The Challenge of Special Needs Education in School-Based Delinquency Research

This article was downloaded by: [McMaster University]On: 19 December 2014, At: 19:32Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Scandinavian Studies inCriminology and Crime PreventionPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/scri20

The Challenge of Special NeedsEducation in School-BasedDelinquency ResearchJanne Kivivuori a & Venla Salmi aa National Research Institute of Legal Policy , Helsinki, FinlandPublished online: 15 May 2009.

To cite this article: Janne Kivivuori & Venla Salmi (2009) The Challenge of Special NeedsEducation in School-Based Delinquency Research, Journal of Scandinavian Studies in Criminologyand Crime Prevention, 10:1, 2-17, DOI: 10.1080/14043850902814530

To link to this article: http://dx.doi.org/10.1080/14043850902814530

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoeveras to the accuracy, completeness, or suitability for any purpose of the Content. Anyopinions and views expressed in this publication are the opinions and views of theauthors, and are not the views of or endorsed by Taylor & Francis. The accuracy of theContent should not be relied upon and should be independently verified with primarysources of information. Taylor and Francis shall not be liable for any losses, actions,claims, proceedings, demands, costs, expenses, damages, and other liabilitieswhatsoever or howsoever caused arising directly or indirectly in connection with, inrelation to or arising out of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms& Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

http://www.tandfonline.com/loi/scri20

http://www.tandfonline.com/action/showCitFormats?doi=10.1080/14043850902814530

http://dx.doi.org/10.1080/14043850902814530

http://www.tandfonline.com/page/terms-and-conditions

http://www.tandfonline.com/page/terms-and-conditions

The Challenge of Special NeedsEducation in School-BasedDelinquency ResearchJANNE KIVIVUORI AND VENLA SALMI

National Research Institute of Legal Policy, Helsinki, Finland

Abstract

There are excellent reviews of methodo-

logical research in the self-report crime and

delinquency studies. Most notably the

reviews by Junger-Tas and Marshall

(1999), Tourangeau and McNeeley

(2003), and Thornberry and Krohn (2000,

2003) provide exhaustive treatment of

relevant issues and problems. Recently,

this body of methodological research has

been discussed in the Scandinavian social

and cultural context (Kivivuori 2007).

Taken together, the message is that self-

report delinquency research is a fairly

reliable and valid means of estimating

criminal behaviour especially in child and

adolescent populations.

Much of self-report delinquency re-

search is conducted in schools. The school

is not, however, a static institution which

remains the same forever. The school under-

goes change.One of the recent developments

is the increasing availability and provision of

special needs education (SNE). In this article,

we first briefly review the classical debate on

the limits of what has been called the ‘school

criminology’. We then describe the recent

rise in SNE provision with special emphasis

on Finland. Third, we use a large school-

based but SNE-inclusive data set to examine

how the exclusion of SNE students in the

sample would have influenced the preva-

lence and incidenceestimatesofdelinquency.

In recent years, there has been a

marked increase in the number

of students who are placed in

special needs education (SNE)

groups within the school system.

Consistent with this international

trend, the percentage of Finnish

students in SNE groups rose

from 2.9% to 7.7% from 1995

to 2006. The inclusion of

SNE groups in school-based

delinquency research has become

a salient issue for methodological

adequacy. In the Finnish Self-

Report Delinquency Study,

which is an indicator system

with repeated measurements,

SNE groups have been included.

In this methodological article, we

use the Finnish Self-Report

Delinquency Study (FSRD) 2001

sweep to analyse the relevance of

that inclusion. First, we analyse

the contribution of SNE students

to the prevalence and incidence

estimates of delinquency. Second,

we examine how the inclusion

or exclusion of SNE students

influences observations of

the correlates of delinquent

behaviour. The results indicate

that the population estimates

of the overall delinquency

prevalence are not seriously

compromised by SNE exclusion.

In contrast, incidence estimation

is highly susceptible to the

inclusion or exclusion of SNE

groups. Students placed in SNE

have higher prevalence of known

risk factors of delinquency, such

as disadvantaged social and

familial backgrounds. Their

inclusion in research appears

to have relevance for the

analysis of risk factors of

delinquency.

KEY WORDS: Correlates of delin-

quency, Prevalence and incidence

of delinquency, School-based

delinquency research, Self-report

delinquency survey, Special needs

education students

2 Journal of Scandinavian Studies in Criminology and Crime PreventionISSN 1404-3858 Vol. 10, pp 2–17, 2009

DOI: 10.1080/14043850902814530 qTaylor & Francis

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

Fourth, we tentatively assess such effects as

SNE exclusion would have on substantive

research on the correlates of delinquency.

This is important, because SNE placement is

not random with respect to delinquent

behaviour. We conclude the article by

discussing the problems and challenges

involved when researchers have to

keep up with the changes in the institutional

infrastructure that they use for research.

