this tendency is to
categorize items
based on these comparisons as well as on our previous
experiences with
members of different categories. However, our natural
inclination to do so
interacts with our cultural experiences; how we categorize
objects depends to a
great extent on what we have learned about those objects from
others in our
culture.
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Various researchers have explored the relationships between
culture and
categorization by studying basic-level categories among people
from different
cultural backgrounds. For example, researchers have asked
individuals from
traditional villages in Central America to identify a variety of
plants and animals
that are extremely relevant to their diet, medicine, safety, and
other aspects of
their lives. Not surprisingly, these individuals referred to plants
and animals at a

more specific level than North American university students
would (Bailenson et
al., 2002; Berlin, 1974). Thus, categorization is based—at least
to some extent
—on cultural learning. Psychologists have also discovered that
cultural factors
influence not just how we categorize individual objects, but al so
how objects in
our world relate to one another.
Although culture and memory both clearly affect how we
describe and categorize
our world, we do need to remember to critically analyze the
results of these
studies. Specifically, as our world becomes more Westernized,
it is possible—
even likely—that these cultural differences will decrease. These
results, then, tell
us about cultural differences at a given time. As you saw in the
Myths in Mind
feature above, we should also exercise caution when reading
about another form
of cultural influences on categorization—linguistic relativity.
Module 8.1b Quiz:
Memory, Culture, and Categories
Know . . .
1. The idea that our language influences how we understand the
world is
referred to as .
A. the context specificity hypothesis

B. sentence verification
C. the Whorfian hypothesis
D. priming
Understand . . .
2. A neurologist noticed that a patient with temporal-lobe
damage seemed
to have problems naming specific categories of objects. Based
upon
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what you read in this module, which classes of objects are most
likely to
be affected by this damage?
A. Animals and tools
B. Household objects that he would use quite frequently
C. Fruits and vegetables
D. Related items such as animals and hunting weapons
Apply . . .
3. Janice, a medical school student, looked at her grandmother’s

hospital
chart. Although her grandmother appeared to have problems
with her
intestines, Janice thought the pattern of the lab results
resembled those
of a patient with lupus she had seen in the clinic earlier that
week. Janice
is showing an example of
A. how memory for a previous example can influence
categorization
decisions.
B. how people rely on prototypes to categorize objects and
events.
C. how we rely on a set of rules to categorize objects.
D. how we are able to quickly categorize examples from
specific
categories.
Analyze . . .
4. Research on linguistic relativity suggests that
A. language has a complete control over how people categorize
the
world.
B. language can have some effects on categorization, but the
effects
are limited.
C. language has no effect on categorization.
D. researchers have not addressed this question.

Module 8.1 Summary
categories
Know . . . the key terminology associated with concepts and
categories.
8.1a
classical categorization
concept
graded membership
linguistic relativity (Whorfian hypothesis)
priming
prototypes
semantic network
Certain objects and events are more likely to be associated in
clusters. The
priming effect demonstrates this phenomenon; for example,
hearing the word
“fruit” makes it more likely that you will think of “apple” than,
say, “table.” More
specifically, we organize our knowledge about the world
through semantic
networks, which arrange categories from general to specific
levels. Usually we
think in terms of basic-level categories, but under some

circumstances we can
be either more or less specific. Studies of people with brain
damage suggest that
the neural representations of members of evolutionarily
important categories are
stored together in the brain. These studies also show us that our
previous
experience with a category can influence how we categorize and
store new
stimuli in the brain.
One of many possible examples of this influence was discussed.
Specifically,
ideas of how objects relate to one another differ between people
from North
America and people from Eastern Asia. People from North
America (and
Westerners in general) tend to focus on individual, focal objects
in a scene,
whereas people from Japan tend to focus on how objects are
interrelated.
Understand . . . theories of how people organize their
knowledge
about the world.
8.1b
Understand . . . how experience and culture can shape the way
we
organize our knowledge.
8.1c

Apply Activity
Try the following questions for practice.
1. What is the best example for the category of fish: a
hammerhead shark, a
trout, or an eel?
2. What do you consider to be a prototypical sport? Why?
3. Some categories are created spontaneously, yet still have
prototypes.
For example, what might be a prototypical object for the
category “what
to save if your house is on fire”?
Researchers have shown that language can influence the way we
think, but it
cannot entirely shape how we perceive the world. For example,
people can
perceive visual and tactile differences between different types
of snow even if
they don’t have unique words for each type.
Apply . . . your knowledge to identify prototypical
examples.8.1d
Analyze . . . the claim that the language we speak determines
how
we think.
8.1e
Module 8.2 Problem Solving,
Judgment, and Decision

