1-s2.0-S0304422X13000132-main.pdf

Adolescents school experience and the importance of

having a cool mobile phone: Conformity,

compensation and resistance?

Mariek Vanden Abeele a,*, Keith Roe b

a Department Communication and Information Science, University of Tilburg, PO Box 90153,

5000 LE Tilburg, The Netherlandsb Leuven School for Mass Communication Research, University of Leuven, Parkstraat 45,

Box 3603, B-3000 Leuven, Belgium

Available online 8 May 2013

Abstract

Based on Bourdieus cultural capital theory this studycarried out among 1899 Flemish secondary school

pupilsexamines (1) whether adolescents experiences at school predict their attitude towards the mobile

phone as a status object, and (2) whether this attitude, in turn, predicts ownership of a high-status phone. Three

concurrent hypotheses were tested. Our conformity hypothesis was supported: in line with the social image

that the school system bestows on them, adolescents in non-academic tracks attach greater importance to

having a cool mobile phone, and lagging behind indirectly predicted this attitude via school track. The

compensation hypothesis was not supported: no direct relationship was found between academic self-

concept or lagging behind and adolescents attitude towards the mobile phone as a status object. The

resistance hypothesis was supported: adolescents with lower academic self-concept, who have lagged

behind and who are in a semi-academic or vocational school track have a more negative attitude towards

school, which in turn predicts a more positive attitude towards the mobile phone as a status object. Finally,

having a more positive attitude towards the mobile phone as a status object strongly predicts ownership of a

high-status mobile phone. Gender, age and ethnicity were shown to moderate some of the relationships found.

# 2013 Elsevier B.V. All rights reserved.

1. Introduction

Previous studies on adolescent mobile phone use have identified the use of the mobile phone

as a status object as a distinctive feature of contemporary mobile youth culture (Campbell and

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Poetics 41 (2013) 265293

* Corresponding author.

E-mail addresses: [email protected] (M. Vanden Abeele), [email protected] (K. Roe).

0304-422X/$ see front matter # 2013 Elsevier B.V. All rights reserved.http://dx.doi.org/10.1016/j.poetic.2013.03.001
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Park, 2008; Castells et al., 2007). Adolescents regard characteristics such as the brand, color or

the technical performance of their phone as a means to express their personal style and group

membership (Caronia and Caron, 2004; Ling, 2004; Skog, 2002). Particularly during early and

mid-adolescence, when teens are at the height of identity exploration (Erikson, 1968; Waterman,

1982, 1990), having a cool mobile phone seems to matter greatly (Green, 2003; Ling and Yttri,

2002, 2006).

Over the past decade, a number of mostly qualitative studies have provided us with rich

insights into the symbolic meaning that adolescents assign to the mobile phone (e.g., Blair and

Fletcher, 2011; Oksman and Turtiainen, 2004; Walsh et al., 2009). Their strong focus on the

commonalities among adolescents, however, has led to neglect of potential differences between

adolescents and their contextualization (Goggin and Crawford, 2011; Haddon, 2007; Haddon and

Vincent, 2009; Katz and Sugiyama, 2006). In this article, differences in adolescents ownership

of and attitude towards the mobile phone as a status object are contextualized in terms of their

experiences in the school system.

School experience was chosen because previous research has shown that adolescents position

in the school system and other (oftentimes related) indicators of school success and failuresuch

as school performance or school commitmentare powerful predictors of media use: pupils who

are successful in the school system, for example, have a stronger preference for media contents

that are culturally more legitimate, while unsuccessful pupils report a stronger preference for

media contents generally considered to be culturally less legitimate (Roe, 1992, 1995).

Bourdieus (1979 [1984]) theory of cultural capital explains these differences in the cultural

preferences of pupils by referring to a hidden mechanism of the school system, namely

socialization into the social image (and, thereby, the cultural preferences) that belongs to an

academic status position. According to this perspective, cultural preferences shared by pupils in

similar academic positions are evidence of their conforming behavior. Besides the effect that

ones position in the school system may have, adolescents individual reactions to their position

and their personal performance may also affect cultural preferences; in particular, youths who

experience failure in school may seek out media practices and contents as a means to compensate

for and show resistance to the reward system of the school.

The purpose of this study is to investigate whether these school experiences relate to attitudes

towards and ownership of the mobile phone as a status object. We test three hypotheses about the

mechanisms underlying this relationship among Flemish high school students: conformity,

compensation and resistance. To begin, however, we shall situate our study in cultural

capital theory.

2. Cultural capital and mobile phones as desired goods in youth consumer culture

2.1. Cultural capital theory and consumer culture

Skog (2002) found that adolescents from lower class backgrounds and those with low school

performance were significantly more likely to own a mobile phone than adolescents from higher

class backgrounds and with high school performance. At first sight, given that higher class youths

are more likely to have the financial resources to buy an up-scale mobile phone and that the elite

is believed to distance itself from the lower classes by means of conspicuous consumption

(Veblen, 1899 [1979]), these results appear contradictory. The insights of Bourdieus cultural

capital theory, however, may help us understand why the mobile phone may be the object of a

reversed logic.

M. Vanden Abeele and K. Roe / Poetics 41 (2013) 265293266

According to Bourdieu (1979 [1984]), the upper classes achieve distinction foremost by

displaying distinctive cultural tastes that do not necessarily involve the most expensive or

luxurious consumer goods. Higher class people are found to be less favorable towards many

aspects of popular consumer culture. When they reject popular consumer culture, this can be

understood as a subtle form of distancing themselves from lower classes. Moreover, with their

preference for simplicity rather than ornateness, they may implicitly mock the wealth of the

nouveaux riches (Steiner and Weiss, 1951, p. 263). This tendency towards counter-

snobbery (Steiner and Weiss, 1951), is most notable in those areas in which intellectualism does

not play a rolefor example, in the area of ostentatious and conspicuous consumption of

consumer goods (Bourdieu, 1979 [1984]). While people from lower socio-economic status (SES)

backgrounds more openly embrace materialism and a desire for luxury and abundance, the elite is

(in)formally educated to downplay materialism and display more abstract humanist ideals

(Bourdieu, 1979 [1984]; Holt, 1998). Kohn (1977) attributes this to the fact that the values of

people from lower SES backgrounds emphasize conformity and external rewards (e.g., money)

as the basis of ones self-esteem, while those of higher class people emphasize self-direction and

internal rewards (e.g., integrity). Thus, lower class people more often seek out economic capital

to gain social status and distinguish themselves. If unaccompanied by a certain degree of cultural

competence, however, this capital will never deliver the same prestige as cultural capital delivers

to the elite (Bourdieu, 1986).

Bourdieus emphasis on the distinction between the highbrow (art) culture of the elite

versus the lowbrow (popular [consumer]) culture of the masses has been criticized because it

cannot be identified as strongly in American society (Lamont and Lareau, 1988) and because

there is evidence that the contemporary elite is much more omnivorous in its cultural tastes,

embracing both highbrow and popular culture, while lower classes are more univorous in their

tastes (Peterson, 2005; Peterson and Kern, 1996). Despite these nuances to cultural capital theory,

however, the basic tenet that the elite embraces and benefits from having distinct and more

intellectual tastes still seems to stand (e.g., Prieur et al., 2008).

