Domestic violence sentencing: coefficient to a natural process that already reduces recidivism ...

33 Pages·2013·0.82 MB·English

NelsonCrimeScience2013,2:9
http://www.crimesciencejournal.com/content/2/1/9
RESEARCH Open Access
Domestic violence sentencing: coefficient to a
natural process that already reduces recidivism
simply as a function of aging
Eric L Nelson
Abstract
Background: Research ondomestic violence (DV) sentencing, post-conviction, has mostly focused onincarceration
and re-education programs, ignoring more than a dozen other components of the criminal sentence. Therefore,
little is known, overall, about the breadth of DV sentencing, antecedentsthatmayshapethecontentofthesentence,
andapossiblerelationshipbetweenthecriminalsentenceandatheorizednaturalprocessbelievedtosignificantlyreduce
DVrecidivismsimplyasafunctionofaging.
Results:Datafromthisempiricalstudy(N=1,810)revealsratesoffemaleDVrecidivismdecreasebyabout2.56%peryear,
betweenages22–61,andmalesbyabout3.13%peryearbetweenages28–60.ThesedatacloselymatchFederalBureauof
Investigationratesforrecidivism,byageandsex,forviolentcrimeingeneral.Thestudyalsoidentified16sentencing
componentsusedbyjudgesinDVcases.Logisticregressionondatafromarandomlyselectedsubset(n=366),usingthe
16sentencingcomponentsasdichotomousoutcomes,regressedagainst49antecedentvariables,illuminatedanumberof
factorsthathaveasignificantrelationshipwiththecontentofindividualDVsentences,includingmanyextrainvestigative
actionsthatpoliceofficerscanoperationalizewheninvestigatingDVcrime.
Conclusion:ConfirmationofanaturalprocessthatdiminishesratesofDVrecidivismasafunctionofaging
demonstratestheneedtofactorthiseffectintoanyequationdesignedtoassesstheeffectivenessofDVsentencing,or
re-education/treatmentprogramsuponratesofrecidivism.Italsoconfirmsthatthenaturalprocessisanimportantpart
ofthemilieuinwhichthecriminalsentenceisoperationalized.The results also demonstrate the need for police to
thoroughly investigate all DV crime, and to list multiple charges whenever the facts support doing so, because
doing so significantly raises rates of inclusion of several sentencing components.
Keyword: Domestic violence; Sentencing; Police; Age; Recidivism
Background componentsshareacommongoal:Reductionofthelikeli-
In western systems of justice criminal defendants (people hoodofcriminalre-offending.
accused of crimes by the State) face the potential of trial, Many defendants may choose to negotiate a reduced
wheretheyriskbeingfoundguiltyonallchargesandhav- sentence in exchange for a guilty plea to one or more of
ing the full set of sentencing options imposed upon them the crimes they are charged with having committed.
suchasincarceration,fines,probation,andanordertoat- Alschuler describes plea bargaining, what this type of
tend some form of treatment, and so forth. The criminal negotiation is called, as “the exchange of official conces-
sentence is an assembly of individual orders that may sions for a defendant’s act of self-conviction” (Alschuler
include punishment, rehabilitation, compensation, and 1979). In the United States 93-95% of all criminal cases
conduct requirements. Arguably, the various sentencing in local and state courts, and 97% of all federal prosecu-
tions are resolved through negotiation and not criminal
trial (Bureau of Justice Statistics 2008; Sourcebook of
Criminal Justice Statistics, 2002, 2004; United States
Correspondence:[email protected] Courts 2011a). Once the defendant pleads guilty or is
Criminology&CriminalJustice(IndividualProgram),UniversityofCalifornia,
c/oOfficeofGraduateStudies,1ShieldsAvenue,Davis,California95616,USA found guiltyat trial,a sentenceisimposed.
©2013Nelson;licenseeSpringer.ThisisanopenaccessarticledistributedunderthetermsoftheCreativeCommons
AttributionLicense(http://creativecommons.org/licenses/by/2.0),whichpermitsunrestricteduse,distribution,andreproduction
inanymedium,providedtheoriginalworkisproperlycited.
