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University of New Hampshire

University of New Hampshire Scholars' Repository

Master's Theses and Capstones Student Scholarship

Winter 2010

Capital Punishment and Specific Offense

Deterrence

Brian Giardina

University of New Hampshire, Durham

Follow this and additional works at:https://scholars.unh.edu/thesis

This Thesis is brought to you for free and open access by the Student Scholarship at University of New Hampshire Scholars' Repository. It has been accepted for inclusion in Master's Theses and Capstones by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contactnicole.hentz@unh.edu.

Recommended Citation

Giardina, Brian, "Capital Punishment and Specific Offense Deterrence" (2010).Master's Theses and Capstones. 138.

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Capital Punishment and Specific Offense Deterrence

BY

Brian Giardina

BA, University of New Hampshire, 2009

Thesis

Submitted to the University of New Hampshire

In partial fulfillment of

The requirements for the degree of

Master of Arts

in

Justice Studies

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UMI Number: 1489955

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This thesis has been examined and approved.

essor of Political Science

ctóffSusan Siggelakis,

Associate Professor of Justice Studies Charles Putn

/

Dr. Cesar J. Rebellón, Associate Professor of Sociology

\Z/<V io

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TABLE OF CONTENTS

LISTOFTABLES iv

ABSTRACT vi

CHAPTER PAGE

INTRODUCTION 1

I. A RECENT HISTORY OF CAPITAL PUNISHMENT IN THE UNITED

STATES 3

II. EXISTING CAPITAL PUNISHMENT RESEARCH 8

III. EXPLANATION OF CURRENT STUDY 17

A. DATAAND MEASURES 17 B. METHOD 19 IV. RESULTS 22 A. PRELIMINARY RESULTS 22 B. FIRSTHYPOTHESIS 22 C. SECONDHYPOTHESIS 23

V. DISCUSSION AND FURTHER

RESEARCH 25

VI. LIST OF REFERENCES 29

VII.REFERENCE NOTES 32

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LIST OF TABLES

TABLE

PAGE

1 . Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2000 34

2. Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2001 35

3. Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2002 36

4. Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2003 37

5. Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2004 38

6. Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2005 39

7. Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2006 40

8. Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2007 41

9. Regression Coefficients for Multiple Regression analyses for law enforcement

Officer Deaths in 2008 42

10. Regression Coefficients for total executions in year (M) and law enforcement

officer deaths in 2000 43

1 1 . Regression Coefficients for total executions in year (M) and law enforcement

officer deaths in 200 1 44

12. Regression Coefficients for total executions in year (M) and law enforcement

officer deaths in 2002 45

13. Regression Coefficients for total executions in year (M) and law enforcement

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14. Regression Coefficients for total executions in year (t-1) and law enforcement

officer deaths in 2004 47

15. Regression Coefficients for total executions in year (t-1) and law enforcement

officer deaths in 2005 48

16. Regression Coefficients for total executions in year (t-1) and law enforcement

officer deaths in 2006 49

17. Regression Coefficients for total executions in year (t-1) and law enforcement

officer deaths in 2007 50

18. Regression Coefficients for total executions in year (t-1) and law enforcement

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ABSTRACT

Capital Punishment and Specific Offense Deterrence

by

Brian Giardina

University of New Hampshire, December, 2010

Deterrence has historically been a justification for capital punishment. Recent studies have found deterrent effects as strong as eighteen murders prevented per

execution (Dezhbakhsh, Rubin and Shepherd, 2003). Most prior studies have tested for

deterrent effects on homicide rates generally. The current study looks for a deterrent effect on a specific type of capital crime; the felonious killing of law enforcement officers. Two separate hypotheses were tested. First, the presence of a capital punishment statute will deter this specific type of homicide in a given year. Second, executions for any reason will reduce the likelihood of this specific type of homicide in

the subsequent year. Results indicate no causal connection between rates of law

enforcement officers being killed and the presence of a capital punishment statute.

Further research at state and local levels is needed to test for more instances of potentially

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INTRODUCTION

In 2009 the New Hampshire General Court passed House Bill 520 creating a

commission to review the implementation, legality, and future of capital punishment.

The bill charges a 22-member commission with the task of determining whether capital

punishment serves the interests of the State of New Hampshire as well as victims and

citizens. Differing expert opinions and justifications have been brought before the

commission to explain the use of capital punishment. This commission, like similar

bodies in other states, is faced with a difficult task. Gaps in the literature and differing

moral perspectives frequently complicate the debate over capital punishment.

Previous capital punishment research has been focused on deterrence theory. The

central tenets of deterrence theory were outlined by Cesare Beccaria in Of Crimes and

Punishments (1 764). According to Beccaria a punishment must meet four requirements

in order to serve as a deterrent: celerity or quickness, certainty of punishment, severity or

proportionality and exposure to general public. Deterrence theory lost favor among

criminologists in the earlier part of the 20* century, but it was revived by those who

sought to apply economic principles to crime (Becker, 1968). Raising the costs

associated with committing crime lowers the expected gain and, according to the theory,

makes committing crime less profitable or advantageous. Isaac Ehrlich applied economic

principles to this issue in a groundbreaking study (1975). He found that for every

execution, eight innocent lives are saved (Ehrlich, 1975). The methodology used in that

study has been criticized by criminologists and recalculated in the following 25 years,

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to tweaking by removing certain years and generally inconclusive (Bowers and Pierce, 1975). This has not stopped the reapplication of econometric principals of analysis to

capital punishment and deterrence.