The digital revolution has further challenged cultural capital theory. While the elite was

generally regarded as more conservative and resistant with regard to electronic media

technologies associated with popular consumer culture (e.g., television, see Bourdieu, 1979

[1984]), recent studies show that new digital technologies are favored by, and significantly favor,

the elite. There is a persistent digital divide, for instance, both in terms of material access and in

terms of the purposes for which the Internet is used, with the elite adopting a more playful and

exploratory stance towards the Internet, while lower classes are restricted to an informational

orientationdescribed by Robinson (2009) as a taste for the necessary. Similarly, when

looking at the contents people produce on the Internet, Schradie (2011) finds that elite voices are

dominant in the digital realm. Compared to the Internet, the mobile phone has received little

scholarly attention as a cultural object. The above research indicates, however, that distinction

may also be played out through ones ownership and use of this new digital technology.

2.2. Mobile phones as desired consumer goods

The differential orientation of the elite versus lower classes to popular consumer culture has

been noticed among youth. Throughout the 20th century, lower class youths were consistently

found to involve themselves more in consumption-oriented youth cultures and lifestyles, while

middle-class youths were more involved in intellectualistic youth cultures and lifestyles (Brake,

1980; Coleman, 1961; Elkin and Westley, 1955; Hebdige, 1979). Despite the evolution towards

M. Vanden Abeele and K. Roe / Poetics 41 (2013) 265293 267

greater cultural omnivorism (Peterson and Kern, 1996) and more fluid, dispersed lifestyles

(cfr. neo-tribalism; Bennett, 1999; Maffesoli, 1996) around the turn of the millennium, social

class still consistently structures youths lifestyles. For example, underprivileged youths are

more attracted to popular consumer-oriented lifestyles (e.g., the bling-bling lifestyle) (e.g.,

Martin, 2009; McCulloch et al., 2006). For these youths, expensive consumer goods are a means

to gain and display ones status in the peer group (McCulloch et al., 2006).

Mobile phones can be identified as popular consumer goods that underprivileged youths may

acquire in order to gain peer rather than school social status, while higher class youths may resist

using the mobile phone as a status object as a display of counter-snobbery and ideological

resistance. For example, Pasquier (2005, in Prieur and Rosenlund, 2008) noted how Parisian

upper class girls refused to adopt a mobile phone.

The school system is a crucial structuring factor, determining adolescents (future) position in

society, while simultaneously reproducing existing social inequalities. As a result of this,

adolescents with more problematic experiences at school may be more likely to turn to the mobile

phone as a status object. To date, we know of only one study that (briefly) examined this idea:

Skog (2002) found thatat a time1 when mobile phone ownership was still comparatively low

adolescents with lower levels of academic self-esteem and lower educational aspirations were

significantly more likely to own a mobile phone. According to Skog, this finding suggested that

adolescents who did poorly in school sought compensation by using their mastery of mobile

phone technology as an alternative display of status in the peer group. Today, given the

widespread penetration of mobile phones among adolescents, mobile phone ownership no longer

carries such a potential for symbolic value.2 However, less successful pupils may still try to

enhance their image and status within the peer group by using mobile phones as a form of

conspicuous consumption (Veblen, 1899 [1979])e.g., by choosing a technically advanced

and/or expensive smart-phone.

3. The school system and the reproduction of social inequality

The school system plays an important role in shaping youths cultural practices through the

reproduction of social inequalityreproducing social inequality in two major ways. First,

pupils from higher social class backgrounds have been socialized into the cultural, academic and

social values and norms to which the school adheres and, thus, find it easier to assimilate to the

school environment (Bourdieu, 1979 [1984], 1986; Bourdieu and Passeron, 1977). Particularly in

school systems where students are grouped into ability-based tracks, this reproduction effect is

noticeable by the higher percentage of lower class youths in non-academic tracks (e.g., Oakes,

1987; Oakes and Guiton, 1995; Wielemans, 1991). In the Flemish school system, this

classification occurs rather explicitly through the division into three types of schools with a

corresponding social image in which different school tracks are offered to pupils: the academic

school tracks (accounting for 40% of pupils) focus on theory and general knowledge, the semi-

academic school tracks (accounting for 32% of pupils) are oriented towards a mix of theory and

practical skills, and the non-academic or vocational school tracks (accounting for 26% of pupils)

are oriented towards learning a particular trade; lower class youths are overrepresented in these


1 Skogs (2002) study took place in Norway in 1999.2 This is, at least, not the case for adolescents older than 12 years. In tweenhood and early adolescence (812 years old),

mobile phone ownership in itself is still regarded a status symbol (Martensen, 2007).

latter tracks (Goedeme and Verbist, 2007). The three different types of school tracks largely

correspond to a specific social standing in society (Wielemans, 1991): academic tracks are

considered the hardest and most prestigious, while semi-academic and vocational tracks are

considered easier and of lower social standing.3 Although envisioned as a compromise

between a comprehensive school that would grant all pupils equal opportunities and an

individualized school that would recognize differences in interests and capacities, in reality, the

Flemish school system thus reproduces social inequalities rather than dissolving them. Given that

the school system as a reproducer of social inequality is central to the study reported in this

article, our first hypothesis links social class background to Flemish youths grouping into school

tracks:

Hypothesis 1. Adolescents from lower class backgrounds are more likely to follow lower

school tracks than adolescents from higher class backgrounds (the first reproduction of

inequality hypothesis).

Closely intertwined with the school track system in Flemish schools is the common practice of

lagging behind: Flemish pupils are frequently forced to repeat a year when their results are

deemed insufficient. By the end of secondary education, more than one in three Flemish pupils is

lagging behind by at least one year (Goedeme and Verbist, 2007). Particularly relevant for the

current study is that lagging behind frequently occurs in combination with a (forced or voluntary)

drop to a lower school track: of the pupils obtaining their diploma in an academic track, only

15% lag behind one or more years, in comparison to 44% of those graduating in a semi-academic

track, and 58% graduating in a vocational track (Goedeme and Verbist, 2007). Well aware of the

social standing of different schools, many parents encourage their children to start in a school that

offers academic tracks, disregarding their interests or skills. When pupils fail, the school advises

or forces them to drop to an easier level, thereby adding to the lower standing of semi- and

non-academic tracks. This structure produces a waterfall mechanism of downward social

mobility within the school system (Goedeme and Verbist, 2007; Wielemans, 1991). The parental

tendency to enroll children in academic school tracks, in combination with lower class youths

being less adjusted to the social and cultural values and norms of the school environment (which

prevail particularly in academic tracks; cfr. Byrne, 1990), may make lower class youths more at

risk of lagging behind in the school system. Thus:

Hypothesis 2. Adolescents from lower class backgrounds are more likely to have lagged behind

in the school system than adolescents from higher class backgrounds (the second reproduction

of inequality hypothesis).