NelsonCrimeScience2013,2:9 Page2of33
http://www.crimesciencejournal.com/content/2/1/9
Componentsofthedomesticviolencecriminalsentence Table1Generalsentencingcomponentsidentifiedinthe
With regard to domestic violence (DV), little scholarly scholarlyliterature,sortedaccordingtopercentageofuse
attention has been paid to the breadth of sentencing op- Variables Source,sizeofstudy,typeofstudy
tions from which a judge can select, when crafting a ICJIA2000 Divineyetal.2008 CRB2003
unique order for a particular convicted person. Typically
(N=3,364) (N=136) (N=451,000)
when scholarly work examines DV sentencing they
GeneralCrime DVROViolation GeneralCrime
report on only two types of data: Length of jail terms
%Inclusion %Inclusion (%NotGiven)
e.g., (Chiricos & Waldo, 1975; Kingsnorth et al. 1998;
Probation 72
Steffensmeier et al. 1998; Ulmer & Johnson, 2006;
Supervisionfee 70
Wooldredge &Thistlethwaite2006)andefficacyoftreat-
ment programs e.g. (National Institute of Justice, 2003a, Courtcosts 52
2003b; Corvo et al. 2008; Dunford, 2000; Dutton, 2005; Restitutionand 52 39 *
Dutton & Corvo 2006; Babcock et al. 2004; Whitaker, fines
Baker, & Arias, 2007).Failing toexaminethe fullrange of Substanceabuse 50 11 *
treatment
sentencing options may have created an incomplete view
of the manner in which a person convicted of domestic Incarceration 49 *
violence crime is punished, rehabilitated, the compensa- Othertreatment 34
tion they must pay, and the conduct requirements they Drugmonitoring 28
mustfulfill.
Batterereducation 24 *
A detailed search of the literature yielded only three program
studies that describe the breadth of sentencing compo-
Communityservice 22
nents from which a judge can choose for any type of
Angermanagement 09 *
criminal case. Two studies summarize a range of senten- class
cing components for a wide variety of crime (Illinois
Mentalhealth 08 *
CriminalJusticeInformationAuthority2002;andCalifornia treatment
Research Bureau, 2003), and one study describes a set
Surrenderfirearms 05
of sentencing options for violation of a domestic vio-
Electronic 04
lence restraining order (DVRO), (Diviney et al. 2008). monitoring
No studies describing a full set of sentencing options
Couplescounseling 01
for domestic violence crime was located. A summary
Sexoffender *
of the sentencing options that were found is seen
treatment
below in Table 1.
Intensive *
As the contents of the table demonstrate, there are a supervision
wide variety of options from which a judge can select
Electronic *
when creating a sentencing order, much more than is monitoring
apparent from reading typical articles on domestic vio-
Dayreporting *
lence sentencing. However, even though judges are pre-
Housearrest *
sented with many choices about what to include, they
Halfwayhouse *
are not always free to craft a sentencing order they feel
placement
is most appropriate. That is because some components
Note:*Denotesusage.
ofthe domestic violence criminal sentence aremandated
by law. For example, in California the sentence is sup- addition, there is another aspect of DV sentencing that
posed to include a minimum of 36 months probation, a must be considered if one is to fairly evaluate the frame-
conduct order with stay away provisions, a minimum of work within which the DV sentence is operationalized,
$400 USD fine, mandatory attendance of a re-education post-criminalconviction.
program, and a requirement to perform community ser-
vice (California Penal Code §1203.097). However, judges Evaluatingthenaturalframeworkwithinwhichthe
in California often deviate from these mandates, by not domesticviolencesentenceisimposed
including all of the required components (California The age/crime relationship has been assumed to be true
State AttorneyGeneral,2005). by many criminologists (Hirschi and Gottfredson, 1983;
Because solittleisknownaboutthebreadthofdomes- Blonigen 2010b), though other factors may also explain
tic violencesentencing,thefirsttaskofthepresentstudy crime without reference to age (Hirschi and Gottfredson
is to help fill that hole in the literature by identifying a 1983). Farrington’s masterful disambiguation of key fac-
full set of sentencing options available to judges. In tors in the age/crime discussion (Farrington 1986) lead
NelsonCrimeScience2013,2:9 Page3of33
http://www.crimesciencejournal.com/content/2/1/9
him to argue for a concurrence of three effects: Aging, a general female violence, the point of inflection is about
period effect influenced by economic and other factors, age 21, and the slope approaches zero at about age 60;
and also a cohort effect based upon year of birth. How- thus, n=39, and we calculate Rate=(1/39)*102=2.5641
ever, Farrington’s dismissal of age as a cause of crime is per year. Thus, the natural process of violence potential
unconvincing when one considers the consistent pattern reduction for females is seen to be slightly more than
of distribution seen across a wide variety of crime, when two and half percent, per year. Male violence achieves
plotted for age. Consistent replication is a strong marker maxima at about age 18, decreasing to slightly above
of established relationships. Yet, at the same time Far- zero by age 60, at a yearly rate of reduction of about
rington’s point that age probably isn’t a cause of crime, 2.38%.