Currently deterrence theory exists in two forms, both general and specific. General deterrence is when punishments are aimed at deterring the entire public, including those who did not commit a crime. This particular type of deterrent effect is measured by testing crime rates and, in the case of the death penalty, homicide rates.

Research on capital punishment and general deterrence is divided. Some studies show

that homicides can be prevented by using capital punishment (Shepherd, 2005; Rubin 2002). Other studies have used similar methods and data and found no significant deterrent effect (Kovandzic, Vieraitis and Boots, 2009). Specific deterrence is when a deterrent effect is measured only for the individual who committed the crime. This can be measured by reoffending and recidivism rates. Due to the "final" nature of capital punishment, specific deterrence is not researched in capital punishment literature.

However, both types of deterrence theory can be combined to look for a deterrent effect

on capital crimes. This has been done in the past, (Peterson & Bailey, 1994 and Fagan,

Zimring and Geller, 2006), but no deterrent effect was found.

The deterrence question has sometimes been framed as, "Does capital punishment deter as well or better than life without parole?" (Bedau, 2004) This question, one of marginal deterrence, has been the subject of prior research (Fagan et al., 2006). However, the question asked here is different, i.e., does the presence, or use, of capital punishment grant law enforcement officers extra protection they would otherwise not have? The

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extra protection would be the deterrent effect, reducing the number of felonious law enforcement deaths and making it safer to be a police officer.

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CHAPTER I

RECENT HISTORY OF CAPITAL PUNISHMENT IN

THE UNITED STATES

Capital punishment had been practiced in Europe and most cultures around the

globe for centuries before exploration of the new world. Early European settlers brought

capital punishment customs with them to this continent. The first execution by the

settlers took place in 1608 when a Virginia man was put to death for being a Spanish spy

(Encyclopedia of Criminology, 2005). All of the original colonies had capital punishment

statutes, some which outlined as many as 12 death-eligible crimes. Executions were public affairs, meant to deter and dissuade potential offenders. In this time executions

were mandatory if a person was found guilty of a death-eligible crime. Men, women and

young adult offenders were subject equally to these harsh laws. Capital punishment has

existed for most of human history and is experiencing an increase in types of reform

during the past half century. Judicial and legislative actions are at the forefront of

controlling capital punishment.

Reform, over time, has changed capital punishment from public hanging to its

procedurally dominated current incarnation. States moved executions out of the public

eye in order to prevent the riots that typically followed, forgoing any deterrent effect in

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for discretion in seeking capital punishment. Previously all states had mandatory death

penalty statues for anyone convicted of a capital crime. All similar mandatory statutes

were not removed from state law until 1963.

The pivotal moment for capital punishment in America was the 1972 case Furman

v. Georgia. The Furman Court decided that the arbitrary nature of capital punishment,

which had partly been introduced earlier in the century with the removal of mandatory

death sentences, had made the punishment unconstitutional. While the Furman Court did not rule that capital punishment was categorically unconstitutional, this decision did

overturn all current state statutes. Many states quickly passed new capital punishment

laws to correspond with the courts decision. To conform to the ruling states introduced

reforms including a bifurcated trial process involving a guilt phase and sentencing phase

and the inclusion of enumerated mitigating and aggravating factors to guide the

sentencing process. The new laws were tested in court and a ruling in Gregg v. Georgia

approved "guided discretion" statutes (Encyclopedia of Criminology. 2005). The court

imposed moratorium lasted 5 years', and the execution of Gary Gilmore in 1977 began

the modern period of capital punishment in the United States (Encyclopedia of

Criminology, 2005).

Recently the Supreme Court has gotten involved again with the shape and

direction of capital punishment in the United States. Three cases all decided between

2002 and 2008 have affected profoundly the way Americans perceive and use capital

punishment.

Atkins v. Virginia, decided in 2002, was a landmark case because the US Supreme

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punishable by death. Previous to this decision Supreme Court jurisprudence had allowed

for the execution of the mentally handicapped. Writing for the majority in the 1989 case

Penry v. Lynaugh Justice O'Connor wrote;

[There is not] sufficient objective evidence today of a national consensus against executing

mentally retarded capital murderers, since petitioner has cited only one state statute that explicitly bans that practice and has offered no evidence of the general behavior ofjuries in this regard."

Both public opinion and the Court shifted away from that point of view.

The majority believed that procedures testing competency to stand trial and the insanity

defense would protect the severely mentally retarded. On these beliefs the Penry Court

concluded that the Eighth Amendment did not categorically exclude capital punishment

of the mentally handicapped. The fact that the Atkins Court reversed that conclusion only

13 years later is evidence that the moral standards, at least as they bear on the legal

standards surrounding capital punishment, are constantly under review.

In 2005 the Court in Roper v. Simmons altered capital punishment by preventing

an offender from facing the death penalty if the crime was committed before the offender

was 1 8. 16 years earlier the Court determined that the Constitution did not prohibit the

execution of offenders who were younger than 18 at the time they committed capital

murder. The Roper Court reasoned that a national consensus had developed against the

practice since its ruling in Stanford v. Kentucky.

