Punishment and Crime: An Examination of Some Empirical Evidence
Author(s): Theodore G. Chiricos and Gordon P. Waldo
Source: Social Problems, Vol. 18, No. 2 (Autumn, 1970), pp. 200-217
Published by: Oxford University Press on behalf of the Society for the Study of Social
Problems
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PUNISHMENT AND CRIME: AN EXAMINATION OF
SOME EMPIRICAL EVIDENCE*
THEODORE G. CHIRICOS AND GORDON P. WALDO
The Florida State University
Data from National Prisoner Statistics and Uniform Crime Reports are used to
re-examine the relationship between rates of crime and the certainty and severity of
punishment in the states of the United States. Recent research by Gibbs and Tittle
using similar data to test deterrence hypotheses are extended in two ways: (1) by
examining the relationships for three points in time which were previously examined
for a single time period, and (2) by relating changes in rates of crime to prior
changes in the certainty and severity of punishment. Little consistent support is found
for the hypotheses that rates of crime and the certainty and severity of punishment
are inversely related. The data for certainty suggest that the relationship with crime
rates is somewhat variable over time and among offenses. These findings contrast
with the strong and consistent negative associations reported by Tittle. An attempt
is made to account for the strength and consistency of the previous findings by exploring the problem of correlated bias that exists in Tittle's measures of certainty
and criminality. The inconsistency of findings, both within this study and among
recent empirical tests of deterrence theory, indicate that existing sources of data may
be inappropriate for use in the testing of deterrence hypotheses.
The question of whether penal sanctions deter crime is still being asked
(Tittle, 1969; Jensen, 1969; Zimring
and Hawkins, 1968; Gibbs, 1968,
1966; Chambliss, 1966; Bittner and
Platt, 1966) after more than a century
of debate among sociologists, crimino-
logists, and legal philosophers. Given
the importance of this issue to our understanding of social control and the
maintenance of social order, it is surprising that its resolution seems little
nearer today than it was in the 19th
century. Most of the input for this debate has been theoretical or moralistic
in nature (Mead, 1918; Wood, 1938;
Ball, 1955; Polier, 1956; Barnes and
Teeters, 1959; Toby, 1964; Jeffery,
1965), and as noted by Chambliss
(1966:70), "... the question of deter-
rence has frequently turned into a de* This research was partially supported
by Ford Foundation Grant #67-586. The
authors would like to express their appreciation to Charles Tittle, Jack Gibbs, Roland
Chilton, and Harry Allen for their com-
ments and suggestions on an earlier draft of
this paper.
bate over the morality of capital punishment."
For a time, sociologists and "enlightened" jurists showed a tendency to
reject Bentham's (1843) "classical"
hypothesis that man avoids criminal
behavior if that behavior elicits swift,
severe, and certain punishment. This
common rejection of deterrence theory
is summarized by Horton and Leslie
(1965:154) who conclude: "there is
no evidence that states with more severe
penalties have lower crime rates or recidivism rates than states with lighter
penalties." Indeed, until recently, empirical evidence on the question of deterrence has been limited to studies
showing the apparent ineffectiveness of
capital punishment in deterring crim-
inal homicide (Sellin, 1967; Savitz,
1958; Schuessler, 1952). Contradic-
tory empirical evidence-in support of
the deterrence hypothesis-has been
slow to accumulate.
Several recent studies, however, have
suggested the possibility that punishment may in fact deter criminality.
Chambliss (1966) reported that the
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Punishment and Crime 201
incidence of parking violations on a
states that were above and below the
college campus dropped sharply when
median level of certainty, Gibbs (1968:
523-527) found an inverse relationship
between certainty of punishment and
the severity and certainty of punishment
for this offense was increased. Having
analyzed the frequency of parking vio-
lations before and after a change in
regulations, Chambliss (1966:74) con-
cluded that "the changes had the effect
of substantially reducing the number of
violations."'
Gibbs (1968:519-521) introduced
a new dimension to the study of deterrence by presenting operational definitions of certainty and severity of punishment that were based upon existing,
though admittedly limited, sources of
aggregate data. Using the Federal
Bureau of Investigation's Uniform
crime Reports and the National Prisoner Statistics published by the Federal
Bureau of Prisons, an index of the
certainty of punishment was given by a
ratio of prison admissions for homicide
to the number of homicides known to
the police. The median number of
criminal homicide rate (Phi = -.48).
A similar analysis for severity and rates
of homicide also showed a negative,
though weaker association (Phi =
-.25). Noting that crime rates may
be as much a product of uncontrolled
etiological (extra-legal) factors as they
are a response to penal sanctions, Gibbs
(1968:529-530) concluded:
... all that can be said of the findings is
that they question the common assertion
that no evidence exists of a relationship
between legal reactions to crime and the
crime rate.
Tittle's (1969) operational definitions of certain and severe punishment
were similar to those introduced by
Gibbs2 and were applied to a study of
all seven F.B.I. "Crime Index" offenses.
Tittle (1969:415) found that for the
months served by persons for homicide
seven crimes considered together, certainty of punishment and rates of "de-
provided Gibbs with an index of the
severity of punishment. Comparing
(Tau-c = -.45). When the relation-
viance,"3 were negatively associated
1 Cohen (1965:10) provides some additional insights into other factors that might have
helped reduce the number of parking violations. "Several years ago the Indiana University
faculty had a high rate of violation of campus parking regulations, in part because of the
disjunction between the demand for parking spaces and the supply. . . . One response to
this situation was to create new parking lots and to expand old ones."