4. Conformity, compensation and resistance

4.1. Conformity

The school system not only reproduces social inequality through its selection of pupils on

the basis of their cultural capital, it also further develops cultural tastes among them. According

to Bourdieu and Passeron (Bourdieu, 1979 [1984]; Bourdieu and Passeron, 1977), cultural taste


3 The terms lower and higher reflect societys judgment of the social standing that corresponds to the three types

of school tracks; a value judgment that we, as authors, do not underwrite.

preferences for either highbrow or lowbrow (popular) culture continue to be acquired within

the school system. The schools allocation of status titles of success and failure hide a

mechanism of cultural capital distribution: when pupils receive their school certificate, they not

only receive a formal qualification of their academic competence, they are also implicitly

socialized into the social image that comes with the status position corresponding to this

qualification. The educational system thus implicitly teaches cultural practices, and youths

tastes can be regarded as a means of classifying themselves in the social space. Given that

higher class youths have an advantage over others when entering the school system, the

classification that takes place in the educational system amplifies the classification resulting

from ones upbringing (cultural reproduction) (Bourdieu, 1979 [1984]; 1989; Bourdieu and

Passeron, 1977; Roe, 1992). Additionally, DiMaggio (1982) found that adolescents cultural

participation during the high school years positively affects educational success (cultural

mobility). Later research by Aschaffenburg and Maas (1997) demonstrated that the cultural

capital provided by youths own cultural participation (particularly outside school) affects

educational success independently of the cultural capital acquired by ones upbringing. Both

the mechanisms of cultural reproduction and cultural mobility imply a strong relationship

between school success and adolescents involvement with more legitimate cultural practices.

Pupils who are successful in the school system conform to the social image that the school

promotes, and they internalize the cultural preferences belonging to this image into their self-

image (Bourdieu, 1979 [1984]).

While schools are no longer ignorant of the added value that popular culture can bring to the

classroom environment (e.g., Verboord and van Rees (2009) study on the use of popular versus

canonical literature in school textbooks), the school system, and academic school tracks in

particular, still celebrate high culture (e.g., Duncan-Andrade, 2004; Giroux and McLaren, 1989;

Giroux and Simon, 1988). In the Flemish schooling system, this translates into a greater affinity

with highbrow cultural preferences among pupils in academic tracks. The highbrow preferences

of the pupils in academic school tracks, then, reflect their cultural competence to recognize, read

and value certain cultural signals and to use these signals for social and cultural exclusion (Roe,

1992, 1995).

With respect to mobile phones, in contemporary society, they are regarded as forms of popular

rather than high culture (Gordon, 2002). Although initially designed and marketed as cutting

edge technologies for up-scale professionals (Katz and Sugiyama, 2005; Leung and Wei, 1999),

today they are seen as mass marketed consumer objects rather than aesthetic, exclusive artifacts

(Djelic and Ainamo, 2005). In the school context, teachers have been found to deem mobile

phones an unnecessary technology for young adolescents that causes social conflicts and

disturbances in the classroom (Mezei et al., 2007). Several schools have banned mobile phones

from the classroom or even the school premises (Ito, 2005; Lenhart et al., 2010). Given this, it is

likely that schools in the Flemish system will embed resistance to the mobile phone as a fashion

or status object into the social image that they pass on to their pupils. Pupils in academic tracks

who have more negative attitudes towards the mobile phone as a status symbol would thus be

conforming to the social image that the school transmits to them. As members of the cultural

elite, teachers in lower tracks will likely also reject mobile phone use, although they will

probably not reject it as strongly as teachers in higher tracks. Consequently, pupils in semi-

academic and vocational tracks conform to the social image that pertains to their school type

more strongly if they accept and value the mobile phone as a status object. These acts of

conformity can then be regarded as examples of adolescents anticipatory socialization

(Merton, 1957; see also Bourdieu, 1979 [1984] or Roe, 1992). Thus:


Hypothesis 3. Adolescents in lower school tracks have a more positive attitude towards the

mobile phone as a status object than adolescents in higher school tracks (the first conformi-

ty hypothesis).

Given the observation that lagging behind oftentimes occurs in combination with a drop to a

lower school track, we also expect to find an indirect relationship between lagging behind and

adolescents attitudes towards the mobile phone as a status object that is mediated by school

track.

Hypothesis 4. School track mediates the relationship between lagging behind and the impor-

tance attached to the mobile phone as a status object (the second conformity hypothesis).

4.2. Compensation

The conformity hypotheses examine whether there is evidence for an effect of adolescents

academic position on their attitude towards the mobile phone as a status object. We may also look

at adolescents individual reactions to their position and performance in the school system to

explain their attitudes towards the mobile phone. As argued above, pupils who are successful in

the schooling system are likely to display the (legitimate) cultural taste preferences that are

valued by the school (Bourdieu, 1979 [1984], 1986; Roe, 1995). When pupils perform poorly in

school, however, they are ascribed a negative identity of failure by the educational system

(Stinchcombe, 1964). Adolescents who are ascribed such a negative identity are often found to

involve themselves in deviant (sub-)cultural and sometimes even delinquent practices (Davies,

1999). Two (concurrent) hypotheses that are often put forward to explain these kinds of

involvement are, first, that adolescents may turn to these practices in an attempt to repair or

compensate for their damaged self-esteem, and, second, that they do so to express their resistance

against the school system and their sense of futility in it (Van Houtte and Stevens, 2008).

To cope with the threat to their self-esteem, unsuccessful pupils have been found to

compensate by involving themselves in media preferences that provide an alternative route to an

(oftentimes sub-cultural) identity with which they can achieve status within their peer group,

such as a preference for heavy metal music (Roe, 1987, 1992), heavy video game playing (Roe

and Muijs, 1998) or violent/pornographic VCR content (Roe, 1989). The same mechanism has

been found with respect to luxurious consumer goods. Research shows that people oftentimes

consume these as a compensatory response to their low self-esteem (e.g., Chang and Arkin, 2002;

Chaplin and John, 2007).

We may thus expect that having a cool or expensive mobile phone provides a means for

adolescents to compensate for the threat against their self-esteem that results from their

experience of school failure (the compensation hypothesis). We include two indicators of

school failure: lagging behind and adolescents academic self-concept. With respect to lagging

behind, previous studies have shown that it significantly damages pupils socio-emotional health

(e.g., Holmes and Matthews, 1984; Jimerson et al., 1997). Thus:

Hypothesis 5. Lagging behind predicts a more positive attitude towards the mobile phone as a

status object (the first compensation hypothesis).

Our second indicator concerns adolescents subjective experience of school failurei.e., their

academic self-concept. Academic self-concept is formed through social comparison with pupils

who are in the same frame of reference (Byrne, 1990), and it can be understood as the

adolescents (self-)perceived scholastic competence (Ireson and Hallam, 2009). It follows that:


Hypothesis 6. Adolescents with a lower academic self-concept have a more positive attitude

towards the mobile phone as a status object than adolescents with a higher academic self-concept

(the second compensation hypothesis).

Previous studies show that both being in a lower school track (e.g., Byrne, 1990; Ireson

and Hallam, 2009; Vanfossen et al., 1987) and lagging behind (e.g., Holmes and Matthews,

1984) negatively affect adolescents academic self-concept, as these students perceive their

scholastic competence as inferior to that of their (same-aged) peers. We thus expect academic

self-concept to mediate the relationship between school track and grade retention, on the

one hand, and adolescents attitude towards the mobile phone as a status object, on the

other:

Hypotheses 7/8. Adolescents in lower school tracks (H7)/who have lagged behind (H8) will

have a lower academic self-concept than adolescents in higher school tracks/who have not lagged

behind.