In 2008 the Supreme Court further limited the applicability of capital punishment

to offenses resulting in a homicide or crimes against the state''. Kennedy v. Louisiana

pronounced a Louisiana law allowing for capital punishment of child rapists who did not

kill their victims unconstitutional. The decision had a sweeping impact on all similar

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Statutes throughout the country. Now, in the majority of cases, the only person who can

have his/her life taken is one who has taken a life.

Capital punishment as an American enterprise has evolved significantly through

both the judiciary and the legislature. Support for capital punishment remains strong in

certain states and within certain populations'". However, the justifications and usage

patterns of the practice have evolved significantly over time. Political decisions, including judicial review and legislative action, will continue to dictate the use and

evolution of capital punishment. As rates of law enforcement deaths trend upwardsiv, a

way to protect law enforcement officers is necessary. If capital punishment is found to protect law enforcement it would strengthen its value to both the public and to

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CHAPTER II

EXISTING CAPITAL PUNISHMENT REASEARCH

Prior capital punishment research on deterrence can be split into two separate

types; deterrence of homicide generally and deterrence of specific types of homicides.

Findings are split between a null effect and deterrent effect. Past studies have looked at

both national and state levels for evidence of deterrence. Along with competing

strategies for analysis there are competing view points. Capital punishment and

deterrence are debated by criminologists and economists, each focusing on separate

indicators and reaching different conclusions.

A study by Shepherd (2005), an economist, used aggregated data to compare

state-to-state homicide rates with individual state execution rates. This study tested

whether each state experienced its own deterrent effect relative to the number of

executions it performs. Shepherd concluded that national averages that measure

deterrence are raised by a few states with high execution rates and high ratings of

deterrence. Only six of the eligible states experienced a deterrent effect, but 13

experienced a "brutalization" effect. Brutalization is when statistical tests indicate that

capital punishment has increased the murder rate when compared to jurisdictions without

capital punishment. States with capital punishment statutes do experience a significant

deterrent effect but only after they have reached the threshold number of executions to

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cause deterrence (Shepherd 2005, p. 240). States can also experience a deterrent effect

by returning capital sentences without performing an execution. Most states experienced

neither a deterring nor brutalizing effect. These results suggest that the presence of

capital punishment can be a deterrent even if it was never used. Shepherd also concludes

that executions can deter all types of murder, including crimes of passion. The addition

of the threshold as a consideration for deterrence improved upon past research. By

looking at each state separately Shepherd was able to separate the states that experience

deterrent effects from states that experience brutalization or null effects. However, this

study was aimed at the deterrent effects of capital punishment on all homicides and not

on a particular subset.

Econometric analyses have also been performed recently that use state data to find

an opposite effect from Shepherd (Kovandzic, Vieraitis and Boots, 2009). Taking recent

criticisms of Ehrlrich's 1975 study into account, Kovandzic et al. tested deterrence theory

from 1977 to 2006. This study used more recent and reliable data, estimated further past

the year 2000 and used more efficient methods for estimating standard error. The authors

tested for several possible deterrent effects including: the presence of a death penalty

statute, returning a sentence of capital murder, execution of an offender and frequency of executions. The authors hypothesized that any one of these factors, or a combination of them, would produce a deterrent effect. Any or all of the perceived factors would

supposedly enter the mind of an offender and be used in a crime calculation.

Kovandzic et al. also included an extensive list of possible controlling factors.

These factors were sociopolitical in nature, covering everything from the

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concealed carry handgun laws and the gallons of beer consumed in any given state. The authors believed that these factors could control for differences

between DP and non-DP states. While some of the variables were eliminated after further analyses, it is possible that collinearity existed between controlling

variablesv. Having too many controlling variables, or having them be collinear,

could have affected the results of this study. It could be one of the reasons why

this study did not find the same deterrent effects as earlier, similar studies.

Kovandzic et al. also focused on the criminal calculus, i.e., the concept that

offenders consider the costs and benefits of an anticipated criminal action. They

determined that, for any deterrent effect to exist, the perceived risk factors of execution

would have to be sufficiently high. A reason for this focus could be the economic nature of the researchers and the analysis. This study cites research to show that, when

offenders perform the criminal calculus, they very infrequently consider long term results. When they do they are more focused on the potential gains rather than the punishments (Kovandzic et al., 2009 p. 834). Social science has shown that offenders engaged in the criminal calculus are prone to discount risk and inflate the value of their actions based on skills or knowledge they havevl. The ineffectiveness of factors relating to capital punishment to enter the criminal calculus, and thus the criminal mind, before committing an offense, has the authors conclude that any deterrent effect would be very small if at all and that any national deterrent effect is biased by a few states. However, the research that is cited here does not mention capital murder. All of the criminal anecdotes discussed are from lower-level offenders (Kovandzic et al., 2009 p. 834). The Criminal calculus will be different depending on the risk assumed. An identity thief does

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not assume the same risk as someone who kills a police officer, therefore the potential to

gain is different. The nature of the criminal calculus is complex and most likely different

for every individual. Trying to characterize all criminals as thinking one way or another

is impossible.