2 Gibbs' (1968) index of certainty of imprisonment for homicide, and Tittle's (1969)
certainty of punishment for individual felonies were given by the following ratios:
# of State Prison Admissions for Homicide in 1960
Gibbs:
Mean # of Homicides Known to Police for 1959-1960
Tittle:
# of State Prison Admissions for "X" Offense in 1960 and 1963
# of "X" Crimes Known to the Police in 1959 and 1962
The severity of punishment was indexed by Gibbs (1968) as "the median number of
months served on a homicide sentence by all persons in prison on December 31, 1960."
Tittle (1969) used "mean length of time served for felony prisoners released from state
prisons in 1960" as his principal index of severity.
3 Tittle (1969) referred to his measure of criminality as a "Deviance Index" and his
operational definition of that index for individual felonies was given by:
Mean # of "X" Offenses Known to Police for 1959 and 1962.
1960 Population
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202 SOCIAL PROBLEMS
ships between certainty of punishment
and rates of deviance were examined
for the seven individual offenses, they
proved to be consistently negative and
ranged in strength from -.57 for sex
offenses to -.08 for auto theft.
Whereas these data for certainty offered
some support for the deterrence hypothesis, severity of punishment was positively related to rates of deviance for all
crimes excepting homicide (-.45).
While Gibbs studied only homicide,
and Tittle examined seven offenses in-
cluding homicide, their findings for this
offense are somewhat contradictory.
Both found certainty and severity of
punishment to be inversely related to
rates of homicide. However, in Gibbs'
analysis, the relationship is stronger for
certainty than for severity, while in
Tittle's research, this represents an
extension of Gibbs' analysis to include
additional offenses. However, an effort
is made to approach the testing of the
deterrence hypothesis in terms that are
less "static" than those used by Gibbs
and Tittle. The operational definitions
of certainty and criminality allow for
a test of the expected deterrence relationship at three points in time. For
severity, the deterrence hypothesis will
be tested at two points in time. By affording a check on the reliability of
empirical relationships, this approach
extends the efforts of Gibbs and Tittle.
A second departure in this approach
to the deterrence question is provided
by a focus upon changes in rates of
crime that follow changes in levels of
certainty and severity. This approach is
Tittle's data the situation is reversed.
prompted by several considerations.
In fact, the relationship between certainty of punishment and homicide was
First, there is an assumption-implicit
in deterrence theory-that a causal relationship exists between punishment
and criminality. In the absence of experimental controls one might logically
consider whether changes in "X" (certainty or severity) precede or accompany changes in "Y" (crime rates).
The relevance of change is further
underscored by the link between the
deterrence issue and aspects of learning
not statistically significant (-.17) in
Tittle's study. Since the findings of
Gibbs and Tittle are inconsistent, even
though they used similar operational
definitions for almost identical time
periods, further examination of the
relationship between crime rates and
legal sanctions appears warranted.
The research reported here is a further test of the hypothesis that rates of
crime are inversely related to the certainty and severity of punishment.4 Like
It will be noted that a major portion of the
"deviance index"-1959 Crimes Known to
Police--is composed of data which reflect
theory. Homans (1961:55) has sug-
gested that the more often a man re-
ceives "reinforcement" in a given
period, the less likely will additional
(comparable) reinforcement be effect-
ive. Applying this interpretation to
both positive (reward) and negative
criminal activity preceding the measures of
certainty and severity used by Tittle. This
would seem to partially violate the logic of
deterrence theory, wherein reduced criminality, or deviance is expected to follow the
imposition of certain or severe punishment.
ment is important in the theoretical formu-
1966; Gibbs, 1968; Tittle, 1969), the
celerity of punishment has not been ex-
research.
4 As in previous research (Chambliss,
(punishment) reinforcement, Jefferey
(1965:298) concluded that "continous
amined. While this dimension of punishlation of deterrence theory, avaialable data
restrict its incorporation for this kind of
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Punishment and Crime 203
punishment will not control behavior
through the criminal justice system
either, for satiation takes place .. "
Even with high levels of certain and
from the point at which an offense be-
severe punishment, a constancy in these
negative sanctions could diminish their
deterrent effectiveness. Thus, in addi-
judicial disposition. Regrettably, this
approach is impossible under existing
conditions for any meaningful number
of cases and one is forced to construct
tion to absolute levels of certainty and
severity, important variables may be
the degree of change in certainty and
severity. In fact, one might argue that
potential criminal offenders are more
likely aware of broad trends and
changes in certainty and severity of
punishment, than of their absolute
levels. For example, an awareness that
the government is attempting to increase the certainty and severity of pun-
ishment for narcotics use may serve
as a greater deterrent to middle-class
Americans than any understanding of
the exact probability (certainty) and
magnitude (severity) of punishment.
This "change" orientation is also re-
flected in Chambliss' (1966:73) approach to the question of deterrence
through punishment:
... change in regulations (and the cor-
responding increase in the certainty and
severity of punishment) greatly reduced
the number of transgressions and the num-
ber of transgressors, and served as an effective deterrent. [Italics added.]
RESEARCH METHOD
As expressed by Gibbs and Tittle,
and as operationalized here, certainty
of punishment actually refers to the
certainty of imprisonment as a final
disposition for crimes known to the
comes known to the police, to final
estimates of certainty from available
sources of information.5
Using data from Uniform Crime
Reports (Federal Bureau of Investiga-
tion, 1950:82-85; 1951:79-82; 1960:
38-51; 1961:38-52; 1963:38-52; 1964:
52-66) and National Prisoner Statistics
(Federal Bureau of Prisons, 1954:72-
74; 1960:41; 1964a:26-27), an index
of the certainty of imprisonment for
each of six offenses6 was computed for
1950, 1960, and 1963. The index gives
the ratio of prison admissions for one
year to the average number of crimes
known to the police in that year and
the previous year, for a specific crime
category. The three certainty indices
were computed for each state as follows:
5 Unless one had the means to conduct
an immensely expensive research project in
all 50 states, these data are unavailable. Indeed, such a project would necessitate covering all police jurisdictions--or a meaningful
sample of jurisdictions-within each state
for a number of years before the desired data
were available.