4.3. Resistance

As mentioned above, a concurrent hypothesis to the compensation hypothesis is the

resistance hypothesis, which posits that academically unsuccessful youths are not (only)

driven to involve themselves in (delinquent) youth cultures by the damage done to their self-

esteem, but also (and perhaps foremost) by their resistance to the school system (Van Houtte and

Stevens, 2008): youths who are in lower school tracks and/or youths who experience school

failure are likely to see no relationship between the schooling they receive and any positive

outcomes for them, resulting in a sense of futility (Van Houtte and Stevens, 2008) and a

general disengagement from the school system that is regarded as irrelevant for ones future

(Davies, 1994).

Resistance to the school system can be recognized in anti-school attitudes, which, in turn, find

expression in involvement with sub-cultures, consumer culture and/or disruptive/deviant

behaviors. Involvement in consumer/youth cultures and/or (media-)delinquency can then be

regarded as a shifted orientation from the irrelevant reward system of the school to other

reward systems (Coleman, 1960; Hagan, 2012; Staff and Kreager, 2008). Goldberg et al. (2003),

for example, found that young adolescents who disliked school had significantly stronger

materialistic attitudes. Roe (1992, 1995, 1997) found that adolescents who performed poorly in

school frequently had more negative attitudes towards school and that these attitudes, in turn,

predict the use of socially disvalued (or media delinquent) media with which status can be

obtained within the peer group. Similarly, Jenkins (1995) found that adolescents in lower school

tracks had a significantly lower school commitment, which in turn predicted misbehavior at

school.

These studies point out that anti-school attitudes may play an important role in explaining the

orientation of failed youths towards reward systems other than that of the school. We expect

that adolescents attitudes towards the school will mediate the relationship between the indicators

of school failure and the attitude towards the mobile phone as a fashion object. Thus,

Hypothesis 9. The attitude towards school will negatively predict adolescents attitude towardsthe mobile phone as a status object (the resistance hypothesis).

Hypotheses 10/11/12. Adolescents school track (H10)/lagging behind (H11)/and academic

self-concept (H12) will predict the attitude towards school.


5. Smartphones as high-status goods

Finally, previous studies point out that most teens consider cool mobile phones to be

expensive and sophisticated. The type and the price of a mobile phone are considered to be

important status-signaling features (Fortunati, 2005; Katz and Sugiyama, 2005; Skog, 2002;

Wilska, 2003). Therefore, we expect that adolescents who believe that having a cool mobile

phone is important will also be more likely to have an expensive and sophisticated one. This

implies that:

Hypothesis 13. Adolescents attitude towards the mobile phone as a status object positively

predicts ownership of a more expensive and sophisticated mobile phone.

This last hypothesis also implies that we expect attitude towards the mobile phone as a status

object to mediate the relationship between the school variables in our model and smartphone

ownership.

The above hypotheses and research question are graphically depicted in a theoretical model

(see Fig. 1). As parental SES might be a confounding variable explaining both school experience

variables, on the one hand, and the attitude towards and ownership of a high status mobile phone,

on the other, direct paths between parental SES and each of these variables were added to the

theoretical model. Additionally, we added direct paths from parental SES, school track, lagging

behind, academic self-concept and attitude towards school to smartphone ownership, so as to

examine whether, and to what extent, the attitude towards the mobile phone as a status object

mediates these relationships.

6. The moderating role of gender, age and ethnicity

Previous research has shown that gender affects almost all the parameters in our model. For

example, educational attainment has been found to be higher among girls (Dekkers et al., 2000;

Baye et al., 2005). Moreover, during adolescence, females have been found to have more positive

attitudes towards school (Jenkins, 1995) and to attach less importance to having a cool mobile

phone (Wilska, 2003). Hence, we include gender as a control variable. Gender may also moderate

the relationships postulated in our model. School failure is considered more stressful for males,

who are socialized to be performance oriented, than for females, who are socialized more towards

achievements in the interpersonal domain (Kirk, 2009). Preference for more socially disvalued

media in response to school failure has therefore been identified as occurring more extensively

among adolescent males (Roe and Jarlbro, 1998). Moreover, Skog (2002) suggested that the

relationship between (academic) self-esteem and having a mobile phone found in her study was

particularly strong for males, because of its potential for emphasizing their mastery of this

technology. This hypothesis is in line with insights on the gender divide in technology use

(Broos, 2005; Kirk, 2009). Hence, we may expect that the relationship between adolescents

experience of school failure and the importance they attach to having a cool mobile phone will be

stronger for male than for female adolescents.

Previous research also suggests that the mobile phone as a status object is most important for

younger adolescents (Ling and Helmersen, 2000; Martensen, 2007). Younger adolescents tend to

be more concerned about conforming to peer group norms (Berndt, 1979; Sumter et al., 2009)

and having the right mobile phone is likely to be such a norm (Caronia and Caron, 2004; Ling

and Yttri, 2006). Age is thus included as a control variable in this study. We also see reason to

include age as a moderator variable. Lagging behind and/or dropping to a lower school track is


M.

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27

4

H3

H4SES

School track

Lagging

behind

H1

H2

H6

H8

H5

H12

H10

H11H9

p13

Academic

Self-concept

Attitu de towards MP as a status ob ject

High-end

MP

Price

Type

Positiv e attitude towards school

H7

Fig. 1. Theoretical model of the postulated relationships between adolescents experiences of school failure, their attitudes towards the mobile phone as a status object, and their

ownership of a high-status mobile phone.

likely to be more detrimental in the lives of younger adolescents, as lagging behind is less

common in the earlier years of secondary school (Goedeme and Verbist, 2007). Consequently,

the relationship between the experience of school failure and the importance of having a cool

mobile phone may be stronger for young adolescents.

Finally, we also include ethnicity as a control and a moderator variable. To date, little is known

about the mobile phones place in the lives of ethnic minority youths. Soenen and Baes (2011)

suggest that minority youths attach great importance to the mobile phone as a fashion article and

status object. This finding conforms with existing studies on ethnic minorities conspicuous

consumption patterns (Charles et al., 2009; Lamont and Molnar, 2001), and it indicates that

ethnicity may be a useful control variable for our study. Ethnicity may also moderate some of the

relationships in our model; indeed, for ethnic minority youths, the negative label of school

failure is likely to be more detrimental than for majority youths, as it cumulates with the

existing label of ethnic minority.

In order to test the aforementioned hypotheses and the (moderating) role of gender, age and

ethnicity, we make use of structural equation modeling, a technique making it possible to

examine multiple relationships simultaneously by comparing how well empirical data fit with

a pre-postulated theoretical model, while comparing the strength of relationships between groups

(Arbuckle, 2005).

