Networks and Actor Attributes in Early Adolescence

219 Pages·2006·1.93 MB·English

ICS Codebook 61
Networks and Actor Attributes in Early Adolescence
[2003/04]

Principal Investigator:
Andrea Knecht

Department of Sociology
Utrecht University
Heidelberglaan 2
3584 CS Utrecht
The Netherlands
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Citation

ICS Codebook number: 61

Data set:
Networks and Actor Attributes in Early Adolescence [2003/04]

Principal Investigator:
Andrea Knecht
Department of Sociology/ICS,
Utrecht University, Heidelberglaan 2, 3584 CS Utrecht, The Netherlands

Years of data collection:
2003/04

Depositor:
Department of Sociology/ICS, Utrecht University

Sponsor:
NWO Netherlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organization for
Scientific Research)

Producer:
ICS Data Archive

Distributor:
Data Archiving and Networked Services DANS, Postbus 93067, 2509 AB Den Haag, The
Netherlands

Restriction of use:
All publications using these data, should refer to the data in the following way:

The data were gathered by Andrea Knecht, as part of her PhD research, building on methods
developed by C. Baerveldt, initiator and supervisor of the project. The project is funded by the
Netherlands Organisation for Scientific Research NWO, grant # 401-01-554 and is part of the
research program ‘Dynamics of Networks and Behavior’ with principle investigator T.A.B.
Snijders.

And to this codebook as follows:

Andrea Knecht (2006), Networks and actor attributes in early adolescence [2003/04].
Utrecht, The Netherlands Research School ICS, Department of Sociology, Utrecht University.
(ICS-Codebook no. 61).

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Table of Contents

Page Title

5-6 1. Study description

7-12 2. Project description
2.1. Scientific relevance
2.2. Elaboration of the problematic
2.3. Methods and techniques of research
2.4. Societal relevance

12-142 3. Data Overview
3.1. Description of data of pupils
3.2. Description of data of teachers
3.3. Descriptives of data of pupils
3.4. Descriptives of data of teachers

143-214 4. Appendix:
4.1. Pupil’s questionnaire wave 1 - 4
4.2. Mentor’s questionnaire wave 1 – 4
4.3. Music codes

215-216 5. The ICS codebook series

217-220 6. List of ICS codebooks

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1. Study description
PRINCIPAL INVESTIGATOR:
Andrea Knecht
Department of Sociology/ICS,
Utrecht University, The Netherlands

FUNDING:
NWO (401-01-554)

DATES OF DATA COLLECTION:
2003/04

EXECUTERS OF DATA COLLECTION:
Researcher and assistants

KIND OF DATA:
Panel survey

UNITS OF OBSERVATION:
Respondents

POPULATION:
Pupils in first grade of Dutch secondary schools (‘brugklassers’)
Mentors (main class teacher) of first grade of Dutch secondary schools

METHOD:
Questionnaire

SAMPLING:
All pupils in the first grade of 14 Dutch secondary schools
Mentors (main class teacher) of first grades of 14 Dutch secondary schools
In the sample are schools that are not among the 10% largest and 10% smallest secondary schools
in the Netherlands. There are no schools with an uncommon denomination or for special needs.
From the remaining schools, a selection was made to have a mixture of public and private, rural
and urban schools spread all over the Netherlands. All main educational levels are included.

WEIGHTING:
No weighting

STATUS/DATA REPRESENTATION:
SPSS portable files

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NUMBER OF CASES:
V wave: pupils 2996
teachers 121
W wave: pupils 2862
teachers 118
X wave: pupils 2913
teachers 111
Y wave: pupils 2932
teachers 84
NUMBER OF VARIABLES:
V wave: pupils 425
teachers 186
W wave: pupils 421
teachers 186
X wave: pupils 421
teachers 175
Y wave: pupils 421
teachers 294

LANGUAGE OF WRITTEN MATERIAL:
Study description: English
Questionnaire: Dutch
SPSS-labelling: English