Problems of ‘school criminology’

The invention of the self-report delinquency

survey by pioneers such as Austin Porterfield

(1946) was one of the most important

break-throughs in twentieth-century crimi-

nology. Systematic analysis of the dark

number of crime became possible, and

criminology was freed from the narrow

boundaries of official statistics and incar-

cerated or clinical samples. In a global and

historical perspective, the Scandinavian

countries were in the forefront of deploying

the self-report delinquency method in

ground-breaking field surveys (Kivivuori

2007). Today, the deployment of self-report

delinquency survey in educational and other

contexts is one of the corner-stones of

criminological research.

Since its inception, the self-report

method has been improved by being

subjected to methodological research and

critique. An important aspect of such

critique has been the study of the insti-

tutional context of research. Twenty years

ago, Cernkovich et al. (1985) argued that

serious chronic offenders are under-rep-

resented in, or totally absent from, many

self-report delinquency studies. They noted

that self-report studies are typically based

on community or school samples. Such

samples do not include serious offenders,

who are less likely to be found in schools.

Cernkovich et al. did not describe school-

based studies as somehow totally mis-

guided, because they were useful in

describing the delinquency of the average

youth and trends in such delinquency.

However, their seminal article highlighted

an important limitation of school-based

delinquency research.

More recently Hagan and McCarthy

criticized the kind of self-report research

which they labelled ‘school criminology’.

While acknowledging the merits of school

and community-based self-report studies,

they correctly pointed out that the self-

report method has been too often restricted

to junior and senior high-school students.

In their view, the appeal and ease of self-

report data collection in schools replaced

the streets as sites of data collection,

directed attention from class structure to

socio-economic stratification, and replaced

delinquency for crime as the main depen-

dent variable in criminology (Hagan and

McCarthy 1999:5).While Cernkovich et al.

underscored the importance of youths who

lived in institutions such as prisons, Hagan

and McCarthy noted that youths living in

the street were absent from the standard

school criminology. Both types of missing

students exemplify the problem of selective

non-response in self-report delinquency

research. The students for whom self-

reports are not obtained may be more

likely than average to engage in delin-

quency (Junger-Tas and Marshall

1999:309).

Recent European studies have indicated

that, in some respects at least, the school

may be a relatively good place to conduct

delinquency research. Naplava et al.

(2002) noted that ethnic minorities and

socially deprived groups could be better

reached by contacting them at school

KIVIVUORI & SALMI: SPECIAL NEEDS EDUCATION IN DELINQUENCY RESEARCH

Journal of Scandinavian Studies in Criminology and Crime Prevention 3

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

instead of at home. This finding was later

corroborated by Kollisch and Oberwittler

(2004). However, the external validity of

school-based research continues to face

criticism. A substantial body of evidence

suggests that being detached from main-

stream school is associated with increased

likelihood of delinquency (Stephenson

2007:91).

Judging from the above-cited research, it

seems clear that the adequacy of school as a

delinquency research site varies from one

country to another. The number of

incarcerated adolescents and street youths

varies. Some school systems are more

inclusive than others. The reasons why

some adolescents are outside the main

school system vary as well. The increasing

provision of special needs education is a

case in point. In a country like Finland,

placement in a special needs education

group is not seen as a very repressive

intervention. In most cases, the SNE

group is located in the same building

where regular classes go to school.

This suggests that the problem of overly

selective ‘school criminology’ should be

lesser in a country like Finland, if SNE

classes are included in self-report (SR)

surveys. Indeed, it would be possible to

compare critically what different societies

do with their unruly children: some may

incarcerate them, some may ignore them as

street youths, and some may take intensive

educational measures while keeping the

youths within the regular educational

framework. Fundamental institutional

arrangements such as these influence the

infrastructure and external validity con-

ditions of school-based delinquency

research.

Especially internationally comparative

self-report delinquency research is at risk

of ignoring important differences in the

institutional archipelago of each partici-

pating country. For example, the percen-

tage of SNE students differs from country

to country. Differences may reflect both

the factual differential incidence and

prevalence rates of disabilities, difficulties,

and disadvantages, or differential re-

sources allocated to special needs edu-

cation. Moreover, there is wide variation

between countries in the conceptual

frameworks to classify SNE students.

This makes it difficult to assess the

prevalence of pupils with different dis-

abilities, difficulties, and disadvantages.

Thirdly, countries vary greatly how inte-

grative their school system is for SNE

students. In some countries almost all SNE

students are educated in regular classes or

schools while in others virtually all of

them are educated in special schools

(Powell 2006; OECD 2007). These differ-

ences may occur also within any single

country when changes take place in

policies, conceptualisation, or available

resources. As will be elaborated below,

the provision of special needs education

has been increasing. We will describe this

trend more closely in the Finnish school

system and study its potential effects on

the external validity of school-based

delinquency research.