One drawback to this study is that states that passed capital punishment legislation

before the year 1977 were excluded from parts of the analysis. This affected the test for

deterrence using the existence of a statute as the major indicator. Studies in the past have

found that the presence of the death penalty can be a deterrent even without its use

(Shepherd, 2005). This methodological shortcoming limited the ability to test this

hypothesis fully. The majority of states with capital punishment statutes passed current

laws before 1977. This would cause them to be excluded from this test. Those states

were considered in later analyses in this study, but this problem makes one of the major,

possibly-deterring factors invalid. The presence of capital punishment within a state is

important because it may contribute to deterrence not of homicide generally, but of some

homicides in particular. It is possible that some civilians do not know whether or not

their state practices the death penalty, but most offenders would be aware if the state they

reside in uses of capital punishment. For this reason the presence of the statute could be a

deterring factor and this test should be redone to account for the missing states.

Econometric studies rely on complex statistical methods to generate results. Kovandzic et al., (2009) criticize earlier studies methodologies for their failure to correct

for serial autocorrelation""1 and heteroscedasticityvl". These statistical problems may have

caused some of the earlier studies to underestimate their standard errors. Underestimated standard errors will cause factors that would normally be statistically insignificant to

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appear significant. However, not all econometric studies on deterrence use the same

correction method as Kovandzic et al. Paul Zimmerman (2009) describes some of the

faults of the cluster correction method for autocorrelation. It can cause intervening

measures that would have some effect to appear as though they had no effect. According

to Zimmerman, there are other methods to correct for serial autocorrelation and

heteroscedastic data. No one method is accepted for resolving this problem. Possibly

that the method used by Kovandzic et al. underestimated the significance of potential

deterring factors by using cluster sampling correction methods. Due to differences in

statistical estimation methods econometric analyses of capital punishment at the national

level are inconclusive.

One criticism of capital punishment research is that it relies on aggregated

national or state level data. This type of data is not ideal for tracking small variations in

homicide rates. Small variations caused by a deterrent effect could be more likely in a

state like New Hampshire with both a low homicide and low execution rate. Studies have been conducted with disaggregated data looking for a localized deterrent effect

(Hjalmarsson, 2009). Hjamlmarsson (2009) used disaggregated data to compare

homicide rates immediately following sentencing and executions in three Texas cities.

When executions are carried out there are 23.6% fewer capital murders in the three days

following an execution (Hjalmarsson, 2009). Despite this study that found no significant

long-term effect when considering all types of homicides, the results may not reflect New

Hampshire or other states. Many social and demographic variables about the cities in this study do not correspond to conditions in many states. These variables could affect both the homicide rate and the propensity to be deterred. The regional and cultural differences

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could also affect unseen variables that govern these relationships, like average education

or kinship felt between towns. The three cities considered by Hjamlmarsson (2009) all

have populations significantly higher than the state ofNew Hampshire as well as

different racial and socioeconomic breakdowns from most US states (US Census.gov).

The method of using disaggregated data and tracking media exposure will have different

results in distinct demographic and geographic situations and could produce results

favorable to deterrence theory. Hjamlmarsson's work suggests that the deterrent effect of

the death penalty can be measured with both aggregate and disaggregated data. The same

research could be modified to look over longer periods of time and at specific types of

homicides. Further research is needed with disaggregated data in other locations to find a

deterrent effect.

Economists are conducing the most recent empirical research. Econometric

analyses have dominated the public policy debate on the effectiveness of capital

punishment. As seen above, the results of econometric analyses, while complex and very

specific, are subject to judgments involving methodology. Due to differences in

methodology, economists are divided on the efficacy of capital punishment. However,

criminology as a field, is not. The American Society of Criminology only has two

positions it endorses as matters of policy. Adopted in 1989 the official policy of the ASC

regarding capital punishment reads;

Be it resolved that because social science research has demonstrated the death penalty to be racist in application and social science research has found no consistent evidence of crime deterrence through execution, The American Society of Criminology publicly condemns this form ofpunishment, and urges its members to use their professional skills in legislatures and courts to seek a speedy abolition of this form ofpunishment.

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Radelet & Lacock (2009) conducted a survey of leading criminologists' current views on

capital punishment. Findings show that a large majority of criminologists do not believe

that capital punishment adds any significant deterrent effect not already produced by life

without the possibility of parole. Only 9.2% of the criminologists surveyed believed "the

death penalty significantly reduces the number of homicides" to be a true statement

(Radelet & Lacock, 2009). Results also indicate that criminologists in 2008 are less

supportive of capital punishment then ever before. Comparing responses from this study

to a similar study from 1996, opposition to capital punishment and disbelief in deterrence

either increased or stayed the same in all questions. When asked if executing people

deters others from committing murder only 2.6% of the criminologists who responded

agreed compared to 89.6% disagreeing (Radelet & Lacock, 2009).