7. Method

7.1. Procedure

During the autumn of 2010, a large-scale survey study was carried out among 13 high schools in

the 5 provinces of Flanders, Belgium. Schools were selected by means of a random stratified

sampling procedure. Of the 24 schools that were contacted, 9 agreed to participate. In four schools,

questionnaires were administered to all the pupils of the school. In five schools, questionnaires were

administered to a random set of classes that happened to have individual study hours during the data

collection period. The (anonymous) questionnaires were administered to the adolescents in their

classroom in the presence of at least two researchers. The sample composition was closely

monitored. By the end of the data collection period, two gaps in the sample (academic tracks and

1st grade pupils were underrepresented) were addressed by means of purposive sampling in four

additional schools, whereby additional questionnaires were gathered only among classes (with

study hours) that fit these criteria (see Table A1 in the Appendix). This procedure resulted in a total

sample of 1952 pupils that came from 13 different schools and 30 different classrooms. Forty-four

pupils (2%) were recruited from a school of arts. Given the somewhat different orientation and

social image of this type of schooling, these pupils were excluded from the analyses. Nine

questionnaires were removed from the sample (e.g., when less than half of the questionnaire was

completed, when the same response was given on each question). The final sample included in the

analyses thus consisted of 1899 pupils, a sample that is representative in terms of gender (51.1%

males), age (M = 15.31 years, SD = 1.87) and school track (see below) for the population of high

school pupils in Flanders.

7.2. Measures

The exogenous variables in our model are gender, age, ethnicity and the socio-economic status

of the parents, as indicated by their educational and occupational position.


Gender was coded as 1 for male, 2 for female respondents. Age was calculated by

subtracting the date of birth from the date on which each questionnaire was administered.

Because proficiency in the ethnic language is conducive to ethnic minorities psychological

adaptation (Vedder, 2005), we chose to ask respondents for the languages spoken at home (Dutch,

French or Other [If Other, specify]); respondents were asked to check all boxes that applied to

them. For our analyses, we differentiated between adolescents who indicated speaking Western-

European language(s) at home (ethnic majority youths) and those who (also or exclusively)

indicated speaking a non-Western-European language(s) at home (ethnic minority youths). In

total, 7.6% (N = 145) of our sample indicated speaking a non-Western-European language at

home.

Parental educational status was indicated by the highest obtained qualification of the

respondents father and mother (primary school, secondary school, higher education). For

occupational level, the respondents were asked in an open-ended question to describe as

thoroughly as possible the jobs held by their parents. Each occupation was classified as a low,

middle or high class profession with the aid of the classification system of the International Labor

Association (ISCO-08). As expected, a close relationship was observed between parental

educational and occupational status. To avoid problems of multi-collinearity, a compound SES-

variable was constructed by first standardizing each measure, and then calculating the average of

these four Z-scores. It should be noted that several respondents had difficulty in reporting the

educational and/or occupational level of their parents: for only 1397 respondents (74% of the

total sample) the SES-score was based on the parental and occupational level of both parents. For

the other respondents, the variable is based on either the parental, either the occupational level of

one or both parents. For 66 pupils, a missing value for the SES-score was replaced with the series

mean.4 This procedure enabled us to retain the total sample, and had little impact on the

relationships in the model.

The intermediary endogenous variables in our model are:

Respondents school track, coded 1 for vocational tracks, 2 for semi-academic and 3 foracademic school tracks. Almost half (41.6%) of the respondents were in an academic track,

34.4% in a semi-academic track, and 24% in a non-academic or vocational track.

Lagging behind, indicating the number of school years that the adolescent is lagging behindin high school (0 = none, 1 = one year, 2 = two years or more). Sixteen per cent (15.6%)

reported having lagged behind one year in high school and 2.6% reported two years or more.

Academic self-concept was measured by three items from the Academic Self-Conceptsubscale of Marshs (1992) Self-Description Questionnaire II: I get bad marks in most school

subjects; I learn things quickly in most school subjects; and I am good at most school

subjects. Negatively worded items were reversed (a = .65). Response categories ranged from

1 (completely disagree) to 6 (completely agree). On average, the respondents had a positive

perception of their own scholastic competence (M = 4.22, SD = .95).

Adolescents attitude towards school was indicated by four items from Roe and Muijs(1998) school commitment scale: Most of the times, I am bored at school; I like going to

school; School is usually boring; and I would rather not go to school. The negatively


4 These missing values were not randomly distributed; 9.5% of pupils in vocational tracks failed to provide any

information in parental education or occupation, compared to only 1.8%, resp. 1.4% of the pupils in semi-academic, resp.

academic tracks (X2(2) = 63.89, p < .000).

worded item of this subscale was reversed so that high scores correspond with a more positive

attitude towards school (a = .80). Response categories ranged from 1 (completely disagree) to

4 (completely agree). On average, the respondents reported a moderately negative attitude

towards school (M = 2.38, SD = .66).

Attitude towards the mobile phone as a status object was measured using six items derivedfrom Martensen (2007): It is important to have a cool phone; Its important to have a

mobile phone that has the latest features; My mobile doesnt have to be expensive or cool

but reliable (reverse scored); I am very interested in mobile phones with the latest features;

A good mobile phone is always expensive; and A cool or expensive mobile phone is like a

status symbol to me. The response categories range from 1 (completely disagree) to 4

(completely agree). The Cronbach alpha for the scale was satisfactory (a = .79).

Finally, the last endogenous variable in our model, ownership of a high status mobile

phone, is a latent variable constructed by two manifest variables. The respondents were asked to

indicate the type of mobile phone they currently useda phone without multimedia features

(value 1), a phone with basic multimedia features (value 2) or a smartphone (Iphone, Blackberry,

. . .) (value 3)and to indicate the cost of their current phone by means of an open-endedquestion.

7.3. Preliminary analyses

Descriptive analyses were conducted with SPSS Statistics 19.0. Given our multistage

sampling procedure, our observations may be nested in meaningful social groups at the class and

school level. This nesting potentially violates the assumption of independence. Not accounting

for multilevel structures in the dataset may lead to parameter estimates that are over-valued in

terms of their contribution to the outcome variable (Hox, 2010). Therefore, we first estimated

general linear mixed models in SPSS Statistics 19.0, so as to examine potential classroom and

school-level variability in the two main variables of interestnamely, adolescents attitude

towards and their ownership of a high status mobile phone. With regard to ownership of a high

status mobile phone, after entering all predictor variables as fixed effects into the equation, no

significant variability was found at the school level (N = 13, s2between :00, SE = .00, Z = 0.00,pone-sided = 1.00, ICC = .00) or at the classroom level (N = 30, s

2between :00, SE = .01, Z = 0.57,

pone-sided = .14, ICC = .01). With regard to adolescents attitude towards having a high status

mobile phone, no significant variability was found at the school level (N = 13, s2between :01,SE = .01, Z = 0.75, pone-sided = .11, ICC = .02). The classroom level, on the other hand, was found

to account for 6% of the variability in attitudinal scores (N = 30, s2between :01, SE = .01,Z = 2.33, pone-sided < .01, ICC = .06). Although the latter intraclass correlation is consideredsmall in the literature (Hox, 2010), we wish to draw the readers attention to this clustering at the

classroom level.