6 The category of "sex offenses" was in-
corporated into Tittle's (1969) study, but
eliminated here because of definitional in-
consistencies between Uniform Crime Reports and National Prisoner Statistics. Uniform Crime Reports provides data for "forci-
police. An estimate of this certainty for
ble rape," while National Prisoner Statistics
combines this crime with a large group of
each offense category is given by the
was also eliminated from the present analysis
proportion of "crimes known to the
police" which result in imprisonment.
Ideally, this estimate would be achieved
by tracing large numbers of cases
rather diverse "sex offenses." "Total crimes"
even though Tittle (1969) included this
category. "Total crimes" is essentially a
meaningless category since it encompasses
entirely different elements in the two sources
of data.
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204 SOCIAL PROBLEMS
1950 Admissions to Prison for "X" Offense
1950 Certainty = Mean of "X" Crimes Known to Police in 1949 & 1950
1960 Admissions to Prison for "X" Offense
1960 Certainty = Mean of "X" Crimes Known to Police in 1959 & 1960
1963 Admissions to Prison for "X" Offense
1963 Certainty = Mean of "X" Crimes Known to Police in 1962 & 1963
In addition to facilitating three tests
of the relationship between certainty of
punishment and rates of crime, the several measures of certainty may be used
reflected in several sources of available
to give three indices of the change in
certainty over time. Change in the certainty of punishment refers to the in-
points in time and change in severity
crease or decrease in the probability that
criminal behavior will result in im-
prisonment. Operationally, change in
certainty is given by the percentage
change (increase or decrease) in the
certainty of punishment between each
information.' However, only "median
length of sentence served by released
prisoners" allows one to look at two
over time. Thus, "median sentence
served" was recorded for 1960 (Federal Bureau of Prisons, 1960:69) and
1964 (Federal Bureau of Prisons,
1964b:52); and the two were used to
compute the percentage change (increase or decrease) in severity of pun-
ishment over time. The operational
pair of years: 1950-1960; 1950-1963;
definitions of severity and change in
and 1960-1963. Thus, for a particular
severity are briefly summarized:
1960 Severity = Median Length of Sentence Served by State Prisoners Released
in 1960
1964 Severity = Median Length of Sentence Served by State Prisoners Released
in 1964
Percentage Change in Severity = (1964 Severity) - (1960 Severity)
(1960 Severity)
state, the changes in certainty were com- The presumed "dependent variable"
puted as follows: in deterrence research is the criminal
(1960 Certainty) - (1950 Certainty)
1950-1960 % Change in Certainty = (1950 Certainty)
(1963 Certainty) - (1950 Certainty)
1950-1963 % Change in Certainty = (1950 Certainty)
(1963 Certainty) - (1960 Certainty)
1960-1963 % Change in Certainty = (1960 Certainty)
The severity of punishment administered by states for specific offenses, is
7 As noted earlier, Tittle (1969) used
"mean length of time served for felony
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Punishment and Crime 205
behavior which is thought to be reduced
by certain and severe punishment. Rates
of crime and percentage of crime rate
change, provide ready, although admittedly crude, measures of the de-
pendent variable in this analysis. Mean
crime rates were computed for three-
year periods following each point in
time represented by the several indices
of certainty and severity of punishment.
This procedure closely approximates
Gibbs' (1968) earlier methodology.
The mean rates of crime for (1950,
1951, 1952), (1960, 1961, 1962), and
(1963, 1964, 1965) were compared
respectively with certainty in 1950
(Time 1), 1960 (Time 2), and 1963
(Time 3). The mean crime rate for
1960, 1961, and 1962 was compared
with severity of punishment in 1960,
while the mean for 1964, 1965, and
1966 was compared with 1964 severity.
In essence, it was expected that there
would be an inverse relationship between the certainty and severity of pun-
ishment as measured in a single period,
and the average rate of criminal offense
in the subsequent period.
For each measure of percentage
change in severity or certainty of punishment, several indices of the percent-
age change in crime rate were computed. For example, percentage change
three periods of time:8 1962-1965;
1963-1966; 1964-1967. The several
measures of change in crime rate cover
time periods that begin either near the
end of the period of change in certainty, or at its conclusion. This allows
a change in certainty or severity to substantially precede a change in rates of
crime. Similar computations of crime
rate change were made with regard to
the additional measures of change in
certainty and change in severity of
punishment.
Classical criminology and the recent
findings of Chambliss, Gibbs, and
Tittle,9 suggest the following hypo-
theses:
1. There is an inverse relationship
between the certainty of punishment and crime rates for each
time period under consideration.
2. There is an inverse relationship
between the severity of punishment and crime rates for each
time period under consideration.
3. There is an inverse relationship
between change in certainty of
punishment and change in crime
rates.
4. There is an inverse relationship
between change in severity of
punishment and change in crime
rates.
in certainty of punishment between
1960 and 1963 was compared with
percentage change in crime rate for
The data are analyzed in 2 X 2 contingency tables using the states in the
prisoners released from state prisons in
age change in crime rate is given by the
1960" as a measure of the severity of pun-
ishment for specific offense. For "total
felonies" Tittle used "the median sentence
for state felony offenders imprisoned in
1960," as well as "the number of crimes
punishable by death" in a state. These data,
as well as data for "median length of sentence served by prisoners" in 1960 and 1964,
were considered prior to our selection of the
latter.