Learning difficulties, problem behaviour, andspecial needs education

According to the Organization for Econ-

omic Co-Operation and Development

(OECD), the need for SNE can arise from

three sources: disabilities, difficulties, and

disadvantages. ‘Disabilities’ refer to

impairments viewed in medical terms as

organic disorders attributable to organic

pathologies. ‘Difficulties’ refer mainly


Journal of Scandinavian Studies in Criminology and Crime Prevention4

Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

to behavioural or emotional disorders, or

specific difficulties in learning. ‘Disadvan-

tages’ are defined to arise primarily from

socio-economic, cultural, and/or linguistic

factors (OECD 2007).

All these causal pathways, especially the

second and the third, may be important

from the point of delinquent behaviour,

because they are known to be associated

with delinquency. According toMaguin and

Loeber, poor academic performance is

related to the prevalence and onset of

delinquency, and escalation in the frequency

or seriousness of offending. Their meta-

analysis shows that the poorer the academic

performance, the higher the delinquency

(Maguin and Loeber 1996:246). Levels of

academic achievement, school attendance,

and graduation rates are connected to youth

involvement in the criminal justice system

(Winters 1997).

While low attainment has been shown to

be a significant predictor of offending, the

link between these two is often indirect.

There are several possible transmission

mechanisms connecting poor school per-

formance and delinquency (Stephenson

2007:106–109). Many studies have

observed that cognitive problems are associ-

ated with above-average delinquent beha-

viour. There is a high prevalence of dyslexia

(reading and writing disabilities) among

prison populations (Jensen et al. 1999).

In theUnitedStates it hasbeenevaluated that

in the juvenile correction system the number

of youths identified as having disabilities is

almost four times higher than in public

school programmes (Quinn et al. 2005).

Some studies give even higher figures

comparing differences between special edu-

cational needs among young offenders and

the general school population (see Stephen-

son 2007:103–104).

Problems in cognitive skills and atten-

tion problems are believed to be common

causes of both poor academic performance

and delinquency. Learning difficulties and

low self-esteem as a learner may cause

frustration and may be expressed through

aggressive behaviour. These problems

lower the school motivation and may lead

to exclusion or even complete disengage-

ment. It is believed that interventions that

improve cognitive skills or decrease atten-

tion problems reduce delinquency (Maguin

and Loeber 1996:248; Winters 1997;

Stephenson 2007).

Reasons for placement in special needs

education

Students can be placed in special education

for a variety of reasons. Figure 1 shows the

main official causes of placement in special

needs education for grades 7–9. Pupils are

transferred to special needs education

mainly because of different types of

physical, mental, and cognitive disabilities

that cause learningdifficulties. The category

‘emotional or social problems’ is high-

lighted in the Figure because it is the

closest approximation of criminality-

related problems. It is very likely that

many students could have been placed in

SNE for many reasons. However, and what

is more important, all causes of SNE

placement are somehow related to cognitive

skills and/or attention problems.

Increase of special needs education

provision

Since 1999 the OECD has gathered a

longitudinal international database on the

trends in the number of students with

disabilities, difficulties, and disadvantages

(DDD students) receiving additional

resources. In the period of 1999–2003, the



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

percentage of DDD students receiving

additional resources increased in several

countries. National data from the United

States indicate the number and percentage

of youths receiving special needs education

services have increased nearly every year

since 1976–77. By 2005–06, a total of 6.7

million youths received SNE services,

corresponding to 14%of total public school

enrolment (Institute of Education Sciences

2007). Germany also manifests similar

trends (Powell 2006). The increase probably

reflects both the rising incidence of certain

types of disabilities, difficulties, and dis-

advantages and new policies making greater

resources available to special needs edu-

cation (Powell 2006; OECD 2007).

In international comparison, Finland

figures as the leading nation in the overall

SNE provision, with Iceland, Denmark, and

Norway also among the top nations (Powell

2006:583). The Finnish trend is consistent

with international trends. The number of

students placed in special needs education

has been increasing substantially during the

recent decade (Figure 2). The percentage of

students in SNE has more that doubled

between 1995 and 2006. This is unlikely to

be a simple function of the increase in the

types of problems that warrant placement in

SNE. Additionally, the educational system

has changed to a direction which empha-

sizes individual and differential treatment of

students.

Regardless of the causes for the increase,

the critical point from the perspective of

school-based research is that these students

are potentially, and in many cases actually,

side-tracked from the regular education

systems. Hence, the problem of SNE

students is increasingly salient in the

methodological evaluation of school-

based research. The increasing placement

of students with disabilities, difficulties,

and disadvantages to SNE threatens to

magnify the problem of selective non-

response to surveys, if SNE students are

excluded from school-based research.

1 Subsequent sweeps of the FSRD do not contain thisquestion, or measure different aspects of specialeducational services.

