Self-Control A central theme in Chapter 7 is that the effects of self-control are not always the same—low self-control sometimes leads to crime and devianc

Self-Control A central theme in Chapter 7 is that the effects of self-control are not always the same—low self-control sometimes leads to crime and deviance, but sometimes it does not. When this pattern occurs, it often is because some “other factor” has come into play to amplify or diminish the effects of low self-control.

For this discussion, pick ONE of the factors below and describe the theory and research suggesting that it leads the effects of low self-control on crime to be different than what they normally would be: 

Criminal opportunity

Association with delinquent peers

Neighborhood disadvantage

sources to use :  
Hay, Carter, and Ryan Meldrum. 2016. Self-control and crime over the life course.    

Hart and Risley (2003), “The early catastrophe,” from American
Educator. The Early

The 30 Million Word Gap by Age 3

By Betty Hart and Todd R. Risley

D uring the 1960’s War on Poverty, we were among the many researchers, psychologists, and educators who brought our knowledge of child development
to the front line in an optimistic effort to intervene early to
forestall the terrible effects that poverty was having on some
children’s academic growth. We were also among the many
who saw that our results, however promising at the start,
washed out fairly early and fairly completely as children

In one planned intervention in Kansas City, Kans., we
used our experience with clinical language in tervention to
design a half-day program for the Turner House Preschool,
located in the impoverished Juniper Gardens area of the city.
Most interventions of the time used a variety of methods
and then measured results with IQ tests, but ours focused
on building the everyday language the children were using,
then evaluating the growth of that language. In addition,
our study included not juSt poor children from Turner
House, but also a group of University of Kansas professors’
children against whom we could measure the Turner House
children’s progress.

All the children in the program eagerly engaged with the
wide variety of new materials and language-intensive activi-
ties introduced in the preschool. The spontaneous speech
data we collected showed a spurr of new vocabulary words

Betty Hart is professor ofHuman Development at the Univer-
sity of Kansas and senior scientist at the Schiefelbusch Institute
for Life Span Studies. Todd R. Risley is professor in the Depart-
ment of Psychology at the University ofAlaska Anchorage and
director ofAlaska’s Autism Intensive Early Intervention Project.
The two have collaborated on research projects for more than
35 years. This article is excerpted with permission from Mean-
ingful Differences in the Everyday Experiences of Young
American Children, © 1995, Brookes; www.brookespublish-; 1-800-638-3775; $29.00.

added to the dictionaries of all the children and an abrupt
acceleration in their cumulative vocabulary growth curves.
But just as in other early intervention programs, the in-
creases were temporary.

We found we could easily increase the size of the chil-
dren’s vocabularies by teaching them new words. But we
could not accelerate the rate of vocabulary growth so that it
would continue beyond direcr teaching; we could not
change the developmental trajectory. However many new
words we taught the children in the preschool, it was clear
that a year later, when the children were in kindergarten, the
effects of the boost in vocabulary resources would have
washed our. The children’s developmental trajectories of vo-
cabulary growth would continue to point to vocabulary sizes
in the future that were increasingly discrepant from those of
the professors’ children. We saw increasing disparity between
the extremes-the fast vocabulary growth of the professors’
children and the slow vocabulary growth of the Turner
House children. The gap seemed to foreshadow the findings
from other studies that in high school many children from
families in poverty lack the vocabulary used in advanced

Rather than concede to the unmalleable forces of hered-
ity, we decided that we would undertake research that would
allow us to understand the disparate developmental trajecto-
ries we saw. We realized that if we were to understand how
and when differences in developmental trajectories began,
we needed to see what was happening to children at home at
the very beginning of their vocabulary growth.

W e undertook 2 1/2 years of observing 42 families for an hour each month to learn aboU[ what typi-cally went on in homes with 1- and 2-year-old
children learning to talk. The data showed us that ordinary
families differ immensely in the amount of experience with


language and interaction they regularly provide their chil-
dren and that differences in children’s experience are
strongly linked to children’s language accomplishments at
age 3. Our goal in the longitudinal study was to discover
what was happening in children’s early experience that could
account for the intractable difference in rates of vocabulary
growth we saw among 4-year-olds.

Our ambition was to record “everything” that went on in
children’s homes-everything that was done by the children,
to them, and atound them. Because we were committed to
undertaking the labor involved in observing, tape recording,
and transcribing, and because we did not know exactly
which aspects of children’s cumulative experience were con-
tributing to establishing rates of vocabulary growth, the
more information we could get each time we were in the
home the more we could potentially learn.

We decided to start when the children were 7-9 months
old so we would have time for the families to adapt to obser-
vation before the children actually began talking. We fol-
lowed the children until they turned three years old.