8 The operational definitions for percent-
following:
Crime Rate (Time 2) - Crime Rate (Time 1)
Crime Rate (Time 1)
9 It should be emphasized that Tittle
(1969:415) found little support for the
hypothesis that rates of crime and the
severity of punishment are inversely related.
The expected inverse relationship was found
only for homicide.
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206 SOCIAL PROBLEMS
TABLE 1
PHI-COEFFICIENTS FOR CERTAINTY OF PUNISHMENT AND CRIME
RATES IN THREE TIME PERIODS FOR SIXMAJOR CRIMES
Time
1
Time
2
Time
3
1950 Certainty With 1960 Certainty With 1963 Certainty With
Mean of 1950, Mean of 1960, Mean of 1963,
1951, and 1952 1961, and 1962 1964, and 1965
Crime Rates Crime Rates Crime Rates
Homicide
.02
-.46a
Robbery
-.26
-.33a
Burglary
-.09
Assault
-.35a
Larceny
Auto
-.38b
-.04
Theft
-.33a
-.17
-.16
-.17
-.25
-.42b
--.50
-.25
-.15
-.16
a = p <.05.
b = p <.01.
e =p <.001.
U.S. as the unit of analysis. Each variable is divided at the median into high
and low scores.10 Phi-coefficients and
chi-squares are computed to show the
strength, direction, and significance of
the associations." Because each rela-
tionship is examined for six offense
categories, the number of contingency
tables is too large for the tables to be
presented in the paper. Instead, the
relationships are summarized by offense
category with phi-coefficients and levels
of significance reported.
10 This procedure is identical with that
used by Gibbs (1968:523-527), but differs
from that of Tittle (1969:414). The latter
rank-ordered the states on each of the several indices, and then divided each distribution into "four to nine approximately equal
FINDINGS
The data of Table 1 show the rela-
tionship between certainty of punish-
ment and rates of crime for six offenses
-at three points in time: 1950 certainty with the mean of 1950, 1951, and
1952 crime rates (Time 1), 1960 certainty with the mean of 1960, 1961, and
1962 crime rates (Time 2), and 1963
certainty with the mean of 1963, 1964,
and 1965 crime rates (Time 3). Although all but one of the relationships are negative-as hypothesized-
the strength and statistical significance
of the associations vary greatly by offense and over time. Indeed, only seven
of the 18 phi-coefficients were statis-
tically significant (p <.05).
categories of states, depending upon the
nature of the distribution and apparent
'natural' groupings . . ." Thus, it was im-
When relationships are compared at
three points in time, only assault shows
a consistently significant inverse rela-
ology, because the cutting points for the
tionship between certainty of punishment and rates of crime. For burglary,
the relationship appears statistically significant at Times 2 and 3, but is very
possible to replicate Tittle's precise methodseveral distributions were not reported.
11 This mode of statistical analysis was
also used by Gibbs (1968:523-527). The
reported phi-coefficients should be somewhat
comparable to Tittle's (1969:414-415)
Tau-c correlations, inasmuch as Tau-c = Phi
in the special case of 2 X 2 classifications.
weak for Time 1. The negative cor-
relations are fairly consistent for robbery, but only in Time 2 is the relation-
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Punishment and Crime 207
TABLE 2
PHI-COEFFICIENTS FOR SEVERITY OF PUNISHMENT AND CRIME
RATES IN Two TIME PERIODS FOR SIX MAJOR CRIMES
Time 1 Time 2
1960 Severity With 1964 Severity With
Mean of 1960, Mean of 1964,
1961, and 1962 1965, and 1966
Crime Rates Crime Rates
Homicide
-.33a
Robbery
Assault
.12
.32a
-.03
.00
-.08
Burglary .25 .08
Larceny .14 -.09
Auto
Theft
.13
.12
a -- p <.05.
ship significant. For larceny and auto
theft, the negative associations are consistently weak and non-significant at
each time period.
Homicide presents one of the more
intriguing patterns with a low positive
Table 2 summarizes the relationship
between severity of punishment and
crime rates for two time periods: 1960
severity with the mean of 1960, 1961,
nificant negative association (-.46)
in Time 2, and a small negative asso-
The findings provide no consistent support for the deterrence hypothesis. The
for Time 2 are similar to the findings
of Gibbs, and the data for Time 3 are
relationships between severity and
crime rates are-with one exceptioneither positive or extremely weak.
Moreover, there is little consistency
association (.02) in Time 1, a sig-
ciation (-.17) in Time 3. The data
supportive of Tittle; but in Time 1 the
data fail to support either Gibbs or
Tittle.12
In short, although all but one of the
associations presented in Table 1 are
negative,13 the examination of the data
for three points in time indicates little
reliability in the relationship between
the certainty of punishment and crime
rates.
12 Gibbs (1968:526) found the relationship between certainty and criminality to be
-.48 (phi) and Tittle (1969:415) obtained
a Tau-c of -.17.
13 Since there is an artifact in the data
which virtually assures that the phi-coefficients will be negative, the reader should not
view this consistent pattern of negative associations as providing very strong support for
deterrence theory. This issue will be ex-
amined in detail in the discussion section.
and 1962 crime rates (Time 1), and
1964 severity with the mean of 1964,
1965, and 1966 crime rates (Time 2).
over time, within offense categories.