but rather a measure of a complicated set of underlying Theage/violencepotentialeffect(AVPE)demonstrated
theoretical construct is well taken and may be right. in Figure 1 uses aggregated data drawn from a number
However, for lack of a better descriptor we continue to of different types of violent crime; thus, its specific ap-
use“age”,with Farrington’spoint dulynoted. plicability to domestic violence crime is uncertain. It
An example of the aging effect can be seen in Figure 1. seems reasonable to suspect that the AVPE would also
Using Federal Bureau of Investigation data for a variety of describe domestic violence crime; however, to date this
violencecrimes(FederalBureauofInvestigation2003,p.6)c proposition has not been tested sufficiently. Pioneering
within-group rates of violence, by sex, were plotted for age. workby(Strausetal.1980:Chart11,p.141)didexamine
The general shape of this plot is consistent with those seen rates of domestic violence in four age groups: 30 and
in other publications, including (Hirschi and Gottfredson under, 31–50, 51–65, and 65 and over. The results
1983),(Farrington1986),and(Blonigen2010). showed a steady diminishment of violence potential
As the graph demonstrates, within-group rates of vio- across the four groups, as age increased. Though a trend
lence by females across a span of violent crimes achieves is seen in their data, the use of large age categories and
maxima around age 21, and thereafter decreases to thefailuretodistinguishbetweenmalesandfemalespre-
slightly above zero by age 60. Because the slope is rela- vents more nuanced analysis. In another study, three
tively linear, the rate of change is approximately the years of longitudinal data demonstrated a similar trend
same each year. Accordingly, we can calculate a rate of (O’Learyet al.1989).
changeusingthealgorithmseeninEquationone(1). Should the natural operation of the age/violence po-
tential effect be confirmed as also describing the natural
Rate¼ð1=nÞ(cid:2)102 ð1Þ reduction of DV recidivism according to age, it would
thereafter become necessary to re-conceptualize our un-
where n is the number of years between apogee and the derstanding of DV sentencing and DV recidivism in
point where the rate approaches zero. In the case of order to account for the natural process. Under these
Figure1Comparisonofwithingrouparrestfrequencies,bysexandagegroup,forviolentcriminalbehavior.Datasource:(Federal
BureauofInvestigation2003:6).
NelsonCrimeScience2013,2:9 Page4of33
http://www.crimesciencejournal.com/content/2/1/9
theorized circumstances imposition of a DV criminal either rejected an investigation, refusing to file criminal
sentence, post-conviction, could therefore be seen as the charges, or until filed cases were concluded. In the year
introduction of an artificial coefficient to a natural equa- 2008 the police agency produced N=1,810 domestic
tion. Inotherwords: violence investigation reports, each assigned a unique
number. Those numbers were used to match prosecutor
y ¼y (cid:2)ð1−xaÞ ð2Þ
x 0 files with police investigation reports. Because the re-
cords of both agencies are computerized, problems lo-
would become
cating files were not encountered. Data was collected
y ¼y (cid:2)ð1−xaÞ(cid:2)b ð3Þ overa2.5year period.
x 0 x
A total of 16 types of data were collected for all cases,
where y is the within-group rate of violence for year x; including demographics of the suspect(s) and victim(s),
x
y is the within-group rate of violence at the point of in- and different crime codes. An additional 242 types of
0
flection; x is a count of whole years past the point of in- data were collected on n=366 randomly selected inves-
flection; a is the within-group rate of linear change tigations. These data included important dates, so that
between maxima and minima as calculated using Eq. 1; time periods could be measured; types of witnesses, and
and b is the coefficient of change induced by the sum of counts of witnesses; charges recommended by police,
the effects of individual sentencing components.d Inves- charges filed by prosecutors, and charges defendants
tigating for the possible operation of a DV-AVPE is the were convicted of; reasons police investigations were
secondpurposeofthepresent study. rejected by prosecutors, and so forth. Theresults are be-
ingreportedacrossseveraljournal articles.
Summary Raw data was entered into a password protected
Little is known about the breadth of domestic violence spreadsheet, comprised of 88,572 data cells. The spread-
sentencing components, or the natural process that sheet was subdivided into a number of tables and was
may represent an important part of the milieu in used for a variety of calculations including mean, stand-
which the DV criminal sentence is operationalized. ard deviation, t and z test significance comparisons for
The domestic violence criminal sentence may actually means and ratios, creation of pivot tables, and so forth.
represent an attempt to apply pressure to the natural The raw data table was imported into Stata/IC 10.0 for
slope in order to significantly increase its negativity. statistical assessment. Stata was used to conduct individ-
Using empirical data the present study aims to correct ual and model OLS and logistic regression, and to per-
a vacuum in the literature regarding the breadth of po- form survivalandhazardanalysis.
tential content of the DV criminal sentence, many of
their significant antecedents, and to examine for the Explanationofstyleusedtopresentstatisticalresults
operation of a domestic violence age/violence poten- In traditional subscription journals the manner in which
tial effect. statistical results are presented may not be understand-
able to non-scholars. For example, Beta values resulting
Hypothesis from logistic regression are probably not easily under-
The null hypothesis asserts that within and between stood. This is true because Beta values must be further
group rates of domestic violence, according to sex and processed into odds ratios, or percentage change values
age, will not be similar to those measured in the general inordertomake usefulsense ofthem.