The first families we recruited to participate in the study
came from personal contacts: friends who had babies and
families who had had children in the Turner House
Preschool. We then used birth announcements to send de-
scriptions of the study to families with children of the de-
sired age . In recruiting from birth announcements, we had
[wo priorities . The first priority was to obtain a range in de-
mographics , and the second was stability-we needed fami-
lies likely to remain in the longitudinal study for several
years. Recruiting from birth announcements allowed us to
preselect families . We looked up each potential family in the
city directory and listed those with such signs of permanence
as owning their home and having a telephone. We listed
families by sex of child and address because demographic
status could be reliably associated with area of residence in
this city at that time. Then we sent recruiting letters selec-
tively in order to maintain the gender balance and the repre-
sentation of socioeconomic strata.

Our final sample consisted of 42 families who remained
in the study from beginning ro end. From each of these fam-
ilies, we have almost 2 1/ 2 years or more of sequential
monthly hour-long observations. On the basis of occupa-
tion, 13 of the families were upper socioeconomic status
(5E5), 10 were middle 5E5 , 13 were lower 5E5 , and six were
on welfare. There were African-American families in each
5E5 category, in numbers roughly reflecting local job alloca-
tions. One African-American family was upper 5E5, three
were middle, seven were lower, and six families were on wel-
fare. Of the 42 children, 17 were African American and 23
were girls. Eleven children were the first born to the family,
18 were second children, and 13 were third or later-born

What We Found
Before children can take charge of their own experience and
begin to spend time with peers in social groups outside the
home, almost everything they learn comes from their fami-


Eighty-six percent to 98 percent
of the words recorded in each
child’s vocabulary consisted
of words also recorded
in their parents’ vocabularies.



lies, to whom soci ety has assigned the task of soc ializing
children. We were not surprised to see the 42 children turn
out to be like their parents; we had no t full y realized, how-
ever, the implications of those simi lari ties for the children’s

We observed the 42 children grow more like their par-
ents in stature and ac tivity levels, in vocabul ary resources,
and in lan guage and interaction styl es . Despite the consid-
erable range in vocabulary size among the children, 86 per-
cent to 98 percent of the words recorded in each child ‘s vo-
cabulary consisted of words also recorded in their parents’
vocabularies. By the age of 34-36 months , the children
were also talking and using numbers of differen t words
very similar to the averages of their parents (see the table

By the time the children were 3 years old, trends in
amount of talk, vocabulary growth, and style of interaction
were well established and clearly suggested widening gaps to
come. Even patterns of parenting were already observable
among the children . When we listened to the children, we
seemed to hear their parents speaking; when we watched the
children play at parenting their dolls , we seemed to see the
futures of their own children.

Families’ Language and Use
Differ Across Income Groups


12 Profession al 23 Working.class 6 Welfare
Measures and scores Paren! Child Pateur Child Paten! Child

Pretest score’ 41 31 14
Recorded vocabulary

Size 2,176 1,116 1,49 8 749 974 525
Average utteran ces

per hour” 487 310 301 223 176 168
Average d ifFerem

words per hour 382 297 25 1 216 167 149
‘Wh en we began the longitudinal study, we asked rhe parents to complete a vocab u·
lary ptetest. At the first observa ti on each paren t was asked to complete a fotm abo
stracted from the Peabod y Pictu re Vocabu lary Test (PPVT ). We gave each parent a
list of 46 vocabulary words and a seties of pictures (fou r op ti ons per vocabulary
word) and asked the pa ten t to write beside each word the number of the picture
rhar corresponded ro th e wrirren wo rd . Pa renr perform ance on [h e resr was highly
correlated with years of ed ucation (r = .5 7).

‘Parent u[(erances and different words were averaged over 13-36 months of child
age. Child utterances and different wotds we re ave raged for the four observarions
when th e chi ld ren we re 33·36 month s old .

We now had answers to our 20-year-old questions . We
had observed, recorded , and analyzed more than 1,300
hours of casual interactions berween parents and their lan-
guage-learn ing children. We had dissembled these interac-
tions into several dozen molecular features that could be reli-
ably coded and counted. We had examined the correlations
berween the quantities of each of those featur es and severa l
outcome measures relating to children’s languageaccom-
plishments. .

After all 1,318 observations had been entered into the
computer and checked for accuracy against the raw data,
after every word had been checked for speJling and coded
and checked for its part of speech, after every utterance had
been coded for syntax and discourse function and every code
checked for accuracy, after random samples had been re-



coded to check the reliability of the coding, after each file
h ad been checked one more time and the accuracy of each
aspect verified, and after th e data analys is programs had fi-
nally been run to produce frequency counts and dictionary
lists for each observation, we had an immense numeric
database that required 23 million bytes of computer file
space. We were flllally read y to begin asking what it all

It took six years of painstaking effort before we saw the
first results of the longitudinal research. And then we were
astonished at the differences the data revealed (see the graph