For example, a significant inverse
relationship (Phi = -.33) between
severity of punishment and rates of
homicide for Time 1 is reduced to
-.03 for Time 2. While the earlier
(Time 1) relationship is similar to the
findings of Gibbs and Tittle,14 the data
for Time 2 represent a substantial contradiction. For the remaining offense
categories, the relationship between
severity of punishment in 1960 (Time
1) and rates of crime is positive, and
for assault, this association (Phi = .32)
14 The relationship between the severity
of punishment and homicide rates was cal-
culated by Gibbs (1968:526) at Phi=
-.25, and by Tittle (1969:415) at Tau-c =
-.45.
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208 SOCIAL PROBLEMS
is statistically significant (p < .05).
However, at Time 2 severity of punish-
between the measure of percentage
change in certainty and crime rate
practical purposes, completely unrelated.
change. However, the relationships between percentage change in certainty
Three of the associations are negative
and three are positive, with the highest
being Phi - .12 for auto theft. If there
is a correlation between the severity of
magnitude. Thirty-four of the 54 associations are positive, 18 are negative,
ment and rates of crime are, for all
and crime rate in Table 3, are both
inconsistent in direction, and low in
punishment and subsequent criminality,
and two are zero. Only six of the 54
our analysis-covering two points in
phi-coefficients are statistically signifi-
Again, questions must be raised con-
Thirty of the coefficients were com-
cerning the reliability of the deterrence
hypothesis.
An alternative test of the deterrence
puted at ?+L .11 or less. Only for assault
time-has not been able to show it.
cant, and four of these are positive.
does one find more inverse than positive relationships between change in the
hypothesis is given by an analysis of
certainty of punishment and the nine
changes in the certainty and severity of
punishment and changes in crime rates.
Table 3 contains the phi-coefficients for
measures of crime rate change. In brief,
percentage change in certainty 1950-
punishment will be followed by decreased levels of crime, or that de-
1960, 1950-1963, and 1960-1963 with
percentage change in crime rate for
selected periods.15 The first three
columns of Table 3 summarize the com-
puted relationships between change in
the certainty of punishment from 1950
to 1960 and change in rates of crime
for three periods of time. Columns
four through six give similar phi-coefficients for change in the certainty of
punishment 1950-1963, and the last
three columns give the correlations of
change in certainty 1960-1963, with
change in crime rate.
If the viability of the deterrence
hypothesis is to be supported, we would
expect consistent inverse relationships
15 It is difficult to determine the most
logical time periods to use in correlating
percentage crime rate change with percent-
age certainty change 1950-1960 and 19501963. The crime rates used were those that
seemed most logical to the authors in attempting to present the dependent variable
as following in part, or completely, after the
independent variable. Percentages of crime
rate change for other year periods were also
examined, however, and the pattern of findings was quite similar to that presented.
these data provide no support for the
hypothesis that increased certainty of
creased levels of certainty will be followed by increased crime.
Table 4 summarizes the computed
relationships between change in the
severity of punishment from 1960 to
1964 and changes in the rates of crime
for several four year periods: 19611965, 1962-1966, and 1963-1967. It
was expected that increased severity of
punishment would be associated with
decreased rates of crime, and that a
decrease in the level of severity would
be followed by an increase in crime.
The relationships involving change
in severity are as inconsistent as the re-
lationships involving change in certainty. The only statistically significant
relationship was a positive association
(.49) for larceny. Thirteen of the associations are positive and five are nega-
tive. The only consistently negative
relationships are found for burglary,
wherein non-significant associations of
-.21 were obtained for all three time
periods. Again, the data in Table 4
provide no consistent support for the
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TABLE 3
PHI-COEFFICIENTS FOR PERCENTAGE CHANGE IN CERTAINTY 1950-1960, 1950-1963, 19
OF PERCENTAGE CHANGE IN CRIME RATE FOR SIX MAJOR CRI
% CHANGE IN CERTAINTY % CHANGE IN CERTAINTY %
1950-1960
1950-1963
19
% Crime % Crime % Crime % Crime % Crime % Crime %
Rate
Rate
Rate
Rate
Rate
Rate
R
Change Change Change Change Change Change C
1955-1965 1959-1968 1960-1965 1955-1965 1959-1968 1963-1965 1
Homicide
Robbery
Assault
.10
.07
-.25
.43b
.19
.11
.20
.11
-.02
.10
.43b
.25
-.33a
.29
.38a
.33a
-.16
-.11
Burglary .07 .11 .25 -.02 -.15 .11 Larceny -.02 .16 .11 -.11 .16 .11 -.
Auto
Theft
.10
.18
.24
-.26
a = p <.05.
b = p <.01.
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-.04
-.0
210 SOCIAL PROBLEMS
TABLE 4
PHI-COEFFICIENTS FOR PERCENTAGE CHANGE IN SEVERITY 1960-1964
AND SELECTED PERIODS OF PERCENTAGE CHANGE IN
CRIME RATES FOR SIX MAJOR CRIMES
% Change in % Change in % Change in
Severity With % Severity With % Severity With %
Change in Crime Change in Crime Change in Crime
Rate 1961-1965 Rate 1962-1966 Rate 1963-1967
Homicide
Robbery
Assault
.00
.14
.28
.23
Burglary -.21
Larceny
.12
Auto
Theft
.06
.14
.06
.19
-.03
-.21 -.21
.16
.49a
.19
.12
-.09
a = p <.001.
deterrence hypothesis. The data do not
support a conclusion that an increase in
the severity of punishment leads to a
decrease in the rate of crime, or that
With regard to the certainty of pun-
ishment, Gibbs (1968) discovered a
strong inverse relationship between certainty and rates of homicide; and Tittle
reduced severity precedes an increase in
(1969:409) observed "strong and con-
criminality.
sistent negative associations . .. between
DISCUSSION
Neither Gibbs' (1968) nor Tittle's
(1969) findings offered strong support for the notion that severe punishment deters crime. Though both discovered a negative relationship between
severity and rates of homicide, Tittle's
analysis of additional offenses showed
this relationship to be consistently positive. The data in this study for Time 1
generally confirm these earlier findings;
however, for Time 2 some of the rela-
certainty of punishment and crime
rates . . ." for several offenses. Though
our data for Time 2 support their findings, the data for Time 1, Time 3, and
the analyses of change in certainty in-
dicate that this relationship is frequently neither strong nor consistent.