Figure 1. Primary cause of placement in special needs education in 2006 (%), grades 7–9, Finland

(Source: Statistics Finland).



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

Data

We use data from the Finnish Self-Report

Delinquency Study (FSRD 2001). The

FSRD survey is targeted at ninth-graders

(15–16-year-olds) in Finnish-speaking

schools. The schools are randomly selected

from a register of Finnish-language

schools. Each year, all ninth-grade stu-

dents of the selected schools comprise the

target population, including the students

who are placed in special needs education

classes because of disciplinary or learning

problems. The inclusion of the special

needs education groups and students is

a priority in data collection. In the

2001 sweep, the respondents (n ¼ 4347;

response rate: 89%) were asked: ‘Are you

at this moment placed in a special needs

education class?’1 Of all respondents,

6.2% reported that they were placed in

special needs education. The reason for

the placement was not specified.

However, there is a potentially import-

ant limitation in the FSRD data. The

information about the respondent’s status

as a regular class or SNE student was

based on the student self-report in the

2001 FSRD sweep. Hence it is possible

that the information about SNE place-

ment is not entirely accurate. Register

data from 2003 indicate that between

4% and 6% of the ninth-grade students

are registered as attending SNE classes

(Register of Educational Institutions,

2003)2. This figure is quite close to the

one based on student self-reports in

FSRD 2001.3

In what follows, our analytic strategy is

first to compare the delinquency levels of

regular and SNE students. We then

examine the contribution of SNE students

to prevalence and incidence of delinquency.

The overall procedure is rather similar to

that used by Fan et al. (2006) who

investigated the impact of so-called joke-

sters on delinquency prevalence in self-

report delinquency research. Third, we

tentatively explore whether observed

2The lower limit is based on assumption that schoolsfailing to report SNE students do not have them. Theupper limit is based on schools which have reported thenumber of SNE students.3 To assess the relevance of how SNE status is measured,we replicated the descriptive analyses of this article usinga small additional sample of known SNE students(n ¼ 32) in the Finnish International Self-Report Studyfrom 2006. In that sample, the student’s placement statuswas beyond doubt. The sample corroborated the resultsbased on the FSRD sample, in which the data on SNEparticipation are based on self-reports.

Figure 2. Percentage of students placed in special needs education (%), Finland 1995–2006 (Source:

Statistics Finland).



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

associations between specific risk factors

and delinquency depend on the presence of

SNE in the sample.

Prevalence and incidence of delinquency inregular and SNE classes

Prevalence

Table 1 shows the prevalence of delinquent

behaviour by the type of class the

respondent attended at the time of the

survey. In most offence types, students

placed in special needs education had

higher prevalence rates than students

attending regular classes. The SNE stu-

dents were about 1.5–2.0 times more likely

than students in regular classes to have

committed most of the offences.

The difference is particularly substantial

in auto thefts, beating up someone, fighting

or running away from home. The overall

‘risk difference’ is quite similar to the one

that Maguin and Loeber found when

examining the delinquency risk of students

with low academic performance (Maguin

and Loeber 1996:147).

In stealing at school, stealing at home,

and misuse of legal medicine, there were no

significant differences in the prevalence rates

of the two groups. Misuse of legal medicine

typically refers to taking pain-killers with

alcohol in order to boost the intoxicating

effect. The lack of difference in stealing at

school and at home may reflect the general

life-styles and routine activity patterns of the

special needs education group. Their life-

styles are probably less school- or home-

Table 1. Participation in delinquent behaviour last year, by educational placement, Finland

2001 (FSRD 2001). Higher prevalence is boldfaced

Regular classes

Special education

placement P (chi-square)

Truancy 37.4 59.6 0.000

Running away from home 5.6 18.3 0.000

Driving without licence 20.8 36.1 0.000

Graffiti writing/drawing 12.9 16.5 0.039

Destruction of property at school 8.1 16.7 0.000

Destruction of property elsewhere 9.6 17.8 0.000

Shoplifting 11.7 17.1 0.004

Stealing at school 19.3 17.4 0.251

Stealing at home 16.5 18.8 0.228

Buying stolen goods 5.6 11.3 0.000

Auto theft 0.6 3.3 0.000

Bullying at school 14.2 20.3 0.006

Taking part in a fight 12.8 30.7 0.000

Beating up somebody 6.8 25.9 0.000

Use of marihuana or hashish 8.1 13.9 0.000

Misuse of legal medicine 7.7 8.9 0.053

Use of other drugs 1.5 2.3 0.031

Drunken driving 11.8 25.1 0.000

n 4064 268



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

centred than the life-styles of the students

attending regular classes.

Table 1 compared the crime prevalence

of students in regular and SNE classes.