Children’S Vocabulary Differs Greatly




‘5 ‘” .0
0 >
> 600



10 12 14 16 18 20 22 24 26 28 30 32 34 36

Age of child in monlhs

Like the children in the Turner House Preschool, the three yea r old children from families on welfare not only had smaller vocabularies than did children of the
same age in professional families , but they were also add ing
words more slowly. Projecting the developmental trajectory
of the welfare children’s vocabulary growth curves, we could

. see an ever-widening gap similar to the on e we saw berween
the Turner House children and the professors’ children in

While we were immersed in collecting and processing
the dat a, our thoughts were concerned only with the next
utterance to be transcribed or coded. While we were ob-
serving in the homes, though we were aware that th e fami-
lies were very different in lifestyles, they were all similarly
engaged in the fundamental task of raising a child. All the
families nurtured their children and played and talked with
them . They all disciplined their children and taught them
good manners and how to dres s and toilet themselves.
They provided their children with much the same toys and
talked to them about much the same things. Though dif-
ferent in personality and skill level s, the children all
learned to talk and to be socially appropriate members of
the family with all the basic skills needed for preschool


Across Income Groups
13 higher
SES children

” (profeSSional)

23 middle/lowe r·
SES children

6 children from
families on welfare

, ,

Test Performance in Third Grade Follows
Accomplishments at Age 3
We wondered whether the differences we saw at age 3 would
be washed out, like the effects of a preschool intervention, as
the children’s experience broadened to a wider community
of competent speakers. Like the parents we observed, we
wondered how much difference children’s early experiences
would actually make . Could we, or parents, predict how a
child would do in school from what the parent was doing
when the child was 2 years old?

Fortune provided us with Dale Walker, who recruited 29
of the 42 families to participate in a study of their children’s
school performance in the third grade, when the children
were nine to 10 years old.

We were awestruck at how well our measures of accom-
plishments at age 3 predicted measures of language skill at
age 9-10. From our preschool data we had been confident
that the rate of vocabulary growth would predict later per-
formance in school; we saw that it did . For the 29 children
observed when they were 1-2 years old, the rate of vocabu-
lary growth at age 3 was strongly associated with scores at
age 9-10 on both the Peabody Picture Vocabulary Test-Re-
vised (PPVT-R) of receptive vocabulary (r = .58) and the
Test of Language Development-2: Intermediate (TOLD)
(r = .74) and its subtests (listening, speaking, semantics,

Vocabulary use at age 3 was equally predictive of measures
of language skill at age 9-10. Vocabulary use at age 3 was
strongly associated with scores on both the PPVT-R
(r = .57) and the TOLD (r = .72). Vocabulary use at age 3
was also strongly associated with reading comprehension
scores on the Comprehensive Test of Basic Skills (CTBS/U)
(r= .56).

The 30 Million Word Gap By Age 3
All parent-child research is based on the assumption that the
data (laboratory or field) reflect what people typically do. In
most studies, there are as many reasons that the averages
would be higher than reponed as there are that they would
be lower. But all researchers caution against extrapolating
their findings to people and circumstances they did not in-
clude. Our data provide us, however, a first approximation
to the absolute magnitude of children’s early experience, a
basis sufficient for estimating the actual size of the interven-
tion task needed to provide equal experience and, thus,
equal opportunities to children living in poverty. We depend
on future studies to refIne this estimate.

Because the goal of an intervention would be to equalize
children’s early experience, we need to estimate the amount
of experience childten of different SES groups might bring
to an intervention that began in preschool at age 4. We base
our estimate on the remarkable differences our data showed
in the relative amounts of children’s early experience: Simply
in words heard, the average child on welfare was having half
as much experience per hour (616 words per hour) as the av-
erage working-class child (1,251 words per hour) and less
than one-third that of the average child in a professional
family (2,153 words per hour). These relative differences in


amount of experience were so durable over the more than
two years of observations that they provide the best basis we
currently have for estimating children’s actual life experience.

A linear extrapolation from the averages in the observa-
tional data to a 100-hour week (given a 14-hour waking
day) shows the average child in the professional families
with 215,000 words of language experience, the average
child in a working-class family provided with 125,000
words, and the average child in a welfare family with 62,000
words of language experience . In a 5,200-hour year, the
amount would be 11 .2 million words for a child in a profes-
sional family, 6 .5 million words for a child in a working-
class family, and 3.2 million words for a child in a welfare
family. In four years of such experience, an average child in a
professional family would have accumulated experience with
almost 45 million words, an average child in a working-class
family would have accumulated experience with 26 million
words, and an average child in a welfare family would have
accumulated experience with 13 million words. By age 4,
the average child in a welfare family might have 13 million
fewer words of cumulative experience than the average child
in a working-class family. This linear extrapolation is shown
in the graph below.

The Number of Words Addressed to Children
Differs Across Income Groups

50 million Professional

40 million



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