In critiques of econometric or deterrence-based capital punishment research

criminologists have adopted the idea that possible deterrence of specific types of

homicides (Fagan, Zimring and Geller, 2006) A question in general deterrence research

has been the percentage of homicides that are either "death-eligible", or, able to be

deterred. No variation in the percentage of death eligible killings was found even as

execution rates increased. Death eligible killings amount to 25% of total criminal

homicides (Fagan et al, 2006). The largest portion of these is felony murder, where a

homicide occurs in the commission of another felony. This conclusion is questionable

because not all states have such a comprehensive felony murder statute. According to the

study, 43.7 % of capital punishment eligible homicides occur during the commission of a

robbery (Fagan et al., 2006). However, of the homicides considered in this study, only

1.1% were related to the felonious killings of law enforcement officers. This study,

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conducted in Texas, used the Texas statutory framework for capital punishment. Texas is

of special interest to capital punishment and deterrence research for several reasons. According to Fagan et al. (2006) Texas accounts for more than one-third of executions

since the Supreme Court reversed itself in 1 976. The capital punishment statute in Texas

does not reflect capital punishment statutes in other parts of the country. Felony murder,

the crime most likely to be charged with to create a capital case, is not a death eligible

crime in some states, including New Hampshire. Texas performs more executions than

any other state. Some criminologists have claimed that, by excluding Texas, the deterrent

effects found in econometric studies are removedlx.

Criminological research on the likelihood that capital punishment protects law

enforcement officers through deterrence has been conducted (Sellin, 1959; Bailey 1982;

Bailey & Peterson, 1994). Sellin (1959) found that, the average police homicide rates

between cities with and without capital punishment were nearly identical. This study with

conducted by comparative methods and did not use multivariate regression. Sellin (1959)

calculated rates of police killing by general population while later studies, (Bailey, 1982;

Bailey & Peterson, 1987, Bailey & Peterson, 1994) used an average calculated by deaths

per 1000 police officers.

Multivariate regression analyses were performed by Bailey (1982) and Bailey and

Peterson (1987). These studies analyzed data for years 1961 to 971 and 1973 to 1984 respectfully. Multivariate regression was used to determine and eliminate the influence

of controlling variables. No evidence of deterrence was found in either study.

Bailey & Peterson (1994) improved on prior research by measuring media

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inclusion ofmeasures to calculate certainty and quickness and quickness ofan execution

along with media exposure tests more ofthe components ofdeterrence theory. This study

tested the components ofdeterrence theory on the specific question ofcapital punishment

and its ability to potentially protect law enforcement officers. Several ofthe controlling

variables used in this study are adapted for use in the current study. Results did not show

any indication of deterrence.

Past studies looked for deterrence within the law enforcement community (Sellin,

1959; Bailey, 1982, Bailey & Peterson, 1982 Bailey & Peterson, 1994) or on deterrence

in general (Shepherd, 2005; Kovandzic et al., 2009). Both econometric and

criminological approaches have been used. Criminology and economics are both testing

the deterrence hypothesis in different ways. Previous studies had one or more ofseveral

issues; multiple regression analysis was not used, the question was not ofspecific

deterrence, not being focused on an offence punishable by death in all 50 states,

statistical issue(s) that caused results to be questioned.

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Chapter III

EXPLANATION OF CURRENT STUDY

Data and Measures

The dependent variable in both sets of models is the felonious killing ofpolice

officers. Data were gathered from the years 2000 to 2008 from the FBI's Uniform Crime

Report It is hypothesized that the relationship between law enforcement deaths will be

dependent, net of controlling factors, on the presence of a capital punishment statute. To

show deterrence the relationship would appear negative; with the presence of a capital

punishment statute resulting in lower law enforcement deaths. It is also hypothesized that

executions in a previous year will reduce the number of officers killed in the following

year. Felonious law enforcement deaths were selected as a more specific measure of

deterrence because all US jurisdictions with capital punishment have a provision for law

enforcement death. Recent research on deterrence of specific offense types was focused

on crimes that were not universally punishable by death (Fagan et al, 2006). The Current

study aims to produce results which are applicable to all capital punishment jurisdictions.

For the first test the independent variable is the presence of a capital punishment

statute. It is meant to test the hypothesis that the presence of a statute would offer extra

protection to law enforcement officers. In the second test the independent variable is

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any kind in a given year will have impact on law enforcement deaths in the following

year.

Additional measures were included to explain variation between the states. These

variables make it possible to compare states with drastically different crime rates and law

enforcement needs. Five controlling variables were included: urbanization, homicide

rate, percent non-white, average high-school graduation and population. Controlling

variables were added in different models to test their explanatory power on the dependent

variable.

Data for this study were gathered from multiple sources. All crime data, homicide

rates and law enforcement homicides by year, were gathered from the FBI's Uniform

Crime Report. The Uniform Crime report is a compilation of officially reported crimes in

the United States. Though the accuracy of official report data has been called into

question in the past (see Elliott & Ageton, 1980; add other citations and also should

describe some examples of why and how official data might be said to sometimes be

inaccurate), the reliability of the homicide data is believed to be higher in comparison

with other official report data (add citations for this). Crimes go unreported or unnoticed,

but homicide rates are believed to be more accurate crime predictors.

Demographic data, including state population and state racial breakdowns, were

gathered from the United States Census website. Data on average high-school graduation

rates were also gathered from the US Census Bureau.

Data on total executions and executions by year was gathered from the Death

Penalty Information Centerx. The sample size for this study was 50. Washington D.C.

and all non-state territories were excluded from this analysisxi. Mediating and controlling

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variables for each state were calculated and included in order for models to more

accurately represent reality. By measuring and mediating the differences in the control

variables the results will reflect the differences related to law enforcement deaths and the

presence of capital punishment.