population for all types of violence combined, as re- One must question to whom open source articles such
ported by the FBI and seen in Figure 1. The alternative as those published in Crime Science are addressed,
explanation asserts the rates will, upon inspection,e be because this should have a bearing upon the manner in
seentobesimilar. which statistical resultsare presented.Ifresearchscholars
are writing to fellows, as is done in subscription-based
Method journals,thereisnoreasontochangetraditionalmethods
Sourceofdata of data presentation. However, open source journals
The author was granted access to the computer system scholarsarewritingtoalargeraudiencethatalsoincludes
of a mid-sized police agency in California, and also the junior high and high school students and teachers, work-
prosecutor’sofficeforthe county.Thepurposeoftheac- ing professionals who may not have access to university
cess was to allow direct reading of police reports and library journal subscriptions, journalists and other non-
prosecutorfiles sothatindividual police investigationsof academic professional researchers, and indeed to all the
domestic violence could be followed from “cradle to interestedpeopleoftheworldwhotakethetimetodown-
grave”, meaning from the moment a police officer was load a particular open source article and read it, in
dispatched to investigate, until the time that prosecutors additiontoanacademicaudience.
NelsonCrimeScience2013,2:9 Page5of33
http://www.crimesciencejournal.com/content/2/1/9
Therefore, it is held that scholars who publish in open may use the β value, and world readers may use the per-
source journals should reconsider how their statistical centage change value.
results are presented. The traditional manner in which
results of logistic regression are presented provides a Dependentvariables
case-in-point example. The non-academic public might Directexaminationofprosecutorfilesdemonstratedthat
make use of these outcome values if only they could 16 sentencing components are available to judges for
understandwhat aBeta scoremeans. possibleinclusioninthesentencingorder.Eachoutcome
It is believed that research scholars publishing in open wasseparatelyrecordedasadichotomousvariablewhere
source journals should assume an intelligent, capable, 1=includedand0=notincluded.
and curious world reader who can make practical use of
their empirical findings, so long as results are made Independentvariables
understandable to all. The first step towards operation- Forty nine explanatory variables, a subset of the larger
alizing that goal has already been taken: Open source data pool, were evaluated for their potential relationship
journals such as Crime Science have been established. to the 16 sentencing outcomes. Of those, eight measure
However, that is not felt to be enough. Open source police actions; one is a word count of the first respond-
scholars must take upon themselves the burden of pre- ing police officer’s written report; two measure aspects
senting understandable data that is accessible to a curi- of charges that are filed by the prosecutor;h four
ous world, whenever possible. Following that mandate characterize statements and actions of the suspect when
then, and continuing to use Beta values as an example, interacting with police; eighteen measure suspect and
we can convert beta values into a form that is more ac- victim demographics; nine measure characteristics of
cessible to world readers. Equation 4 displays the algo- witnesses and their statements to police; and seven
rithm fordoingso.f measure the types of charges that a defendant is con-
(cid:1) (cid:3) victed of. Among these, seven are continuous variables,
PctChange¼ expβ−1 (cid:2)102 ð4Þ and forty two are dichotomous. A list of these variables
isseeninTable2.
An example should make this point clear. Using other
data from a prior paper (Nelson, 2013) we can logistic- Analysisofthedata
ally regress the continuous variable “pdcsum” on the di- Because all of the outcomes are dichotomous variables,
chotomous outcome “DAFile” g. The antecedent variable logistic regression is the appropriate choice for statistical
is a count of how many charges are recommended in analysis. The outcomes are seen in the results tables.
the written report of a first responding police officer Each explanatory variable was regressed individually on
(FRPO) who investigated a particular domestic violence all outcomes, thus producing a results spreadsheet com-
crime, (e.g., one charge is listed, or two, or three, and so prised of 784 individual cells. Variables that were signifi-
forth).Theoutcomeiscodedone(1)iftheprosecutorfiled cant for a particular outcome were regressed again, en
a criminal case, and zero (0) if not. Logistic regression masse, for that outcome, and then a third time in a best-
produces the following result: β=1.292882 (n=366, fit model. Results for each stage of regression are pre-
χ2=40.92,p<.0000,pseudoR2=.0918;z=5.10,p<.0000). sented inindividual tables.
One must ask: Could a curious and intelligent non-
academic really make sense of the outcome β=1.292882? Criteriaforestablishingantecedentvariablesignificance
WhatdoestheBetavaluetellapoliceofficerinSingapore, Paying less attention to explanatory variables that show
aprosecutorinMalaysia,ahighschoolstudentinSweden, diminished power when assessed in a model, rather than
or a judge in Sudan? To make this outcome useful to a alone, might be a mistaken practice. Scholars cannot
world readership it must be converted to an understand- rule out the possibility that the influence of a particular
ablevalue.Accordingly,usingthefourthequation,wecal- variable may continue to be expressed, albeit through
culate the percentage change value to be 264%. That is a another outcome with which the variable is collinear;
number the world can work with, so long as it is inter- after all, something has to explain how the explanatory
preted correctly. In this case that explanation would be power of some independent variables increase when
“ForeachadditionalchargelistedintheFRPOswrittenre- regressedinparallelwith others,inamodel.