The models were tested using AMOS 19.0. The evaluation of the fit of a model is based on a

number of goodness-of-fit indices. The X2-square statistic is the only measure with an

associated significance test; however, as the X2-statistic is known to inflate when large samples

are used, Joreskog and Sorbom (1993) advise evaluating the X2/df ratio. For large samples, a

X2/df ratio smaller than 3.0 is considered a good or acceptable model fit. A second fit index

commonly used is the Root Mean Square Error of Approximation (RMSEA). An RMSEA-value

below .05 is considered a close fit, a value between .05 and .08 an acceptable fit, a value

between .08 and .10 a mediocre fit and a value above .10 an unacceptable fit


(Diamantopoulos and Siguaw, 2000; Schermelleh-Engel et al., 2003). A third fit index that we

report is the Comparative Fit Index (CFI), with a CFI-value above .95 indicating a good fit and

a value above .90 an acceptable fit (Kelloway, 1998). Both the CFI and RMSEA are relatively

unaffected by sample size (Schermelleh-Engel et al., 2003).

8. Results

8.1. Descriptive statistics and correlations

Table 1 presents the correlations between the variables in our study. The experience of school

failure variables were all significantly related to one another (r > j.07j, p < .01; see Table 1).Boys were significantly more likely to have already lagged behind than girls. Presumably

partially as a result of their lagging behind, boys were also more likely to be in a semi-academic

(40.1% versus 30.3%) or non-academic school track (23.6% versus 21.1%; X2(2) = 29.50,

p < .000), and they expressed more negative attitudes towards school. Age related to each of thethree variables measuring school success/failure, but it did not relate to teens attitude towards

school. Over half of ethnic minority respondents (55.3%) were in a vocational track, compared to

only 20.2% of ethnic majority youths (X2(2) = 75.72, p < .000). No relationship was foundbetween ethnicity and lagging behind, academic self-concept or attitude towards school.

With respect to teens attitude towards the mobile phone as a status object, on average, the

respondents reported attaching little importance to having a cool mobile phone (M = 2.15 [scale

mean = 2.5], SD = 0.59). Seventy-six per cent owned a mobile phone with basic multi-media

functions, followed by 18.1% who owned a smartphone, and 5.6% whose phone lacked any

multimedia feature. The mean price of adolescents mobile phone was 139.80 euro

(SD = 103.88). As expected, the price of a mobile phone and its type were strongly related

(r = .48, p < .000; see Table 1).A small gender difference was found with respect to the importance attached to having a

cool mobile phone, with boys attaching greater importance to this than girls (r = .06,p = .015). Boys (M = 147.34, SD = 119.24) reported having more expensive mobile phones than

girls (M = 132.05, SD = 84.64; t(1632.71) = 3.13, p < .01). With respect to age, youngeradolescents were found to attach greater importance to having a cool mobile phone (r = .23,p < .000), while older teens were found to have significantly more expensive mobile phones(r = .10, p < .000). Age did not affect the type of mobile phone. Finally, ethnic minority youthsshared more positive attitudes towards the mobile phone as a status object (r = .12, p < .000),were more likely to have a more sophisticated (r = .11, p < .000) and a more expensive mobilephone (r = .10, p < .000).

8.2. Structural equation models

8.2.1. Test of hypothesized relationships

Before examining the fit of the structural model, the fit of the measurement models for the

latent variables were examined to assess whether the measured variables represent uni-

dimensional factor structures. The fit indices and factor loadings of individual items for each

measurement model are listed in Table A2 of the Appendix. The models showed acceptable

model fit. Next, we fitted the theoretical model as presented in Fig. 1. The model fit the data

reasonably well (X2 (150) = 501.72, p = .000, X2/df = 3.35, CFI = .96, RMSEA = .04). Following

Aish and Joreskog (1990), insignificant paths were removed. This trimmed model provided a


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Table 1

Correlation table.

1 2 3 4 5 6 7 8 9 10 11

1 Gender (male = 1, female = 2) 1

2 Age .06** 13 School track (1 = vocational) .09*** .14*** 14 Years lagging behind .19*** .43*** .23*** 15 SES .17*** .03 .34*** .03 16 Ethnicity (0 = majority, 1 = minority) .02 .08*** .18*** .04 .20*** 17 Academic self-concept .03 .05* .10*** .07** .03 .00 18 Positive attitude school .17*** .02 .14*** .10*** .03 .00 .23*** 19 Attitude MP status object .06* .23*** .13*** .07** .10*** .12*** .07** .12*** 1

10 Type of mobile phone (1 = basic phone) .00 .02 .08** .02 .06** .11*** .01 .04 .30*** 111 Price of mobile phone .07** .10*** .07** .09*** .03 .10*** .02 .06** .33*** .48*** 1

* p < .05.** p < .01.

*** p < .001.

reasonable fit, but did not fit significantly better than the original model (X2(166) = (520.31,

p = .000, X2/df = 3.13, CFI = .96, RMSEA = .03).

Fig. 2 shows the standardized beta weights for the (statistically significant) parameter

estimates; for reasons of clarity, the significant beta weights and correlation coefficients of the

relationships between the control variables and the variables were not depicted in this figure but

can be found in Table 2. Several of our hypotheses were supported. Parental SES was a strong

predictor of school track (b = .33, p < .000; H1 supported), and it was a weak, yet significantpredictor of lagging behind (b = .06, p < .000; H2 supported). Both conformity hypotheseswere also supported: not only did school track significantly predict adolescents attitude towards

the mobile phone as a status object (b = .12, p < .000; H3 supported), lagging behind was alsoindirectly related to this attitude by predicting adolescents school track (b = .15, p < .000; H4supported). A mediation test of this indirect relationship revealed it to be significant, albeit weak

(b = .02, SE = .01, p = .01).

Our compensation hypotheses were not supported by the model: neither lagging behind nor

academic self-concept significantly predicted adolescents attitude towards the mobile phone as a

status object5 (H5 and H6 not supported). While school track significantly predicted academic self-

concept (b = .11, p < .000; H7 supported), no relationship was found for lagging behind (H8 notsupported). The resistance hypothesis was supported, however: adolescents with a more negative

attitude towards school attached significantly greater importance to having a cool mobile phone

(b = .14, p < .000; H9 supported). We also see that school track (b = .08, p < .05), laggingbehind (b = .06, p < .05) and particularly academic self-concept (b = .27, p < .000) predictadolescents attitude towards school (H10, H11 and H12 supported). The mediating role of

adolescents attitude towards school was significant both for school track (b = .01, SE = .00,p = .01), lagging behind (b = .01, SE = .01, p = .01) and for academic self-concept (b = .03,SE = .01, p < .00). In total, the school failure indicators in our model together with gender, ageand ethnicity explained 13% of the variance in adolescents attitude towards the mobile phone as a

status object. The strongest predictor of smartphone ownership was adolescents attitude towards

the mobile phone as a status object (b = .53, p < .000; H13 supported), which explained 29% of itsvariance (together with gender, age and ethnicity). None of the other school variables, nor parental

SES, predicted smartphone ownership. Finally, parental SES directly predicted adolescents

attitude towards the mobile phone as a status object (b = .06, p < .05).Gender, age and ethnicity were included in the theoretical model as direct predictors of each of

the endogenous variablesand as correlates of parental SES and of each other. Only parameter

estimates that revealed significant associations were retained in the final trimmed model. These

are reported in Table 2. Boys were significantly more likely to have lagged behind, to be in a

lower school track, and to have a less positive attitude towards school. Boys had more positive

attitudes towards the mobile phone as a status object (b = .07, p < .05). Age strongly predictedlagging behind and also significantly predicted the school track of the adolescent.6 Older


5 As the latter lack of direct relationships may be attributable to a full mediation effect of attitude towards school, we re-

estimated our model, leaving out attitude towards school. The fit of this revised model was good (see Figure A1 in the

Appendix). When examining the parameters of this revised model, we now found a significant relationship between

academic self-concept and adolescents attitude towards the mobile phone as a status object (b = .06, p = .05). Laggingbehind was still not a direct predictor, however.