SCIENTIFIC DISCIPLINE:
Sociology

KEYWORDS:
Social networks, adolescence, relations, behavior, social norms

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2. Project description

2.1. Scientific relevance

In this project the emergence of effective group norms is studied in pupils’ social networks at
secondary schools. The norms studied are restricted to social behavior of pupils, more precisely,
the way pupils use social rules in three areas which are very important to them: school, peer group,
and the outer (adult) society. In this study, social rules at schools refer to making homework and
truancy; social rules in the peer group refer to trust and reciprocity; and social rules in the outer
society refer to social action and delinquency.
The relevance of group norms at school is illustrated by a classical study of Willis (1977).
He uses the concept of anti-school culture (which is broader than norms per se), and shows how
working class pupils first generate such a set of norms and then may be affected by it, eventually
leading them to becoming dropouts. His study shows that anti-school norms can develop, and that
they can be effective, i.e., influence behavior; and that school norms are strongly related to the
other norms about social behavior.
The question of development of norms can hardly be treated without discussing the
dynamics of networks and behavior. According to Coleman (1990), norms can come into existence
when individual behavior has externalities (i.e. effects on other individuals) and when there is the
possibility of sanctioning (cf. project 3, and related rational-choice explanations for the emergence
of norms, e.g., Voss 2000, 2001). Being subjected to consequences of others’ behavior and having
the possibility of sanctioning takes place in the context of the social embeddedness in networks.
The development of norms influences the extent to which group members perform the behavior in
question, but the norms are also influenced by the behavior itself being observed by group
members and by the observed sanctions. The decision to carry out sanctions again is influenced by
the individual’s network position and status, and will feed back upon this status (a successful
sanction will tend to increase, an unsuccessful sanction to decrease the status of the sanctioning
person).
Pupils avoid actual sanctions by comparing their intended behavior to norms of others, and
using this in choosing how to behave. Two kinds of reference processes are relevant here:
normative and comparative references (also see Guldemond, 1994). In normative references pupils
compare their own behavior with group norms (Homans, 1950). In comparative references they
compare their behavior with that of significant others (Festinger, 1954). When a little delinquent
subgroup exists in a non-delinquent class, comparative references could stimulate a group member
to shoplifting, but normative references would not. This illustrates that it is important to compare
the effects of groups and subgroups.
Social network research is essential for the study of group norms (cf. Friedkin, 2001).
However, empirical scientific studies of development of norms in networks of adolescents are rare.
Hallinan started to study pupils' networks in the 70’s and 80’s (for an overview see Hallinan &
Smith, 1989). Most studies are descriptive (like Hallinan’s). Recently, researchers started to tackle
the topic of influence of the network on individual behavior and individual norms (see for instance
Bender & Lösel, 1997, Reed & Rose 1998, Houtzager & Baerveldt, 1999, about the effect of peer
relations on delinquent behavior). No empirical studies of the creation of norms have been carried
out in which the mutual influence between behavior and relational networks were traced
longitudinally . Our research question, accordingly, is quite basic:
What conditions facilitate the development of effective group norms in pupils’ social networks in
the first years of high school; and what induces the content of these norms?
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2.2. Elaboration of the problematic