Another approach is to ask how much the

SNE students contribute to prevalence or

incidence estimates. How erroneous esti-

mates would have been produced if SNE

students had been excluded from the

sample? To begin with, it needs to be

noted that SNE students comprised only

6.2% of all students in the FSRD 2001

sample. No matter how criminal they are,

their impact on total prevalence is likely to

be limited.

In Figure 3, the contribution of SNE

students to prevalence is graphically high-

lighted. If SNE students had been exactly as

criminal as regular classes, there would

have been only a straight line in the figure.

Because the SNE students were actually

more criminal than the regular classes, they

‘push up’ the prevalence estimates. How-

ever, due to their relatively small number,

their inclusion does not result in dramatic

increase in the estimated prevalence of

offending. The largest impact is found in

violence: including the SNE students

results in an increase of one percentage

point in the prevalence estimate. Driving

without licence, truancy, drunken driving,

and running away from home also manifest

a one percentage point increase.

It can be concluded that the effect of

including SNE students in prevalence esti-

mates is relatively small. The exclusion of

Figure 3. Change of observed prevalence when special needs education students are included in the

sample (percentage points) (Source: FSRD 2001).



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

SNE students from school samples does not

seem to compromise the ability of self-report

surveys to estimate prevalence levels, at least

in Finland.We next turn to the estimation of

incidence.

Incidence

Wecalculated the last-year incidence figures

to examine the respective contributions of

regular education and SNE students to

FSRD 2001 incidence estimates. These

kinds of incidence estimates tend to be

heavily influenced by students reporting

large numbers of incidents. We therefore

used a forced maximum of 25 annual

offences. All self-reports exceeding that

limit were recoded as 25.

The results are shown in Figure 4. For

example, SNE students, comprising 6% of

the respondents, committed about 20% of

last-year incidents of beating someone

up. The impact of SNE students on

incidence estimation is much bigger than

their impact on prevalence estimation.

SNE students tend to commit more

offences than students in normal edu-

cation. Therefore, they contribute more to

incidence of crime than they contribute to

prevalence of crime. From a methodologi-

cal point of view, this means that samples

excluding SNE students are likely to under-

estimate the incidence of crimes (while the

under-estimation of prevalence is small or

non-existent).

Correlates of delinquency

Above, we observed that exclusion of SNE

students from samples has a relatively

small impact on prevalence estimation but

seems to risk the external validity of

incidence estimates. Next we explore

whether the exclusion of SNE students

impacts substantive research on the corre-

lates and causes of juvenile delinquency.

Since ‘school criminology’ is sometimes

accused of focusing on trivial and occasional

delinquency, we decided to use frequent

delinquency as our dependent variable. This

was alsomotivated by the above finding that

incidence appears to be more sensitive to

SNE exclusion than prevalence. Based on a

sum variable of 14 offence types, the

respondents who had offended at least 25

times during the last year were defined as

frequent offenders. The repertory of inde-

pendent variables, described in the Appen-

dix, was restricted by the rather limited set

of correlates in the FSRD 2001.

The Appendix additionally shows vari-

ablemeans separately for regular classes and

SNE students. As can be seen, all risk factors

of delinquency were more prevalent among

students placed in special needs education (P

, 0.05). On average, the SNE students had

more economic problems and unemploy-

ment in the family, came from non-nuclear

families, and reported worse relationships

with parents. The SNE students were more

likely to have a girl-friend or boy-friend,

which may reflect early social and/or

biological maturation (Stattin and Magnus-

son 1989). They were also more likely to

come from large families. Two-thirds of

them were males. These descriptive facts

alone strongly suggest that the analysis of

risk factors of delinquent behaviour benefits

from their inclusion in research.

Since the SNE students are relatively few,

the relevance of their inclusion or exclusion

was additionally and tentatively examined

by specifying a multivariate regression

model with and without them (Table 2).

Irrespective of SNE inclusion, the following

variables emerged as significant correlates of

frequent offending: economic situation of



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

the family, familystructure, relationshipwith

parents, having a girl-friend/boy-friend, and

sex. However, the point of the present

analysis was to examine whether the

inclusion of SNE students has any relevance

for which factors are pin-pointed as relevant

correlatesof repeatoffending. It appears that

the presence of SNE students has some

marginal relevance for the results. The

truncated sample excluding SNE students

erodes the association between (bad) econ-

omic conditions of the family and repeat

delinquency. Had we not included the SNE

students in FSRD 2001, we might have

concluded that serious economic difficulties

in the family are not significantly associated

with repeat offending. As a tentative and

preliminary conclusion, it might be argued

that SNE exclusion involves the risk of

undermining the ability of the study todetect

the economical and structural correlates of

frequent offending. This is consistent with

the finding that students from relatively

disadvantaged social and familial back-

grounds are over-represented in the SNE

population.

Figure 4. The percentage of offences committed by regular education and special needs education

students (nregular education ¼ 4064, nspecial needs education ¼ 268) (Source: FSRD 2001).