6 Age thus predicts school track, even when controlling for the relationship between age and lagging behind (and, thus,

the waterfall effect). This relation may be attributed to the sampling procedure, as more higher grade classes were

sampled in vocational tracks (r = .05, p < .05).

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R = .19

R = .21

R = .02

R = .12

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-.1 2** *

-.1 5** *SES

School track

Lagging

behind

.33** *

-.0 6*

.11** *

.27** *

.08*

-.0 6*-.1 4** *

.53** *

-.0 6*Academic Self-conc ept

High-end

MP

Price

Type

-.77** *

-.62** *Attitu de

towards MP as

a status ob ject

Positiv e attitude towards s chool

Fig. 2. Structural equation model of the postulated relationships between adolescents experiences of school failure, their attitudes towards the mobile phone as a status object, and

their ownership of a high-status mobile phone (X2(166) = (520.31, p = .000, X2/df = 3.13, CFI = .96, RMSEA = .03). Note: For clarity, relationships with control variables (gender,

age, ethnicity) are not depicted in this figure, but reported in Table 2.

adolescents reported having a lower academic self-concept. Younger adolescents were

significantly more likely to have a positive attitude towards the mobile phone as a status

object (b = .27, p < .000), yet were significantly less likely to own a smartphone (b = .23,p < .000). Finally, the results for our third control variable, ethnicity, indicate that ethnicminority youths were significantly more likely to have lagged behind, to follow a lower school

track, to have more positive attitudes towards the mobile phone as a status object (b = .08,

p < .05) and to be more likely to own a smartphone (b = .09, p < .05).

8.2.2. The moderating role of gender, age and ethnicity

In order to explore possible differences in the pattern of relationships according to gender, age

or ethnicitymultiple-group analyses of our initial model were carried out (see Table 3). For

each of the moderators, we first estimated the full theoretical model (including the remaining

control variables) and then trimmed this model by removing insignificant paths. Next, we

assessed measurement invariance by examining whether constraining the measurement weights

of the latent variables and the structural weights in the model across groups significantly altered

the fit of the trimmed models. In the case of gender, measurement invariance was supported.

Hence, the analysis was performed on the model in which measurement weights were

constrained to be equal. In the case of age and ethnicity, measurement invariance was not

supported. Here, multi-group analyses were performed on the trimmed models.


Table 2

Regression weights, standard errors and standardized regression weights of gender, age and ethnicity.

Unstandardized estimate SE Standardized estimate

Regression weights

Lagging behind Gender .16 .02 .17***Lagging behind Age .11 .01 .42***Lagging behind Ethnicity .11 .04 .06**School track Gender .19 .03 .12***School track Ethnicity .35 .06 .12***School track Age .04 .01 .09***Academic self-concept Age .03 .01 .06*Attitude towards school Gender .18 .03 .17***Attitude towards school Age .01 .01 .05Attitude MP status object Gender .07 .03 .07*Attitude MP status object Age .07 .01 .27***Attitude MP status object Ethnicity .15 .05 .08**High-status mobile phone Age .09 .01 .23***High-status mobile phone Ethnicity .27 .08 .09***Correlations

Parental SES $Gender .07 .01 .17***Parental SES $Ethnicity .04 .01 .20***Gender $Age .05 .02 .06**Ethnicity $Age .04 .01 .07**

Note: The current table reports only significant parameter estimates of control variables in relation to other variables as

obtained in the final fitted model.* p < .05.

** p < .01.*** p < .001. p = .07.

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Table 3

Moderator effects for gender, age and ethnicity.

Gender Age Ethnicity

bmale N = 970 bfemale N = 929 Z byoung N = 948 bold N = 951 Z bmajor N = 1754 bminor N = 145 Z

Lagging behind Parental SES .1*** .00 2.9** .06 .09** 1.76 .05* .12 .91School track Lagging behind .18*** .11*** .14 .04 .26*** 2.25* .19*** .13 3.48***School track Parental SES .27*** .38*** 2.25* .38*** .27*** 2.23* .36*** .05 3.86***Academic SC School track .15*** .1** .91 .15*** .07 1.4 .12*** .02 2.15*Academic SC Lagging behind / / / .02 .09* .54 .09** .14 2.59**Attitude school School track .06 .09** .45 .07* .1** .75 .08** .11 .27Attitude school Lagging behind .1* .02 .85 / / / / / /Attitude school Academic SC .27*** .27*** .38 .25*** .29*** 1.15 .28*** .25* 1.11Attitude MP Attitude School .1** .19*** 1.82 .22*** .06 3.08** .15*** .15 2.07*Attitude MP School track .12** .12** .21 .08* .14*** 1.13 .14*** .01 1.06Attitude MP Lagging behind / / / .01 .12** 1.65 / / /Attitude MP Parental SES .02 .08* .98 .1** .01 1.55 / / /Attitude MP Academic SC / / / / / / .02 .39** 2.76**High status MP Attitude MP .56*** .50*** 3.63*** .46*** .56*** 4.67*** .53*** .39*** .77High status MP Lagging behind / / / .10* .06 1.13 / / /High status MP Parental SES / / / / / / .01 .22** 2.74**Lagging behind Ethnicity .05 .11*** .49 .07* .07* 1.44 / / /School track Ethnicity .1** .14*** .95 .08** .15*** 2.25* / / /Attitude MP Ethnicity .07* .09* .13 .06 .12*** 1.76 / / /High status MP Ethnicity .09** .12** .24 .07 .13*** 2.62** / / /Lagging behind Age .50*** .32*** 9.05*** / / / .42*** .45*** .89School track Age .12*** .06* 1.15 / / / .07** .28** 2.32*Attitude School Age .07 .01 1.26 / / / .04 .23* 2.76**Attitude MP Age .29*** .25*** 1.06 / / / .28*** .11 .99High status MP Age .26*** .18*** 2.91** / / / .22*** .32*** 2.06*Lagging behind Gender / / / .10** .26*** 6.04*** .17*** .12 .37School track Gender / / / .11*** .13*** .31 .13*** .01 1.28Attitude school Gender / / / .16*** .19*** .79 .18*** .11 .56Attitude MP Gender / / / .04 .11** 1.12 .06* .08 .41Model fit indices

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4Table 3 (Continued )