Making
Polaris/Newscom
Learning Objectives
Ki-Suck Han was about to die. He had just been shoved onto the
subway’s tracks and was desperately scrambling to climb back
onto the
station’s platform as the subway train rushed toward him. If you
were a
few metres away from Mr. Han, what would you have done?
What factors
would have influenced your actions?
In this case, the person on the platform was R. Umar Abbasi, a
freelance
photographer working for The New York Post. Mr. Abbasi did
not put
down his camera and run to help Mr. Han. Instead, he took a
well-framed
photograph that captured the terrifying scene. The photograph
was
published on the front page of the Post and was immediately
condemned
by people who were upset that the photographer didn’t try to
save Mr.
Han’s life (and that the Post used the photograph to make
money). In a
statement released to other media outlets, the Post claimed that
Mr.
Abbasi felt that he wasn’t strong enough to lift the man and
instead tried
to use his camera’s flash to signal the driver. According to this

explanation, Mr. Abbasi analyzed the situation and selected a
course of
action that he felt would be most helpful. Regardless of whether
you
believe this account, it does illustrate an important point:
Reasoning and
decision making can be performed in a number of ways and can
be
influenced by a number of factors. That is why we don’t all
respond the
same way to the same situation.
Know . . . the key terminology of problem solving and decision
making.
Understand . . . the characteristics that problems have in
common.
Understand . . . how obstacles to problem solving are often self-
imposed.
Apply . . . your knowledge to determine if you tend to be a
maximizer or a
satisficer.
Analyze . . . whether human thought is primarily logical or
intuitive.
8.2a
8.2b
8.2c
8.2d
8.2e
Focus Questions
1. How do people make decisions and solve problems?

2. How can having multiple options lead people to be
dissatisfied
with their decisions?
In other modules of this text, you have read about how we learn
and remember
new information (Modules 7.1 and 7.2 ) and how we organize
our
knowledge of different concepts (Module 8.1 ). This module
will focus on how
we use this information to help us solve problems and make
decisions. Although
it may seem like such “higher-order cognitive abilities” are
distinct from memory
and categorization, they are actually a wonderful example of
how the different
topics within the field of psychology relate to each other. When
we try to solve a
problem or decide between alternatives, we are actually drawing
on our
knowledge of different concepts and using that information to
try to imagine
different possible outcomes (Green et al., 2006). How well we
perform these
tasks depends on a number of factors including our problem-
solving strategies
and the type of information available to us.
Defining and Solving Problems
You are certainly familiar with the general concept of a
problem, but in

psychological terminology, problem solving means
accomplishing a goal
when the solution or the path to the solution is not clear
(Leighton & Sternberg,
2003; Robertson, 2001). Indeed, many of the problems that we
face in life
contain obstacles that interfere with our ability to reach our
goals. The challenge,
then, is to find a technique or strategy that will allow us to
overcome these
obstacles. As you will see, there are a number of options that
people use for this
purpose—although none of them are perfect.
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Problem-Solving Strategies and Techniques
Each of us will face an incredible number of problems in our
lives. Some of these
problems will be straightforward and easy to solve; however,
others will be quite
complex and will require us to come up with a novel solution.
How do we
remember the strategies we can use for routine problems? And,
how do we
develop new strategies for nonroutine problems? Although these
questions
appear as if they could have an infinite number of answers,
there seem to be two
common techniques that we use time and again.
One type of strategy is more objective, logical, and slower,
whereas the other is
more subjective, intuitive, and quicker (Gilovich & Griffin,
2002; Holyoak &
Morrison, 2005). The difference between them can be illustrated
with an

example. Suppose you are trying to figure out where you have
left your phone.
You’ve tried the trick of calling yourself using a landline
phone, but you couldn’t
hear it ringing. So, it’s not in your house. A logical approach
might involve
making of list of the places you’ve been in the last 24 hours and
then retracing
your steps until you (hopefully) find your phone. An intuitive
approach might
involve thinking about previous times you’ve lost your phone or
wallet and using
these experiences to guide your search (e.g., “I’m always
forgetting my phone at
Dan’s place, so I should look there first”).
When we think logically, we rely on algorithms , problem-
solving strategies
based on a series of rules. As such, they are very logical and
follow a set of
steps, usually in a pre-set order. Computers are very good at
using algorithms
because they can follow a preprogrammed set of steps and
perform thousands
of operations every second. People, however, are not always so
rule-bound. We
tend to rely on intuition to find strategies and solutions that
seem like a good fit
for the problem. These are called heuristics , problem-solving
strategies that
stem from prior experiences and provide an educated guess as to
what is the
most likely solution. Heuristics are often quite efficient; these

“rules of thumb” are
usually accurate and allow us to find solutions and to make
decisions quickly. In
the example of trying to figure out where you left your phone,
you are more likely
to put your phone down at a friend’s house than on the bus, so
that increases the
likelihood that your phone is still sitting on his coffee table.
Calling your friend to
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ask about your phone is much simpler than retracing your steps
from class to the
gym to the grocery store, and so on.