As a measure for urbanization a list was compiled of the 100 largest cities in the

United States. Each state was ranked based on how many of the cities were within that

state. States ranged from having 0 ofthe 100 most populous cities; 17 had zero, including

New Hampshire. California had the most with 15 of the largest 100. These data was

gathered from a website which compiles data on US cities™.

A variable was included to control for racial distribution among states. Earlier

studies on this topic (Bailey & Peterson, 1994; Bailey, 1982) included measures for racial

diversity. These studies used percent African-American which has been adapted to

percent non-white to be a better measure of racial diversity. Data were based on the 2000

US Census data. A measure was included to control for average educational attainment.

The percentage of high-school graduates within a state was attained by using census data.

In this study it is hypothesized that educational attainment will equalize some differences

between states and regions of the country.

Method

Multiple non-linear regression analyses were performed in Small STATA 10.

Several estimation methods were used to find the best fit for the data and to ensure the

validity of the results. OLS regression was not chosen due to the use of "count" data;

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data but was rejected for the first hypothesis due to a violation of a core assumption. Poisson regression and negative binomial regression were used at different points during the analyses. Poisson regression requires that the mean and the variance are equal to be consistent (Hübe, 2007). Poisson regression is often avoided due to a problem known as

over-dispersion. Over-dispersion will deflate the standard errors. This causes

significance to appear falsely for some controlling variables. This is similar to a Type-I error, finding a significant relationship when one does not really exist. More than half of the years analyzed in the first test were found to be over-dispersed. For this reason negative binomial regression is the method on which the first hypothesis is modeled. The second hypothesis was not over dispersed and is modeled using poisson regression.

The first hypothesis; the presence of a capital punishment statute will reduce the number of law enforcement homicides. To determine significance several independent and controlling variables were used. The dependent variable was set as the number of police officers feloniously killed in the line of duty with the existence of a capital

punishment statute over a nine-year period as the independent variable. Control variables include: homicide rate, percent non-white of state population, urbanization and average high-school graduation. Homicide rate, percent non-white and urbanization were adapted from Bailey & Peterson (1994) with average high-school graduation added for

exploratory purposes. Five models were run with each year with the fifth model including all controlling variables being the most accurate. Controlling variables were checked for

covariance and no significant correlation was found.

The second hypothesis; the presence of an execution, for any offense, in a preceding year will reduce the number of law enforcement officers feloniously killed in

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the line of duty in the following year. Poisson models were used to test the dependent

variable the number of officers feloniously killed. The independent variable was total

executions in the previous year. Controlling variable in this model included state

population and homicide rate.

The homicide rate for each year analyzed is included to determine whether

changes in the number of law enforcement homicides are a function of changing

homicide rates within individual states. States that have higher murder rates are going to

have a higher need for policing. A measure of crime is created using homicide rate and

population. This measure is similar to the studies conducted by Sellin (1959). Population

is used as a predictor of law enforcement assuming larger populations require more law

enforcement officers. Peterson and Bailey (1994) used the number of police officers

rather than overall population in their analyses on deterrence. However, controlling

variables for racial differences and urban differences from that study were adapted to this

one. By combining measures from both Sellin (1959) and Peterson and Bailey (1994) a

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CHAPTER IV

RESULTS

Preliminary results

Poisson regression was used to test the first hypothesis. Two out of nine years had significant results in the predicted direction. However, three out of the nine years were significant in the opposite direction. This modeling method was eventually rejected

due to over-dispersion and the negative binomial regression method was selected.

Over-dispersion was evident based on the mean and variance values displayed during testing. Values are assumed to be identical for Poisson but were more than three times apart in the

over-dispersed years.

First Hypothesis

A negative relationship between the presence of a capital punishment statute and

the total number of law enforcement killings per year would indicate deterrence. None of the years considered produced results to indicate that the presence of a capital

punishment statute would reduce the number of officers killed. Several years produced coefficients with the sign that would be consistent with the hypothesis but they were not

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The homicide rate was significant in six out of nine years. The relationship was positive with higher general homicide rates being accompanied by higher rates of law-enforcement deaths. This relationship was predicted due to similar results appearing in

an earlier study (Bailey & Peterson, 1994).

In six out of the nine years analyzed urbanization was a significant predictor. States that were higher on the urbanization scale used were statistically more likely to have higher rates of law enforcement homicide. Percent non-white was not significant in any of the models. Average high-school graduation was significant in two years, but in a

different direction for each year.

In five out of the nine years results suggested the opposite of deterrence, with the presence of a capital punishment statute resulting in the likelihood of more law

enforcement deaths. Due to limitations in these analyses no causal direction can be determined. In four of those years the significant positive relationship was eliminated with the inclusion of controlling variables. However, one of the nine years had a

significant relationship in the positive direction that was not mitigated by the inclusion of

controlling variables.

Overall puesdo-R2 values™1 varied from .08 to .23 for these tests. This could

mean that some of the models derived were not accurately tracking the differences

between the independent and dependent variables.