port, there is a 264% greater chance that the prosecutor Probably no experiment can ever be designed to test
will file a criminal case against the suspect identified in whetherthisistrue,forcertain,ornot;however,borrowing
thepolicereport.” from physics the assumption of a form of conservation
Acting to expand the accessibility of the empirical is not believed to be unreasonable; and, ultimately,
findings of the present study, Beta and percentage values criminologists and social science scholars must guess
are presented side-by-side in the results tables. Scholars about such things anyway. Because guesses about how
NelsonCrimeScience2013,2:9 Page6of33
http://www.crimesciencejournal.com/content/2/1/9
Table2Antecedentvariables:abbreviations& Table2Antecedentvariables:abbreviations&
explanations explanations(Continued)
Abbreviation Explanation Onbalancethewitnessstatementsare
EPOObtained AnEmergencyProtectiveOrder(EPO)was favorabletowardsthesuspect.
obtained.
Mult.Chgs.-Conv. Thedefendantwasconvictedofoneor
PhotosReq.orObtained Photographswererequestedorobtained. morecharges(alltypescombined).
Susp.WasArrested Thesuspectwaslocatedandarrestedby Conv.≥1Misd.DV Thedefendantwasconvictedofoneor
police. moremisdemeanorDVcrimes.
≥1Juv.Victims Oneormorejuvenileslistedasavictim Conv.≥1Fel.DV Thedefendantwasconvictedofoneor
inthepolicereport. morefelonyDVcrimes.
PDInv.Time<240hrs. Thepolicereportwasdeliveredtothe Conv.≥1ViolationDVRO Thedefendantwasconvictedofoneor
prosecutor’sofficein240hoursorless. moreviolationsofaDVrestrainingorder.
ChargeCount-Police Count:Thenumberofcharges Conv.≥1Non-DVCrime Thedefendantwasconvictedofoneor
recommendedbypolice. morenon-DVcharges.
ChargeCount-Filed Count:Thenumberofchargesfiledby Conv.≥1ChildEndanger. Thedefendantwasconvictedofoneor
prosecutors. morechildendangermentcharges.
ChargeCount-Conv. Count:Thenumberofchargesthe WordCount-PoliceReport Thenumberofwordsinthepolice
defendantwasconvictedof. report.
ReasonsCount-CaseRej. Thenumberofreasonsgivenby Susp.Sex:Male Thesuspect’sbiologicalsexismale.
prosecutorsforrejectingan Susp.Sex:Female Thesuspect’sbiologicalsexisfemale.
investigation.
Susp.Age Thesuspect’sageonthedaythepolice
5thAmend.Invoked Thesuspect,whenquestionedby
reportwaswritten.
police,invokedthe5thAmendment.
Susp.Race:White ThesuspectisWhite.
Susp.AdmitsGuilt Thesuspect,whenquestionedby
police,admittedcommittingone Susp.Race:Black ThesuspectisBlack.
ormorecrimes.
Susp.Race:Hispanic ThesuspectisHispanic.
Susp.ClaimsMutual Thesuspect,whenquestionedby
Susp.Race:Asian ThesuspectisAsian.
police,claimedtheDVwasmutual
combat. Susp.Race:NotWhite ThesuspectisnotWhite(Black+
Hispanic+Asian).
Susp.DeniesGuilt Thesuspect,whenquestionedby
police,deniedcommittingoneor Susp.Race:NotBlack ThesuspectisnotBlack(White+
morecrimes. Hispanic+Asian)
WitnessSum Thenumberofwitnesseslistedin Vict.Sex:Male Thevictim’sbiologicalsexismale.
policereport(notnecessarily
Vict.Sex:Female Thevictim’sbiologicalsexisfemale.
interviewed).
Vict.Age Thevictim’sageonthedaythepolice
WitnessesInterviewed Thenumberofwitnessesinterviewed
reportwaswritten.
bypolice.
Vict.Race:White ThevictimisWhite.
NoWitnesses Nowitnesseswereinterviewedby
police. Vict.Race:Black ThevictimisBlack.
Juv.Wit.NotRelated Oneormorewitnessesarejuveniles Vict.Race:Hispanic ThevictimisHispanic.
notrelatedtothesuspect.
Vict.Race:Asian ThevictimisAsian.
Juv.WitnessRelated Oneormorewitnessesarejuveniles
relatedtothesuspect. Vict.Race:NotWhite ThevictimisnotWhite(Black+
Hispanic+Asian).
Juv.WitnessRel.Unk. Oneormorewitnessesarejuveniles
whoserelationshiptothesuspectis Vict.Race:NotBlack ThevictimisnotBlack(White+
notclarified. Hispanic+Asian).