The overall goal of both algorithms and heuristics is to find an
accurate solution
as efficiently as possible. In many situations, heuristics allow
us to solve
problems quite rapidly. However, the trade-off is that these
shortcuts can
occasionally lead to incorrect solutions, a topic we will return
to later in this
module.
Of course, different problems call for different approaches. In
fact, in some
cases, it might be useful to start off with one type of problem-
solving and then
switch to another. Think about how you might play the
children’s word-game
known as hangman, shown in Figure 8.9 . Here, the goal state is
to spell a
word. In the initial state, you have none of the letters or other
clues to guide you.
So, your obstacles are to overcome (i.e., fill in) blanks without
guessing the
wrong letters. How would you go about achieving this goal?
Figure 8.9 Problem Solving in Hangman
In a game of hangman, your job is to guess the letters in the
word represented
by the four blanks to the left. If you get a letter right, your
opponent will put it in
the correct blank. If you guess an incorrect letter, your
opponent will draw a body
part on the stick figure. The goal is to guess the word before the
entire body is
drawn.

On one hand, an algorithm might go like this: Guess the letter
A, then B, then C,
and so on through the alphabet until you lose or until the word
is spelled.
However, this would not be a very successful approach. An
alternative algorithm
would be to find out how frequently each letter occurs in the
alphabet and then
guess the letters in that order until the game ends with you
winning or losing. So,
you would start out by selecting E, then A, and so on. On the
other hand, a
heuristic might be useful. For example, if you discover the last
letter is G, you
might guess that the next-to-last letter is N, because you know
that many words
end with -ing. Using a heuristic here would save you time and
usually lead to an
accurate solution.
As you can see, some problems (such as the hangman game) can
be
approached with either algorithms or heuristics. In other words,
most people start
out a game like hangman with an algorithm: Guess the most
frequent letters until
a recognizable pattern emerges, such as -ing, or the letters -oug
(which are often
followed by h, as in tough or cough) appear. At that point, you
might switch to
heuristics and guess which letters would be most likely to fit in

the spaces.
Cognitive Obstacles
Using algorithms or heuristics will often allow you to
eventually solve a problem;
however, there are times when the problem-solving rules and
strategies that you
have established might actually get in the way of problem
solving. The nine-dot
problem (Figure 8.10 ; Maier, 1930) is a good example of such a
cognitive
obstacle. The goal of this problem is to connect all nine dots
using only four
straight lines and without lifting your pen or pencil off the
paper. Try solving the
nine-dot problem before you read further.
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Figure 8.10 The Nine-Dot Problem
Connect all nine dots using only four straight lines and without
lifting your pen or
pencil (Maier, 1930). The solution to the problem can be seen in
Figure 8.11 .
Source: Maier, N. F. (1930). Reasoning in humans. I. On
direction. Journal of Comparative Psychology, 10 (2), 115–143.
American Psychological Association.

Figure 8.11 One
Solution
to the Nine-Dot Problem
In this case, the tendency is to see the outer edge of dots as a
boundary, and to
assume that one cannot go past that boundary. However, if you
are willing to
extend some of the lines beyond the dots, it is actually quite a
simple puzzle to
complete.
Here is something to think about when solving this problem:
Most people impose
limitations on where the lines can go, even though those limits
are not a part of
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the rules. Specifically, people often assume that a line cannot
extend beyond the
dots. As you can see in Figure 8.11 , breaking these rules is
necessary in
order to find a solution to the problem.
Having a routine solution available for a problem generally
allows us to solve that
problem with less effort than we would use if we encountered it
for the first time.
This efficiency saves us time and effort. Sometimes, however,
routines may
impose cognitive barriers that impede solving a problem if
circumstances change
so that the routine solution no longer works. A mental set is a
cognitive
obstacle that occurs when an individual attempts to apply a
routine solution to
what is actually a new type of problem. Figure 8.12 presents a
problem that
often elicits a mental set. The answer appears at the bottom of
the figure, but
make your guess before you check it. Did you get it right? If

not, then you
probably succumbed to a mental set.
Figure 8.12 The Five-Daughter Problem
Maria’s father has five daughters: Lala, Lela, Lila, and Lola.
What is the fifth
daughter’s name?
The fifth daughter’s name is Maria.
Mental sets can occur in many different situations. For instance,
a person may
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experience functional fixedness , which occurs when an
individual identifies
an object or technique that could potentially solve a problem,
but can think of
only its most obvious function. Functional fixedness can be
illustrated with a

classic thought problem: Figure 8.13 shows two strings hanging
from a
ceiling. Imagine you are asked to tie the strings together.
However, once you
grab a string, you cannot let go of it until both are tied together.
The problem is,
unless you have extraordinarily long arms, you cannot reach the
second string
while you are holding on to the first one (Maier, 1931). So how
would you solve
the problem? Figure 8.16 offers one possible answer and an
explanation of
what makes this problem challenging.
Figure 8.13 The Two-String Problem
Imagine you are standing between two strings and need to tie
them together.
The only problem is that you cannot reach both strings at the
same time (Maier,
1931). In the room with you is a table, a piece of paper, a pair
of pliers, and a ball
of cotton. What do you do? For a solution, see Figure 8.16 .

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Figure 8.16 A

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