In fact, these data suggest that the correlation of certainty with criminality is
somewhat variable over time and highly
variable among offenses.
Inasmuch as the present findings are
somewhat inconsistent with Tittle's
tionships become slightly negative and
are all of low magnitude. Analysis of
change in severity and change in crime
cerning the certainty of punishment and
ship varies both among offenses and for
different time periods.
ticular, one might ask why Tittle
(1969:409) was able to observe such
rates further indicates that this relation-
Thus, the present data indicate no
consistent support for the hypothesis
that severe punishment deters crime. In
contrast with Gibbs (1968) and Titttle
(1969), this conclusion applies to
homicide as well as to the other crimes
examined.
(1969:419-423) major findings conrates of crime, an explanation of the
discrepancies seems warranted. In par-
"strong and consistent negative associations . . . between certainty of punishment and crime rates . . ."16 while
16 For the six offenses in Tittle's study
which correspond to the offenses studied
here, Tittle (1969:415) reported the fol-
lowing Tau-c coefficients between certainty
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Punishment and Crime 211
this study observed weaker and more
inconsistent relationships.
One clue is provided by Tittle, who
recognized that the denominator of his
certainty index and the numerator of
his deviance index were almost iden-
tical. The numerator of one, and the
denominator of the other, both contain
1959 and 1962 "crimes known to the
ousness is that Tittle used a product-
moment correlation with the random
data, while he used Kendall's Tau-C
with the real data. The meaning of this
comparison is difficult to assess, given
the diverse character of the measures
and their distributions. A second problem is that Tittle used 1,000 cases for
his single random correlation, whereas
fifty is the maximum number of cases
police" (Tittle, 1969:414-415) :
1960 + 1963 Admissions
Tittle's Certainty Index - 1959 + 1962 Crimes Known
1959 ? 1962 Crimes Known/2
Tittle's Deviance Index = Population 1960
In this regard, Tittle (1969:414) was
concerned "that a negative association
available for computation with real
data. It may be noted that with N =
automatically and spuriously produced"
as a consequence of their similar opera-
1,000, a product moment correlation
of r = -.07 is statistically significant
at p < .05. If Tittle had used the same
his findings represented stronger in-
number of cases in his random computations as were present in his real com-
between the two indices . . . could be
tional definitions. To be assured that
verse relationships than might be spuri-
ously produced, Tittle (1969:414) estimated the "maximum possible spurious
negative association which might occur"
between his two indices. This was ac-
complished by assigning random digits
to the terms of his certainty and devi-
ance indices in such a way that the
denominator of the first fraction (cer-
tainty) equalled the numerator of the
second fraction (deviance) for a total
of 1,000 cases. A product-moment correlation coefficient was then computed
at r = -.07 for "random certainty"
and "random deviance." Tittle (1969:
415) concluded that "associations
greater than -.07 in the data . . .
represent real rather than spurious asso-
ciations."
One problem with this test of spuriand deviance: Assault: -.46; Larceny:
-.37; Robbery: -.36; Burglary: -.31;
Homicide: -.17; Auto Theft: -.08. For
all but homicide and auto theft, the coefficients were statistically significant.
putations, (circa 50) a correlation of
r = -.27 would be required for sta-
tistical significance. Again, the comparison of diverse measures based upon
diverse sample sizes seems difficult to
interpret.
A third problem with Tittle's test of
spuriousness is that it was conducted
only for "total felonies," and thereby
failed to take into account real differ-
ences in the magnitude of appropriate
random numbers for the several specific
offenses. For example, the range in
the real data for 1959 homicides
known to the police is from 2 to 524.
For burglary, however, the range of
real 1959 crimes known is from 543
to 111,643. Assignments of "random
crimes known" for burglary should in-
volve much larger digits than those
assigned to homicide, or other crimes.
Finally, Tittle's test of spuriousness is
based upon a single generation of random data and a single correlation co-
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212 SOCIAL PROBLEMS
TABLE 5
COMPARISON OF PHI-COEFFICIENTS FOR TITTLE'S CERTAINTY
AND DEVIANCE MEASURES USING REAL AND
RANDOM DATA FOR SIX MAJOR CRIMES
Lower Upper
Mean of Std. Dev. Range of Range of
100 Phi- of Phi- 100 Phi- 100 Phi-
Phi- Coefficients Coefficients Coefficients Coefficients
Coefficients Using Using Using Using
Using Real Random Random Random Random
Data
Homicide
Data
-.17
Data
-.33
Data
.14
.04
Data
-.60
Robbery --.33a -.35 .17 .20 -.76
Assault
-.54e
-.34
.16
.04
-.68
Burglary -.38b -.37 .15 -.04 -.68
Larceny
Auto
-.10
Theft
-.34
-.20
.15
-.35
.04
.14
.04
-.68
-.68
a=p <.05.
b = p <.01.
e = p <.001.
efficient. Thus, it is impossible to assess
the sampling distribution from which
the r = -.07 was drawn.
is repeated a total of 100 times for each
crime category. The results of computations with random data are then com-
In the present study an effort is made
to compute the random spurious factor
in a manner that tries to avoid the
pared with recomputations of Tittle's
(1969:415) original relationships using
aforementioned problems. The first two
association.17
problems are minimized by using the
same measure of association (Phi) for
both random and real data and by using
50 cases in both sets of computations.