Second Hypothesis

In testing whether an execution during a given year reduces the likelihood of law enforcement deaths in the following year the Poisson model was reinstituted. These data did not suffer from over-dispersion like the first hypothesis. In three out of the nine years

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tested the executions were significant, but not in the predicted direction. Results indicate

that an execution will not reduce the amount of law enforcement deaths in the following

year and that states that have had an execution are statistically more likely to have law

enforcement officers killed than states that do not. Population was a significant predictor

in all models. States with higher populations were statistically more likely to have law

enforcement officers killed.

Homicide rate was significant in all but one of the years. The finding that higher general homicide rate results in more officers being killed is not surprising. It also supports results from the first hypothesis. Even when a control for population was introduced, higher homicide rates were the best predictors of law enforcement officers

being killed. R2 values ranged from .08 to .32.

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CHAPTER V

DISCUSSION AND FURTHER RESEARCH

No evidence for deterrence was found from either test and the results require the rejection of both hypotheses. Based on these results capital

punishment does not offer additional protection to law enforcement officers from lethal assault. However, the analyses performed here are methodologically limited. Improvements on the methodology could strengthen the conclusions and

drive future research.

These results are questionable due to low pseudo-R values. In some years the values indicate that the controlling variables had little to no impact on law

enforcement homicides. It is possible that the pseudo-R2 values for non-linear

regression are lower than for OLS regression. It is also possible that some intervening or mediating variables that affect law enforcement deaths were left out of these analyses. These analyses only covered a nine-year period between 2000 and 2008. A longer time series could more accurate model what is going on. The control variables in the current study could be improved for future research. This could be done with both the inclusion of new variables and the refinement of

existing variables. Factors might include, unemployment, percent of population

within 18-25, and average income could control for differences between states and regions to give a clearer picture of capital punishment. The variable for

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urbanization in this study, while an effective predictor, could be improved.

Counting the number of cities with a population of 1 00,000 or cities with over a

certain amount of police officers has the potential to be a better measure of

urbanization for these tests.

Washington D.C. and all Federal capital offenses were excluded from

these analyses. Initially, Washington D.C. was included but all significant relationships were erased with the inclusion of the additional factor. Washington D.C. is unique in that it has a high population with a high crime rate but does not have capital punishment. Future research could explore the potential impact of

Washington D. C. in studies that claimed to find a national deterrent effect.

A future study on specific offense deterrence and law enforcement could better

incorporate all of the attributes of deterrence, similar to Peterson & Bailey (1994) or Hjalmarsson (2009). Deterrence is founded on; celerity, severity, certainty and public exposure. These studies included measures of media exposure of

executions. It is possible that executions that are more public will have greater

deterrent effect than executions done in private. Throughout history executions were performed in public to increase the deterrent effect. This practice was stopped because of the immediate danger to public safety that was caused.

However, in the modern world of television, newspaper and internet news an execution could be very public without as much immediate danger to public

safety. Separating what is "public" and what is "public knowledge" becomes

important. In the past, with limited mass communication and media, executions

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at the same time their publicity. In the modern era publicity and public locale are

not as congruent. Executions could be very public without gathering a large

group into a potential dangerous situation. Increasing the amount of media

coverage or allowing for spectators remotely are ways that the publicity of

executions could be raised. These changes would affect the amount of deterrence any individual execution carries. A future study could test executions for

differences in media exposure and determine how much deterrence is affected by

these differences.

The role of deterrence research in legislative or judicial action is unclear.

States are reviewing the implementation of capital punishment and deterrence is a

possible justification. Research showing capital punishment improves police

safety, or public safety, would be a powerful tool in this debate. The US Supreme

Court is clear in its support for capital punishment. The Court has recently been

more willing to quantify and restrict certain specific attributes of capital

punishment. The evolving moral standards require that capital punishment is

monitored and that its application is not detrimental to society. The Court has

shown its willingness to restrict the practice of capital punishment to conform to

moral standards. Research that demonstrates where, when and how capital

punishment could be more effective, or effective at all, would be influential to this policy making process. The more the issue of capital punishment becomes

debated by legislatures the more important the position of the Supreme Court.

The question on deterrence is frequently reduced to one of marginal

deterrence; does it deter better than life without the possibility of parole? Studies

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on the possibility of deterring certain groups of people, certain localities

(Hjalmarsson, 2009) or certain crimes (Bailey and Peterson, 1994; Fagan, 2006)

fail to answer that question. Future research on deterrence should be as specific

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List Of References

Babay, E. (2010, July 22). Law enforcement deaths rise nationwide. Washington

Examiner. Retrieved July 24, 2010, from

http://www.washingtonexaminer.com/local/crime/Law-enforcement-deaths-rise-nationwide-1002383-98957419.html

Bailey, W. (1982). Capital punishment and lethal assaults against police. Criminology,

19(4), 608-625.

Bailey, W., & Peterson, R. (1987). Police Killings and Capital Punishment: The

post-Furman period. Criminology, 25(1), 1-26.

Bailey, W., & Peterson, R. (1994). Murder, Capital Punishment, and Deterrence: A review

of the evidence and an examination of police killings. Journal ofSocial Issues,

50(2), 53-74.

Becker, G. (1968). Crime and Punishment: An Economic Approach. Journal ofPolitical

Economy, 4, 169-217.