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

Some additional findings warrant brief

comment as a stimulus for further inquiries.

First, when SNE students are excluded,

better-than-average economic conditions of

the family emerge as risk factor

Table 2. Correlates of frequent offending, with and without special needs education students.

Logistic regression equations, odds ratios

A. All students

B. Special needs

education students

excluded (truncated

sample)

Exp(B) 95% CI Exp(B) 95% CI

Economic situation of the family

Normal 1.00 1.00

Better than normal 1.32 0.93–1.88 1.46* 1.00–2.13

Difficulties 1.21 0.86–1.70 1.35 0.94–1.93

Serious difficulties 3.26** 1.76–6.00 2.08 0.95–4.55

Family structure

Both present 1.00 1.00

Single mother 0.91 0.66–1.26 0.86 0.60–1.23

Single father 0.62 0.32–1.18 0.67 0.34–1.32

Neither present 2.54** 1.43–4.50 2.08* 1.06–4.10

Relationship with parents a

Good/close 1.00 1.00

Average 1.71** 1.16–2.51 1.88** 1.24–2.85

Strained/distant 3.87** 2.68–5.60 4.20** 2.81–6.27

Dating behaviour currently

No 1.00 1.00

Yes 2.20** 1.68–2.88 2.36** 1.77–3.15

Parental employment

Both 1.00 1.00

One 0.91 0.67–1.24 0.83 0.59–1.16

Neither 1.08 0.63–1.86 1.06 0.58–1.96

Family size

0–3 siblings 1.00 1.00

4 or more siblings 1.20 0.70–2.08 1.15 0.62–2.15

Sex

Female 1.00 1.00

Male 2.46** 1.87–3.23 2.49** 1.86–3.34

n 4040 3796

a Based on sum variable with four items (alpha ¼ 0.67). Items measured relationships with parents and

parental knowledge of respondent’s leisure time friends. The sum variable was categorized into three equally

large categories. In both full and truncated data-based models, father’s socioeconomic status (SES) is included

(non-significant odds ratios in all models). Missing data not replaced. * ¼ p , .05; ** ¼ p , .01.



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

of delinquency. This appears to be consistent

with the notion that the economic con-

ditions–delinquency link may be non-linear

so that exceptionally good economic situ-

ation of the family may be a risk factor of

delinquency (Wright et al. 1999). Second,

when we included father’s SES in the model,

it did not emerge as a significant correlate of

frequent offending. This probably reflects

the fact that the occupation-based SES

measure fails to capture real economic-

structural differentials in the research

population (Farnworth et al. 1994). The

same seems to apply to parental employ-

ment. In the presence of the economic

situation variable, the SES and parental

employment variables are uncorrelated with

delinquency risk. Parental unemployment

means that one or two parents have more

time to control their children’s behaviour,

which reduces delinquency risk when the

economic aspect of unemployment is separ-

ately tapped by another variable.

The findings are largely consistent with

the arguments advanced by the critics of

school criminology, such as Hagan and

McCarthy (1999). Students placed in

special education manifest multiple risk

factors, and their exclusion may influence

the observation of links between risk

factors and delinquency. Luckily, the SNE

students actually were available through

the (Finnish) school system where exclu-

sion from the comprehensive school system

is deployed only when all other means are

ineffective. As noted above, the inclusive-

ness of school systems is a variable, not a

constant in international and temporal

perspectives. In some other school systems,

problematic students might be side-tracked

to different special schools, ‘youth facili-

ties’, or even to repositories like the prison

or the street.

Summary and discussion

The main result of our analysis is that SNE

students differ from those who do not

receive special needs education. The SNE

students tend to have higher delinquency

levels. More precisely, we observed that the

exclusion of SNE students has a relatively

small impact on the estimation of overall

prevalence levels of delinquency. In con-

trast, such exclusion has a major impact on

incidence estimation. Samples excluding

SNE students are likely to under-estimate

the incidence of delinquency.

Additionally, the prevalence of major

social and economical risk factors of

delinquency is higher in the population of

students placed in special needs education.

This clearly indicates that their inclusion is

important for research focusing on the

causal sources of delinquency. The exclu-

sion of SNE students from the sample

appears to have a marginal influence on

which variables emerge as correlates of

serious offending and possibly on how

strong the correlation is. Our results

tentatively suggest that SNE exclusion

undermines the ability of the study to

detect the link between economical con-

ditions and frequent delinquency. Further

research is needed to explore whether SNE

exclusion artificially boosts the link

between ‘human relation’ types of variables

such as parental relationships. Further-

more, our data did not include measures of

cognitive skills or impairments, but logi-

cally one would assume that excluding



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

SNE students jeopardizes the capacity of a

study to assess the role of cognitive factors

in delinquency causation. Taken together,

the exclusion of SNE students from the

research design affects the validity of

school-based self-report delinquency sur-

veys by influencing population estimates of

delinquency incidence, and by potentially

affecting the observed associations

between delinquency and its risk factors.