AdultWit.NotRelated Oneormoreadultwitnessesarenot
relatedtothesuspect. to interpret criminological findings can affect criminal
justice procedure, and public policy, prudence would
AdultWitnessRelated Oneormoreadultwitnessesare
relatedtothesuspect. seem to suggest that one should be cautious about
AdultWit.Rel.Unk. Oneormorewitnessesareadults rejecting any variable that demonstrates significance
whoserelationshiptothesuspect upon individual regression. That caution drives this
isnotclarified.
paper; and thus, variables that perform significantly
Wit.NotClassified Thereareoneormoreothertypesof well, individually, are viewed as important indicia of
witnessnotclassifiedinanyother
how the criminal justice response to domestic violence
category.
crime is shaped with regard to post-conviction senten-
WitnessesFavorable
cing, even as the measure of the pressure of their
NelsonCrimeScience2013,2:9 Page7of33
http://www.crimesciencejournal.com/content/2/1/9
influence is elusive, all this being done while remaining number of variables that show significance in modeling
aware of the possible operation of collinearity. By pro- may actually be demonstrating a parasitic collinear effect,
viding probability levels for all outcomes, in the results, bydrawingstrengthandsignificancefromdonor variables
readers can evaluate the results within their own range of that were excluded because they show diminished power
acceptance. It is for that reason that the full data tables, and significance when regressed in parallel. Thus, caution
andnotmerelysummariesareprovidedintheappendix. is indicated when interpreting both individual or model
results.
Justificationfortheassumptionofcause Another potential weakness is the fact that not all do-
Acausalrelationshipisassumedbetweenpolice-controlled mestic violence comes to the attention of police; so, it is
variablesandoutcomes,forseveralreasons.First,withone unknown how well data acquired from police records
exception,alloftheexplanatoryvariableshaveafixedvalue actually describes rates of domestic violence in general.
beforeprosecutorsbecomeinvolvedwiththecase.iSecond, In this study, that concern only applies to the measure
there no feedback system by which prosecutors can influ- of the DV age-violence potential effect (DV-AVPE), be-
ence decisions taken by police, when investigating domes- cause the remainder of the data is not generalized to the
tic violence crime, in situ, nor can they change victim, full population. It is possible the AVPE rate to be mea-
suspect, witness, and child-victim demographics. Prosecu- sured for DV, by the present study, may differ from the
torsdonotrideinpolicecarsinordertoadvisepoliceoffi- unmeasuredrate inthegeneralpopulation.
cers how to do their job. Third, the uni-directional, linear
natureofthe criminal justice system issuch that thework Results
of the first responding police officer is entirely completed, In order to address the null hypothesis, the full data set
and memorialized in a written report before the work of (N=1,810) wasused. Figure 2 contains a graph that pre-
prosecutorsbegin.Prosecutorsworkforadifferentgovern- sents within group frequencies, by sex and age group,
ment agency, in a different location. If they have contact for individuals who were identified as a domestic vio-
with police, it is after reading an officer’s report. Thus, lencesuspectinawritten policereport.
thereareno feedback loops of influence from prosecution As the graph demonstrates, females and males show a
to officer, for specific investigations. Finally, a causal as- similarly diminishing longitudinal pattern, though for
sumption is felt to be parsimonious: It makes sense tobe- males the peak of violence is delayed by about 6–7 years
lievethatthequalityofthepoliceinvestigationsignificantly compared to females. The maxima for females is, essen-
influences prosecutorial outcomes. It should be noted that tially,identicaltotheoneseeninFigure1,itbeingabout
someofthecharacteristicsofacasearenotunderthecon- age 22, with female violence decaying to zero at about
trolofpolice,suchasdemographics.Variablesthatmaybe age 61. That rate of decline is 2.56% per year of age,
underpolicecontrolinclude:Thedecisionwhethertoseek making it identical to the one calculated from Figure 1.
an emergency protective order, whether to take photo- However, for domestically violent males, a bimodal max-
graphs,whethertomakeanefforttolocateadditionalwit- imaisseen,anditpresentationisdelayedabout10years,
nesses, whether to make an arrest, whether to list more to about age 28, when compared to the maxima for
thanonecharge,andwhethertocompletetheinvestigation males seen in Figure 1. The end point for males is about
andwriteareportthesameday,ornot. the same in both figures, at age 60. The rate of change
for males in Figure 2 is about 3.13% per year of age. For
Limitations both males and females, once the onset of the natural
These data describe a particular criminal justice system reduction in recidivism has begun, an approximately lin-
inaspecificcityinCalifornia;assuch,theymaynotfully ear pattern is seen; however, at points within these data
describe the sentencing processes in other criminal just- onesees someinterestingpointsoflocalizedinflection.