Bedau, H., & Cassell, P. (2004). Debating the Death Penalty: Should America Have

Capital Punishment? The Experts on Both Sides Make Their Best Case. New

York: Oxford University Press, USA.

Bowers, W., & Pierce, G. (1975). The Illusion of Deterrence in Issac Ehrlich's Research

on Capital Punishment. Yale Law Journal, December, 5.

Census Bureau Home Page. (n.d.). Census Bureau Home Page. Retrieved June 25, 2010,

from http://www.census.gov/

Death Penalty Information Center, (n.d.). Death Penalty Information Center. Retrieved

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Dezhbakhsh, H., Rubin, P., & Shepherd, J. (2003). Does capital punishment have a deterrent effect? New evidence from postmoratorium panel data. American Law and Economics Review, 5, 344-376.

Ehrlich, I. (1975). The Deterrent Effect of Capital Punishment: A Question of Life and Death . The American Economic Review, 65(3), 397-417.

Fagan, J., Zimring, F., & Geller, A. (2006). Capital punishment and capital murder: market share and the deterrent effects of the death penalty. Texas Law Review, 84, 1-19.

Gerber, R. J., & Johnson, J. M. (2007). The Top Ten Death Penalty Myths: The Politics of

Crime Control. Westport, CT: Praeger Publishers.

Hübe, J. M. (2007). Negative Binomial Regression (1 ed.). New York: Cambridge

University Press.

Hjalmarsson, R. (2009). Does Capital Punishment have a "local" Deterrent effect on Homicides?. American Law and Economics Review, 77(310), 1.

Kovandzic, T., Vieraitis, L., & Boots, D. (2009). Does the Death Penalty Save Lives?.

Criminology & Public Policy, 5(4), 808-824.

Miller, J. M. (2005). Capital Punishment: US History. Encyclopedia ofCriminology (1

ed., pp. 144-148). New York: Routledge.

Mocan, N., & Gittings, K. (2003). Getting off death row: commuted sentences and the

deterrent effect of capital punishment. Journal ofLaw and Economics, 46,

453-478.

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from http://www.asc41 .com/policies/policyPositions.html

Radelet, M., & Lacock, T. (2009). Do executions lower homicide rates?: The views of

leading criminologists. The Journal ofCriminal Law & Criminology, 99(2),

489-504.

Shepherd, J. (2005). Deterrence versus Brutalization: Capital Punishment' Differing

Impact Among States. Michigan Law Review, 104(203), 14-20.

Zimmerman, P. (2009). Statistical Variability and the Deterrent Effect of the Death

Penalty. American Law and Economics Review, 11,1.

Supreme Court Cases

Atkins v. Virginia, 536 U.S. 304 (2002

Kennedy v. Louisiana, 554 U.S. (2008)

Penry v. Lynaugh, 492 U.S. 302 (1989)

Roper v. Simmons, 543 U.S. 551 (2005)

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Reference Notes

1 The actual moratorium on executions was from 1976 to 1977. However, this was not required by the Supreme Court. States limited their use of capital punishment due to the highlighted problems in the

Furman and Gregg cases.

Crimes against the state that do not necessarily have homicides associated with them are treason and espionage.

111 A Gallup Poll conducted in October, 2009 found that 65% of those polled were in favor of capital punishment for someone convicted of murder and that 31% were against.

lv Law Enforcement Deaths Rise Nationwide, The Washington Examiner, 8/24/2010

v Multicollinearity is a problem is regression modeling because it can compromise the reliability of predictors in a given model. When two predictor variables are highly correlated, so that they may be

predicting almost the same thing, including both in the analyses can compromise the validity of the results on those predictors. This affects Kovandzic et al. (2009) because of the number of included predictors increases the chances for multicollinearity.

V1 Parisi, Francesco and Smith, Vernon L., The Law and Economics of Irrational Behavior: An Introduction. George Mason Law & Economics Research Paper No. 04-16; F. Parisi & V. Smith, THE LAW &

ECONOMICS OF IRRATIONAL BEHAVIOR, Stanford University Press, 2005

™ Auto Correlation is a measure of the connected relationship between values during a time series set of

data. When many variables over time have the same value it can be said to be auto-correlated.

™' Heteroscedasticity is when random variables have different variances. This can violate an assumption

required for some statistical tests. The result can be biased standard errors which make variables appear significant when they are not (Hübe, 2007).

lx A study by Mocan & Gittings (2003) found that executions deter around five homicides and that

commutation of executions increase the homicide total by the same amount. A critique of this study by Richard Berk found that excluding Texas caused any deterrent effect to disappear. Mocan & Gittings are economists and Berk is a criminologist. The debate on this topic is split between the two disciplines.

x The Death penalty Information Center is the foremost abolitionist organization in the United States. They

work towards abolishing capital punishment in every state. However, they also compile lots of accurate

data and that was extremely helpful in the creation of a dataset for this paper.

"' The same analyses were preformed with Washington D.C. included. Washington D.C. was an anomaly

that caused other relationships to be obscured. For this reason the study was focused on just the 50 states.

™ www.City-Data.com has been recognized by CNN and gets their information from public records. It is

owned and operated by Advameg.

X1" Pseudo R2 values are indicators of goodness-of-fit. Values range between zero and one. The value indicated the degree of linear connection between the predictor variable(s) and law enforcement deaths.

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