Needless to say, the findings are depen-

dent on the setting of our study, that is, the

institutional arrangements of Finnish com-

prehensive school in this decade. This,

however, is a lesson we wish to draw from

the findings. The critique directed against

‘school criminology’ has been warranted

and beneficial for school-based delin-

quency research, because more attention

is being given to the institutional ramifica-

tions of such research. Especially in

comparative research the institutional

archipelago of different areas and times

needs to be charted. Such analyses could

also highlight that the critique of school

criminology may be exaggerated. At least

in Sweden and Finland, involvement in

crime is only one of a number of reasons

why an adolescent can be placed in

institutions. This means that the insti-

tutional or custodial juvenile population

includes youths who are actually less

delinquent than the average school popu-

lation (Shannon, 2006). Consider, for

example, the youths who are placed in

special institutions because of physical

handicaps. The SNE students who are

placed in special classes within normal

schools may be more delinquent than

institutionalized youths in general.

Recently it has been argued that the

cultural context of a country, for example

the level of general social trust, may impact

the validity of comparisons based on self-

report delinquency research (Kivivuori

2007:27–31). This article adds to that

argument by stressing the role of the

institutional context for such comparisons.

Countries (and epochs) are likely to vary

according to how inclusive their ‘ordinary’

or ‘comprehensive’ school system is. In

some countries, students with different

types of disabilities, difficulties, and dis-

advantages are kept within the regular

schools and even within the regular classes,

while other countries side-track such

students to special needs education groups

or special education institutions. However,

there is a need to regard the institutional

framework in an even broader perspective.

It is important to describe how the school

system processes children and adolescents

with difficulties and disadvantages, but this

is not sufficient. The youths who are

entirely absent from or who manage to

circumvent the school system need to be

also considered. The complete institutional

location of adolescent populations needs

to be charted. This means that all

‘repositories’ of youths should be taken

into account, ranging from the regular

school to various kinds of youth facilities,

foster care arrangements, clinics, prisons,

and the street. This is needed if the purpose

of the study is to compare the delinquency

of the populations in a way that exceeds the

comparison of prevalence levels. Basic

prevalence levels seem to be rather immune

to the problems specified here, if suffi-

ciently large samples are used.

References

Cernkovich SA, Giordano PC, Pugh MD

(1985). Chronic Offenders: the Missing

Cases in Self-Report Delinquency Research.



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

Journal of Criminal Law & Criminology

76(3): 705–732.

Fan X, Miller BC, Park K-E, Winward BW,

Christensen M, Grotevant M, Tai RH

(2006). An exploratory study about

inaccuracy and invalidity in adolescent self-

report surveys. Field Methods 18(3):

223–244.

Farnworth M, Thornberry TP, Krohn MD,

Lizotte A (1994). Measurement in the Study

of Class and Delinquency: Integrating

Theory and Research. Journal of Research in

Crime and Delinquency 31(1): 32–61.

Hagan J, McCarthy J (1999). Mean Streets:

Youth Crime and Homelessness. Cambridge:

Cambridge University Press.

Institute of Education Sciences (2007). The

Condition of Education. US Department of

Education.Washington,DC:USGovernment

Printing Office.

Jensen J, Lindgren M, Wirsen Meurling A,

Ingvar DH, Levander S (1999). Dyslexia

Among Swedish Prison Inmates in Relation

to Neuropsychology and Personality. Journal

of the International Neuropsychological

Society 5: 452–461.

Junger-Tas J, Marshall IH (1999). The Self-

Report Methodology in Crime Research. In:

Tonry M (ed.). Crime and Justice: a Review

of Research. Vol. 25. Chicago: The Univer-

sity of Chicago Press.

Kivivuori J (2007). Delinquent Behaviour in

Nordic Capital Cities. Publication no. 227.

Helsinki: Scandinavian Research Council for

Criminology/National Research Institute of

Legal Policy.

Kollisch T, Oberwittler D (2004). Wie ehrlich

berichten mannliche Jugendliche uber ihr

delinquents Verhalten? [How Honestly Male

Adolescents Report About Their Delinquent

Behaviour?] Kolner Zeitschrift fur Soziologie

und Sozialpsychologie 56(4): 708–735.

Maguin E, Loeber R (1996). Academic Per-

formance and Delinquency. In: Tonry M

(ed.). Crime and Justice: a Review of

Research. Vol. 20. Chicago: University of

Chicago Press.

Naplava T, Oberwittler D (2002). Methode-

neffekte bei der Messung selbstberichteter

Delinquenz von mannlichen Jugendlichen

[Methodological Effects in the Measurement

of Self-Reported Delinquency Among

Males]. Monatsschrift fur Kriminologie und

Strafrechtsreform 85(6): 401–423.