ice systems in other places. Also, there is potential for Because these data demonstrate a number of close
authorial bias, as the author is a former police officer similarities to those seen in Figure 1, including a very
who specialized in domestic violence investigation at the close parallel to the aggregated violence pattern, they
first responder level. However, because the data is quan- are interpreted as fairly strong evidence that the age-
titative in nature, it is felt that the potential to insert bias violence potential effect does, in fact, describe changes
wasnaturally kepttoa minimum by the non-interpretive, in the rates of domestic violence recidivism as well, ac-
numericalnatureofmostofthedata;suchas,eitherasec- cording to age; therefore, the null hypothesis is rejected
ondary charge of vandalism was included, or not, and so andthealternativeexplanationisaccepted.
on.Thereisariskofbothtypesofinterpretiveerrorwhen
examining the results of individual variable regression ta- Sentencingcomponentfrequencies
bles, due to the potential operation of collinearity. How- Of the n=366 randomly selected investigations, 70% re-
ever, that argument can be turned around. The reduced sulted in prosecution, and 44% resulted in criminal
NelsonCrimeScience2013,2:9 Page8of33
http://www.crimesciencejournal.com/content/2/1/9
Figure2Comparisonofwithinsexaccusationfrequencies,fordomesticviolencecrime,byagegroup.
conviction. Though 16 sentencing components are avail- black bars; whereas, inverse relationships extend to the
able to judges, in actuality only 15 are used. The senten- left and are indicated by red bars. For example, we see
cing orders of defendants convicted of at least one that the choice of the suspect to invoke her/his 5th
domestic violence misdemeanor crime contain an aver- Amendment right significantly increases the likelihood
age of 5.09 components (sd=3.28). Sentencing orders about 60% of the sentencing options will be included in
following a felony DV conviction contain an average of the order. Checking Tables 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,
5.22 components (sd=3.19). The full set of domestic 14, 15, 16, 17, 18 we see this to be true, noting nine of
violence sentencing options are described in Table 3, or- them show a positive effect correlated to invoking the
dered bytheirfrequencyofuse. right to be silent (9/16=56). Similarly we see that the
Probation is the most frequently used sentencing op- age of the victim is inversely correlated to about 40% of
tion, followed by confinement in jail. Nine sentencing
options are used in at least one third of the cases, three Table3Domesticviolencesentencingvariablesandtheir
percentageofuse
in 15-30% of the cases, and the other four are not used
very often. A wide variety of antecedent variables were Sentencingvariables Percentuse
found to have significant relationships with the various Probation 86
sentencing options. Those relationships are summarized Confinementincountyjail 82
in Figure 3, and their full details provided in Tables 4, 5,
Payafine 54
6,7,8,9,10,11,12,13,14,15,16,17,18.
Attenda26or52weekdomesticviolence 54
re-educationcourse.
Relationshipsbetweenexplanatoryvariablesand
Stayawayfromthevictim 47
sentencingoutcomes
Submittowarrantlesssearchesbypoliceor 41
A wide variety of explanatory variables displayed signifi-
probationofficers
cant interactions with multiple sentencing outcomes,
Surrenderallfirearms,donotpossessfirearms 39
from a high of n=17 antecedents positively influencing
Obeyalllaws 39
the probability of being sentenced to jail, to a low of n=2
antecedents for being ordered to submit to random drug Donotannoy,threaten,harass,orstrikethevictim 35
testing. The average number of significant individual inter- Payrestitutiontothevictim 29
actionsis8.73(sd=4.68).Asummaryoftheserelationships Donotcommitthesameorsimilaroffenses 21
canbeseeninFigure3below.Thefullresultscanbeseen
Donotusedrugsoralcohol 15
inTables4,5,6,7,8,9,10,11,12,13,14,15,16,17,18.
Harveywaiver 5
Figure 3 is avisual rendition of the direction of the re-
Confinementinstateprison 5
lationship between particular antecedents and outcomes
they significantly influence, as well as the percentage of Submittodrugtestingwithoutawarrant 2
outcomes that are influenced in each direction. Positive Performcommunityservice 0
relationships extend to the right and are denoted by Note:n=160convictions.
NelsonCrimeScience2013,2:9 Page9of33
http://www.crimesciencejournal.com/content/2/1/9
Figure3Comparisonof24independentvariablesonfrequency&typeofrelationshiptosentencingoutcomesasagroup.
the sentencing options (6/16=38). In all but one case and minima, and the percentage values for rates of
individual influence is unidirectional. Overall then, we change. Thus, it seems reasonable to accept the propos-
can see from inspection of Figure 3 that nearly all ante- ition that age is a strong predictor of domestic violence
cedents are unambiguous about the direct and scope of recidivism. Some interesting, previously unknown char-
theirinfluenceoverpotentialsentencingcomponents. acteristics arealso seeninthe current data.