Group norms in social networks may or may not develop. When group norms do not develop,
pupils’ individual norms (attitudes) vary much and the chance that behavior is sanctioned is small.
In this case it is possible that social network dynamics do not have any effect on norms. The
attitudes within pupils’ networks then could reflect, e.g., the aggregated backgrounds of the pupils,
especially the norms inherited from parents. This would mean that the pupils’ network plays no
role in the development of norms, the individual pupil’s norms developing from other reference
groups like family, school, or neighborhood. This is indeed the (often implicit) assumption of
many studies on social norms. However, in many situations there will develop group norms.
When group norms develop, they bring about a leveling of attitudes and a perception of
sanctioning. The power of group norms is that pupils can trust others to sanction ‘bad behavior’ or
back up their own sanctions. The development of such trust is intertwined with the development of
the social network and cooperation (cf. project 3; see also Snijders, 1996, section 1.4). However,
there are theoretical arguments that also when sanctioning is expected, pupils might act in conflict
with the norms. From ASE-theory (see project 5), e.g., we could predict that pupils would deflect
more if their attitudes deviate more from the norm, social costs of deflecting are less, and their self
efficacy is stronger. From this, we could conclude that norms are less effective when attitudes vary
more. Also, it could be predicted that norms are less effective in loose networks, and that norms
are less effective for pupils who are less dependent on others, like high status pupils and loners.
Furthermore, we could conclude that for pupils with a low educational level, positive group norms
about peer interaction are more effective than about school behavior because they perceive that
they can improve their behavior with peers more easily than their school behavior.
Aside from the question when norms are effective, it is still an open question which
network characteristics are conducive for the development of group norms. According to Coleman
(1990), effective group norms develop when the ties in networks are strong and the networks are
closed. This is consistent with arguments from Coleman & Hoffer (1987) who state that in closed
networks costs of information and sanctions are lower, which makes it easier to maintain effective
group norms. From this, it could be predicted that group norms will arise more easily in cohesive
and intimate pupils’ networks. However, the relevant others do not necessarily have to comprise
all the members of the network. Baerveldt and Snijders (1994) suggest that a social network can be
segmented into subgroups., which would lead to stronger norms within the subgroups, while the
content of norms could differ strongly between the subgroups. It seems that Coleman & Hoffer’s
arguments can also be used for subgroups: when subgroups within the pupils’ networks are
cohesive and intimate, group norms within those subgroups develop more easily. It is not easy to
predict the content of the norms, especially when pupils’ networks are segmented, because pro-
social norms may develop as easily as anti-school norms.
The pupil’s network is bigger than the pupils’ network. Parents and teachers are also part
of a pupil’s network. Therefore, when parents and teachers are important, Coleman & Hoffer’s
arguments should be extended to these bigger networks. This means that the whole network of
pupils, parents, and teachers should be closed to produce a group norm shared by all. As the
attitudes of parents and teachers are mainly those of the dominant society, the group norms
accordingly will be the same. According to Bronfenbrenner (1979) and Bronfenbrenner & Gecci
(1994), congruence between social norms of different social networks (like home and school) of
children facilitates a development according to dominant norms. This agrees with a classical
theory of Coleman (1961), who states that when schools have a stable and visible network of
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parents (when they are a ‘community’), the norms of the whole school population are those of the
parents, whereas in other cases the norms of popular pupils dominate.
Coleman’s community hypothesis has been questioned in social network research.
Empirical results are not decisive (e.g., Dijkstra, 1997; Dijkstra & Veenstra, 1999). According to a
study of Baerveldt (1992), Dutch secondary schools hardly differ systematically with respect to
delinquency, integration of pupils, or school climate. However, Dijkstra (1992, 2001) concludes
that in Reformed schools, school climate can have a substantial effect on school motivation of
pupils. Morgan & Sorensen (1999) state that the latter type of school can favor positive school
norms because they produce more opportunities for information and resources (see also
Granovetter, 1973). Their arguments reflect a recent discussion in social network research about
the value of open versus closed networks.

2.3. Methods and techniques of research

We collected the longitudinal data at for time points with three month in between in the academic
year 2003/04. The data was gathered with the help of standardized questionnaires from pupils in
first grade of secondary school (brugklassers). In total 126 classes in 14 schools participated. The
schools are spread out in the Netherlands. They were chosen from a data set containing all Dutch
secondary schools after excluding 10% of the smallest and 10% of the biggest schools. Some
randomly selected schools were informed about the study and were asked if they would like to
participate. From the schools that were willing to participate we chose public schools and those
with different kind of denominations and schools from different areas. The main selection criterion
were the educational tracks of the classes. We tried to match the percentage of classes of one
educational track based on the previous year with the national percentage of this educational track.
In the end this did not work out as the number of educational tracks per school can vary very
easily from one year to the next.
The first survey took place in the first few weeks after the beginning of the new academic
year in August/September. Trained assistants visited the schools and distributed the questionnaires
for pupils. They gave explanations about the purpose and the way to handle the questionnaire.
They were available for questions throughout the time the pupils filled in the questionnaire. These
questions and comments from pupils were written down and considered before the next measuring.
The questionnaire was pre-tested in a small pilot study and subsequently adjusted. The big
majority managed to finish the questionnaire within 40 minutes. There were no big differences
between pupils of different educational tracks.
The pupils’ questionnaire includes items about reciprocity and trust (cf. project 3),
homework and truancy (Bosker & Hofman 1994), social action and delinquency (Baerveldt 2000),
about related norms/attitudes (cf. project 5, see also Scheerens and Bosker 1997), expected
acceptability and sanctions by fellow pupils, school, and parents, and about self-efficacy (project
5; also see Dijkstra & Kassenberg, 1999). The extent to which norms are a group phenomenon is
reflected by intra-group correlations in the attitudes, combined with (aggregated) expectations
about sanctions.
The actual existence of relationships between pupils is measured by using dyadic social
network items in the questionnaire. The items concern shared activities, social support, friendship,
intimacy, trust, and sanctions. For each item, pupils can nominate fellow pupils in the same class.
Thus, for each item, the pupils in each class constitute a pupils’ network (Houtzager & Baerveldt,
1999, Baerveldt, 2000).
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