OECD (2007). Studentswithdisabilities, learning

difficulties and disadvantages. Policies,

statistics and indicators. http://www.oecd.org/

document/45/0,3343,en_2649_39263231_

35669869_1_1_1_1,00.html (accessed1April

2009).

Porterfield AL (1946). Youth in Trouble. Fort

Worth: Leo Potishman Foundation.

Powell J (2006). Special Education and the Risk

of Becoming Less Educated. European

Societies 8(4): 577–599.

Quinn M, Rutherford R, Osher D, Poirier J

(2005). Youth with Disabilities in Juvenile

Corrections: a National Survey. Exceptional

Children 71(3): 339–345.

Register of Educational Institutions (2003).

Statistics Finland. Upublished data set.

Shannon D (2006). Chronic Offenders or

Socially Disadvantaged Youth? Institutiona-

lizedMales as Missing Cases in School-based

Delinquency Research. Journal of Scandina-

vian Studies in Criminology and Crime

Prevention 7(1): 78–100.

Statistics Finland (2007). Education Statistics.

Helsinki. http://www.stat.fi/til/erop/index_

en.html (accessed 1 April 2009).

Stattin H, Magnusson D (1989). Social tran-

sition in adolescence: a biosocial perspective.

In: Ribaupierre A (ed.). Transition Mechan-

isms in Child Development: the Longitudinal



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

Perspective. Cambridge: Cambridge Univer-

sity Press.

Stephenson M (2007). Young People and

Offending: Education, Youth Justice and

Social Inclusion. Cullompton: Willan Pub-

lishing.

Stone AA, Turkkan JS, Bacrach CA, Jobe JB,

Kurtzman HS, Cain VS (eds) (2000). The

Science of Self-Report: Implications for

Research and Practice. Mahwah, New

Jersey: Lawrence Erlbaum Associates.

Thornberry TP, Krohn MD (2000). The Self-

Report Method of Measuring Delinquency

and Crime. In: Measurement and Analysis of

Criminal Justice. Criminal Justice 2000.

Vol. 4. National Institute of Justice.

http://www.ncjrs.org/criminal_justice

2000/vol_4/04b.pdf (accessed 1 April 2009).

Thornberry TP, Krohn MD (2003). Compari-

son of Self-Report and Official Data for

Measuring Crime. In: Pepper JV, Petrie CV

(eds). Measurement Problems in Criminal

Justice Research. Workshop Summary.

National Research Council of the National

Academies. Washington DC: The National

Academies Press.

Tourangeau R, McNeeley M (2003). Measuring

Crime and Crime Victimization: Methodo-

logical Issues. In: Pepper JV, Petrie CV (eds).

Measurement Problems in Criminal Justice

Research. Workshop Summary. National

Research Council of the National Acade-

mies. Washington DC: The National

Academies Press.

Winters CA (1997). Learning Disabilities,

Crime, Delinquency and Special Education

Placement. Adolescence 32(126): 451–463.

Wright BRE, Caspi A, Moffitt TE, Miech RA,

Silva PA (1999). Reconsidering the

relationship between SES and delinquency:

causation but not correlation. Criminology

37(1): 175–194.

JANNE KIVIVUORI

Research Director

National Research Institute of Legal Policy

POB 444

00531 Helsinki

FINLAND

Email: [email protected]



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

Appendix

Descriptives of variables

Coding Mean SD

Mean,

regular

education

Mean,

special

needs

education

Economic

situation

of the family

1 ¼ average;

2 ¼ better than average;

3 ¼ difficulties;

4 ¼ serious difficulties

1.58 0.85 1.57 1.78

Family structure 1 ¼ both present;

2 ¼ single mother;

3 ¼ single father;

4 ¼ neither present

1.42 0.72 1.39 1.74

Relationship

with parents

1 ¼ good/close;

2 ¼ average;

3 ¼ strained/distant

0.99 0.79 0.97 1.16

Dating

behaviour

currently

0 ¼ no; 1 ¼ yes 0.24 0.43 0.24 0.36

Parental

employment

1 ¼ both employed;

2 ¼ one employed;

3 ¼ neither employed

1.39 0.60 1.37 1.60

Family size 0 ¼ 0–3 siblings;

1 ¼ 4 or more siblings

0.06 0.23 0.06 0.09

Sex 0 ¼ female; 1 ¼ male 0.50 0.50 0.49 0.67

Repeat

offending

0 ¼ others; 1 ¼ at least

25 annual offences

0.07 0.25 0.06 0.16



Dow

nloa

ded

by [

McM

aste

r U

nive

rsity

] at

19:

32 1

9 D

ecem

ber

2014

Documents

The Challenge of Special Needs Education in School-Based Delinquency Research