First is the delay of the male point of inflection for the
Discussion crime of domestic violence. The data used to construct
The present study responds to two fundamental ques- Figure 1 is an aggregate of five types of violence crime:
tions: “Does the aging process negatively influence rates Murder, manslaughter, forcible rape, robbery, and aggra-
of domestic violence recidivism?”, and, “What is the vatedassaultj.InFigure1inflectionoccursaroundage18;
identity and frequency of occurrence of individual DV whereasdomestic violencedata showsmaleinflectionde-
sentencing components, and their antecedents of signifi- layed about 10 years (age 28), as shown in Figure 2. This
cance?” As the results of this study have demonstrated, is an interesting finding because between ages 18 and 28
the answers to these questions should be considered to- male violence is decreasing across many types of violent
gether because the two processes, aging and criminal crime even as it is still increasing across one other,
sentences, act upon the same outcome. So long as one domestic.
assumeseachitem ofaDVcriminal sentenceisintended The second artifact is seen when individual sex pat-
to reduce recidivism, then the aging process should be terns are compared. In Figure 2 females show two dis-
seen as an important part of the milieu within which the tinct periods of increasing violence–in the early and mid
DVcriminal sentence isoperationalized. 20′s, and also the late 30′s and early 40′s. There is a
clear 8–10 year gap between them. Interestingly the
Makingsenseofthenaturalprocess male pattern seems to follow the female pattern, delayed
Comparing the distribution pattern seen in Figure 2 to by a few years, seen at four distinct locations on the
that in Figure 1 is seen to robustly answer the first em- graph. Twice as the female rate of violence increases the
pirical question in the affirmative. On six characteristics male rate increases thereafter; and, twice the female rate
the distributions are seen to be quite similar: The direc- decreaseswithmalesfollowingsuit.
tion of the slopes, the shape of the slopes as approxi- It is possible these patterns represent new findings re-
mately linear, the location on the Yscale where maxima garding domestic violence recidivism. It is also possible
is achieved, the location on the X scale where frequency these artifacts will flatten when larger data sets from
approaches zero, the period of decline between maxima multiple sources are analyzed. Since age records for DV
hN
ttp://welson
ww Crim
.c e
rim Sc
e ie
s n
cie ce
n2
Table4Byantecedent,percentagechangeandoddsofbeingsentencedtoaterminthecountyjail cejo013
u,
Regressedalone Regressedinfull Bestfitregression rna2:9
Variables χ2 p PseudoR2 β %Chg z p χ2 p PseudoR2 β %Chg z p χ2 p PseudoR2 β %Chg z p l.c
o
m
Model 209 .000 .442 204 .000 .427 /c
o
Susp.WasArrested 6.63 .010 .014 .566 76 2.57 .010 -.385 −32 .93 .352 nte
n
Sum,Witnesses 3.55 .060 .007 .390 48 1.89 .059 -.862 −58 .94 .348 t/2
/1
PDInv.Time<240hrs. 15.7 .000 .033 .873 139 3.92 .000 .806 124 2.19 .028 .736 109 2.32 .020 /9
WordCount-PoliceReport 3.58 .059 .008 .0005 .048 1.89 .059 .0003 .03 .68 .499
ChargeCount-Police 21.5 .000 .045 .620 86 4.41 .000 .301 35 1.44 .150
ChargeCount-Filed 48.0 .000 .101 .637 89 6.37 .000 -.191 −17 .99 .323
ChargeCount-Conv. 130.0 .000 .272 2.27 965 9.24 .000 -.278 −24 .43 .671
Conv.≥1Misd.DV 145 .000 .303 3.11 2100 10.5 .000 4.34 667 5.65 .000 3.90 4800 10.7 .000
Conv.≥1Fel.DV 5.51 .019 .012 .842 132 2.35 .019 2.25 853 2.89 .004 2.07 694 4.64 .000
Conv.≥1Non-DVCrime 5.68 .017 .012 .775 117 2.39 .017 2.07 691 2.51 .012 1.60 396 3.66 .000
5thAmend.Invoked 6.38 .012 .013 1.10 200 2.49 .013 .509 66 .65 .515
Susp.AdmitsGuilt 3.21 .073 .007 .573 77 1.80 .071 .180 20 .25 .803
Susp.DeniesGuilt 6.74 .009 .014 -.611 −46 2.60 .009 -.217 −20 .38 .705
Susp.Sex:Male 8.76 .003 .018 1.05 186 2.73 .006 .748 111 1.25 ..210
Susp.Race:White 3.74 .053 .008 -.586 −44 1.87 .061 .069 7.16 .14 .890
Susp.Age 9.14 .003 .019 -.033 −3.26 2.92 .004 -.031 −3.03 1.08 .279 -.036 −3.51 2.17 .030
Vict.Age 6.44 .011 .014 -.029 −2.87 2.48 .013 -.00. -.26 .09 .928
NoWitnesses 4.02 .015 .008 -.468 −37 2.01 .044 −1.02 −63.9 .98 .327
≥1Juv.Victims 4.55 .033 .010 .891 144 2.13 .033 .334 39.7 .50 .615
P
a
g
e
1
0
o
f
3
3