The differences among the offenses
are taken into account by randomly as-
signing digits that fall within the
real data, and the same measure of
Table 5 contains the phi-coefficients obtained when Tittle's (1969)
certainty and deviance indices are correlated using real data. The table also
summarizes the results of correlating
Tittle's (1969) indices using random
data. The mean of 100 "random phi-
parameters of real data for the terms
of Tittle's certainty and deviance in-
coefficients" for each offense is given,
as well as the standard deviation and
dices. That is, Tittle's (1969:412-413)
the range of the 100 correlations. From
this table, it is apparent that the random
operational definitions for certainty and
deviance are used, and digits are randomly assigned from within the range
of actual data for "Admissions to
Prison," "Crimes Known to Police,"
and "Population" for each offense and
state. The indices of "random cer-
17 That is, Tittle's (1969:412-413) orig-
inal operational definitions of certainty and
deviance were used, and the real data were
analyzed in 2 X 2 tables, with the respective
distributions divided at the median. Phicoefficients were computed for each of the
six offenses, and are referred to as "real"
tainty" and "random deviance" for the
50 states are then correlated for each
phi-coefficients, because they were computed
of the six crimes, and the entire process
definitions.
from real data, using Tittle's operational
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Punishment and Crime 213
relationships between certainty of punishment and rates of crime vary from
one random assignment of digits to an-
other (columns 4 and 5) but are--on
the average-appreciably higher for
individual offenses (column 1) than
reported by Tittle (1969:414-415)
using product moment correlation (r =
-.07) for total felonies.
Most important, there appears to be
little difference between the mean of
100 "random" phi-coefficients and the
phi-coefficients based on real data. The
largest (-.54) and smallest (-.10)
of the real relationships fall well
within the range of random relationships for the respective offenses (assault
and larceny). Of the total of 600 correlations between random certainty and
random deviance, only none are positive. For the one offense-assault-in
which the real relationship exceeds the
average random relationship, it may be
noted that nine of the random phi-coefficients are greater than the apparent
real correlation.
From this perspective, it may be sug-
gested that Tittle's (1969) findings for
specific offenses probably do not exceed
what could "be automatically and spuriously produced" by the similarity of
terms in his certainty and deviance indices. It should be noted at this point
that the operational definitions for cer-
tainty and deviance used in this study
are somewhat affected by the methodological problems discussed above. The
indices used in this study do not have
identical terms in the denominator of
the certainty measure and the numerator of the deviance measure; however,
crimes known to the police are so
highly correlated from year to year that
the same problem of correlated bias is
likely to be present. This probably explains why the phi-coefficients in Table
1, though not as consistent as Tittle's,
are negative in all but one instance. If
it were not for this correlated bias the
findings would have likely been even
more sporadic and inconsistent for the
various crimes at the different points in
time.
If it is assumed that Tittle's findings
for the certainty of punishment are no
greater than could be spuriously and
randomly produced, and that the present findings, although not consistent
with Tittle's, are still affected by the
same correlated bias, one of two con-
clusions may be appropriate. The most
obvious conclusion might be that cer-
tain and severe punishment fails to
deter crime, or at best, provides a
deterrent effect that varies among of-
fenses and over time. For reasons to be
summarized below, however, this conclusion may be inappropriate. In this
regard one might at least suggest that
conclusive support for deterrence theory
has not been found in this research.
A second possible conclusion, and
one that bears directly upon the first,
is that the entire question of deterring
crime through punishment may be inadequately addressed through the use
of available aggregate data. If, in fact,
punishment does deter criminal behavior-a conclusion unsupported in
this study-then it may be unreasonable to expect data from Uniform
Crime Reports and National Prisoner
Statistics to establish that fact.18 In the
first place, this "structural" approach
minimizes the possibilities of controlling for non-punitive factors affecting
the crime rate (dependent variable).
As noted by Gibbs (1968:517):
s18 Both Gibbs (1968:522-523) and Tittle
(1969:411-412) have indicated a concern
for the adequacy of these kinds of data, and
their conclusions are apparently tempered by
acknowledged deficiencies in the available
sources of information.
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214 SOCIAL PROBLEMS
At least two sets of factors may jointly
determine the crime rate: (1) the eti-
changes in the age distribution of the
population, or changes in the concen-
(2) the repressive, meaning aspects of
areas.21 In brief, "crimes known to the
ological, meaning those extra-legal conditions which are conducive to crime; and
reaction to crime which operate as deterrents. If there is any validity whatever to
theories on criminality, then there are
extra-legal conditions that generate high
rates of crime; and whether a given type
of reaction to crime has a deterrent effect
cannot be determined unless these etiological conditions are held constant.19
In addition to etiological variables,
any number of additional factors bear
directly upon the level of crime as
tration of that population in urban
police" are probably sensitive to so
many extra-punitive factors, that their
use in measures of certainty and criminality is ill-advised for deterrence research. This sensitivity could account, in
large measure, for the discovered vari-
ability of relationships between Time
1, Time 2, and Time 3, reported in
Table 1.
represented by "crimes known to the
police." The level of crime is respon-
The variability of the findings, both
between and within offense categories,
further suggests that future research
crime to the police, and the recording of
might fruitfully test these relationships
for other types of criminality and other
sive to changes in the reporting of
crime by the police. In no way can a
consistency be assumed in either dimension of reporting,20 and changes in the
dependent variable may be more a consequence of reporting fluctuation than
a consequence of changes in the certainty and severity of punishment.
Further, the level of crime may reflect
19 Tittle (1969:414-415) has apparently
attempted to control for several variables
with presumed etiological significance for
crime rates. The relationships between certainty, severity, and deviance were compared
for different levels of urbanization, age, and
sex composition, and educational and industrial characteristics of the states. Little appears to have been added to an understanding of the relationships between certainty,
severity, and deviance with the inclusion of
the additional variables.
20 For a discussion of problems in the
under-reporting of crimes to the police, see
the victimization survey conducted by the
National Opinion Research Center (President's Commission, 1967:17-19) wherein
the extent of under-reporting and reasons for
non-reporting of crimes to the police are
suggested. The impact of irregularities in the
reporting of crime by the police is discussed
in the same volume (1967:22-24), wherein
precipitous jumps in rates for specific crimes
and jurisdictions may be attributed to
changes in police administrative policy.
periods of time. It may be that deterrence theory is more applicable to those
offenses and situations in which the
fear of stigma, produced by arrest and
adjudication, is greatest. The "respect-
able middle-class" citizen who might
engage in fraud or embezzlement may
be deterred by this threat, while the
potential armed robber or thief, having
less to lose, might be willing to ignore
the probabilities of apprehension.22 For
white-collar criminals, the threat of de-
gradation and loss of status may be the
crucial dimension of deterrence, far
out-weighing the certainty of incarceration or the severity of sentence.
However desirable, the expansion of
this analysis to include additional offenses and time periods is all but im-
possible with the existing data used
here and by Gibbs and Tittle. Alternative periods of time are difficult to study
21 Crime and its Impact: An Assessment
(President's Commission, 1967:24-28) also
summarizes the effects of these and other
sociological factors upon rates of crime.
22 For a discussion of the effects of ap-
prehension on "respectable" citizens, see
Cameron's (1967:115-120) study of naive
shoplifters.
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Punishment and Crime 215
because admissions to prison by state
and offense are available in National
Prisoner Statistics for only a few time
periods. Alternative offenses cannot be
examined because "crimes known to the
police" are not specifically enumerated
by Uniform Crime Reports for offenses
other than the seven included in the
"crime index."
Finally, by using these broadly based
available data, we may be ignoring a
third dimension of classical deterrence
theory: the celerity of punishment.
Even without the problems surrounding "crimes known to the police," the
necessary elimination of celerity of punishment from this type of analysis could
account for our inability to show the
deterrent effect of certain and severe
punishment. Quite possibly, if one were
to control for the speed of administering justice, then the effects of certainty
and severity might be realized. With
available structural data, however, such
control is not possible.
For these reasons, it is suggested that
future empirical research on the question of deterrence should not be based
upon available macroscopic data.
Rather, an attempt might be made to
follow a number of individual cases
through the criminal justice system to
determine the celerity, severity and certainty of punishment, and to assess the
impact of that punishment upon be-
havior of the individual and of his
peers and significant others. The opera-
tional definition of "punishment"
might be expanded to include arrest
and adjudication, inasmuch as these
may prove to be as effective as incar-
ceration in deterring some types of
offenders.
To examine the broader societal im-
probabilities of apprehension, adjudication, and incarceration for different
kinds of criminal acts; and (2) the
severity of punishment that is likely to
accompany that adjudication. Without
such awareness, existing penalty structures may have little deterrent effect.
Finally, future research should make
distinctions between general deterrence
(the impact of punishment on potential
offenders in the population) and specific deterrence (the impact of punishment on the offender).23 Some of these
distinctions are implicit in past research
but need to be made explicit and ex-
amined in more detail since the two
kinds of deterrence imply widely divergent mechanisms of control.
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BEING DISCOVERED: A STUDY OF HOMOSEXUALS
IN THE MILITARY
COLIN J. WILLIAMS and MARTIN S. WEINBERG
Indiana University
Current conceptions of deviance have placed less emphasis on the role played by
the deviant himself in being assigned a deviant label. To examine the role of the
deviant, a sample of male homosexuals who had received less than honorable discharges from the military for homosexual conduct (LHD group) were compared
with a sample who had received honorable discharges (HD). It was found that,
compared to the HD group, the LHD group was more likely (a) to have been engaging in homosexual sex more frequently before induction, (b) to have experienced
more frequent homosexual sex while in the service, and (c) to have had predominately other servicemen as homosexual partners. Further examination of the data
showed how these factors specified the manner in which members of the LHD group
were discovered.
Current among sociological conceptions of deviance is an approach that
concerns itself less with the attributes of
for both labellers and labelled. How-
ever, despite the emphasis laid on devi-
ance as a product of interaction, in
the person or persons said to have violated a social rule than with the char-
practice most attention has been paid
acter of the reactions of other persons to
Social control agencies have been especially focused on; most of the findings
have documented the discrepancies between formal statements of procedures
and actual operating procedures and the
immense power of control agencies in
the social production of deviants (cf.
these attributes and events. This approach, sometimes called the "labelling"
approach to deviance, sees the deviant
as a social product, the outcome of
interaction sequences between labellers
and labelled ) cf. Becker, 1964a). The
questions that are raised by this ap-
proach thus concern the behaviors that
are labelled as deviant, what the processes are by which the labels are successfully applied or avoided, and what
the consequences of such processes are
to the labeller's role in this process.
Scheff, 1964; Sudnow, 1965; Chambliss and Liell, 1966).
The emphasis on labelling, rather
than the attributes of deviants, has been
rich in its contribution to a better
understanding of deviance as a social
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