Gender Age Ethnicity

bmale N = 970 bfemale N = 929 Z byoung N = 948 bold N = 951 Z bmajor N = 1754 bminor N = 145 Z

Theoretical model X2(279) = 624.90, p < .000 CFI = .96;

RMSEA = .03

X2(279) = 698.41, p < .000 CFI = .95;

RMSEA = .03

X2(279) = 633.78, p < .000 CFI = .96;

RMSEA = .03

Trimmed model (insignificant paths

removed)

X2(308) = 648.70, p < .000 CFI = .96;

RMSEA = .02

X2(304) = 720.60, p < .000 CFI = .95;

RMSEA = .03

X2(304) = 655.64, p < .000 CFI = .96;

RMSEA = .03

Nested model: measurement weights

constrained

X2(319) = 663.74, p < .000 CFI = .96;

RMSEA = .02

X2(315) = 741.80, p < .000 CFI = .95;

RMSEA = .03

X2(315) = 691.56, p < .000 CFI = .96,

RMSEA = .03

Nested model: regression weights

constrained

X2(339) = 786.77, p < .000 CFI = .95;

RMSEA = .03

X2(335) = 848.07, p < .000 CFI = .94;

RMSEA = .03

X2(336) = 755.86, p < .000 CFI = .95,

RMSEA = .03

* p < .05.** p < .01.

*** p < .001.

The multiple-group analysis for gender resulted in an acceptable fit (model with constrained

measurement weights: X2(319) = 663.74, p < .000; CFI = .96; RMSEA = .02). To assess whetherparameter estimates for boys might be significantly different from those for girls, the critical

ratios for differences between the two models parameters were examined. This analysis revealed

interesting differences (see Table 3). Two concern the reproduction of social inequality: while

boys from lower socio-economic backgrounds were significantly more likely to have lagged

behind than girls, girls from lower socio-economic backgrounds were significantly more likely to

follow a semi-academic or vocational school track. The relationship between attitude towards the

mobile phone as a status object and ownership of a high status mobile phone was significantly

stronger for boys (b = .56) than for girls (b = .50).

The multiple group analysis comparing younger (15.31 years) and older adolescentsresulted in a good fit (X2(304) = 720.60, p < .000, CFI = .95, RMSEA = .03). The relationshipbetween attitude towards school and attitude towards the mobile phone as a status object was

significantly stronger among younger adolescents. Older adolescents with a more positive

attitude towards the mobile phone as a status object, on the other hand, were significantly more

likely to own a smartphone.

Finally, with regard to ethnicity, the trimmed model achieved a good fit (X2(304) = 655.64,

p < .000; CFI = .96; RMSEA = .03). Given the small sample size of the ethnic minority youthgroup, few of the parameters in the minority model reached significance. Nonetheless, interesting

differences can be found between majority and minority youths. Among ethnic minority youths,

adolescents with positive attitudes towards the school system also had more positive attitudes

towards the mobile phone as a status object. The compensation hypothesis was partially

supported among minority youths: academic self-concept (b = .39, p < .05) significantlypredicted these youths attitude towards the mobile phone as a status object. While parental SES

did not predict ownership of a high status mobile phone among ethnic majority youths, a

significant positive relationship was found in the group of ethnic minority youths (b = .22,

p < .000).

9. Discussion

The purpose of this article was to examine the relationship between adolescents position in

the school system and their attitude towards the mobile phone as a status objectwith particular

focus on the mediating role of academic self-concept and school attitude, and on the moderating

role of gender, age and ethnicity.

A first set of hypotheses examined, concerned the schools role in the reproduction of social

inequality. Confirming earlier studies, we found that lower class youths were overrepresented in

lower school tracks and that they were more likely to have lagged behind during their high school

years. Interestingly, we found an outspoken gender difference here: while the relationship

between class background and school track was much stronger for girls, the relationship between

class background and lagging behind was significantly stronger for boys. A tentative explanation

for these findings may be that parents and/or educators apply gender-stereotypical norms for boys

and girls with respect to their performance in the school system: while academic performance is

downplayed for girls (for lower class girls, in particular), thereby encouraging them to already

begin their high school career in a lower school track, it is over-emphasized for boys, forcing

them to begin high school in an academic track whatever their academic interests and/or

competency. The result of this double standard in the school system is likely to be detrimental

for both, as girls chances for upward social mobility are minimized, while boys are at a greater


risk for the frustrating experiencing of downward social mobility (and all the undesirable

consequences associated with it) (Van Houtte, 2005). The school system thus not only reproduces

inequality in terms of social class background, but also in terms of gender inequality.

The major focus of this chapter, however, was on the relationship between adolescents

experiences in the school system and their attitude towards the mobile phone as a status object.

Three concurrent hypotheses were postulated: conformity, compensation and resistance.

The conformity hypothesis postulated that, in the Flemish school system, adolescents would

conform to the social image that the school bestows on themnamely, acceptance of the mobile

phone in lower levels of schooling (and resistance in higher levels of schooling). The conformity

hypothesis found support: adolescents in semi-academic and, particularly, vocational tracks

attached greater importance to having a cool mobile phone than adolescents in academic

school tracks. Moreover, lagging behind also indirectly predicted these attitudes. This finding

supports the idea that the track system in Flemish high schools brings forth certain expectations

with regard to adolescents social image and that visible material objects such as the mobile

phone are a part of that image. The indirect relationship with lagging behind points towards

anticipatory socialization of youths who drop to a lower level as a result of their lagging

behind. To further validate the conformity hypothesis, however, future research may need to

focus on school policies on and teachers attitudes towards mobile phones. This could inform us

about whether and how schools implicitly and explicitly teach critical resistance to the mobile

phone as a consumer good.

Our second and third set of hypotheses concerned the idea of compensation for the damage

that school failure brings to self-esteem and the idea of resistance against the irrelevance of the

school as a reward system. Our results failed to support the compensation hypothesis (neither

lagging behind nor academic self-concept were directly related to adolescents attitudes towards

the mobile phone as a status object), while the resistance hypothesis gained strong support. When

excluding adolescents attitude towards school from our original model, however, we found

support for the compensation hypothesis, with academic self-concept negatively predicting

attitudes towards the mobile phone as a status object. This finding suggests that compensation

may explain some of the relationship, but that school failure serves mostly as an antecedent to

anti-school attitudeswhich, in turn, predict more positive attitudes towards the mobile phone as

a status object. This causal chain is in agreement with what Van Houtte and Stevens (2008)

found in their study on youth delinquency, and it suggests that youths will attempt to remedy the

damage to their self-esteem by developing resistance against the school and the reward system

for which it stands. By adopting cultural values and symbols that the school rejects, but that are

strongly valued in the peer group, these pupils attempt to develop an alternative identity that is

rewarded by the status mechanism of the peer group, namely popularity.

With regard to gender, our finding that boys have more positive attitudes towards the mobile

phone as a status object is congruent with gender stereotypes, in that boys typically have a greater

desire to display their masculinity through their technological mastery (Kirk, 2009; Skog,

2002; Wilska, 2003). Overall, however, little difference was found in the impact of boys and

girls experiences of school failure on their attitude towards the mobile phone as a status object.

With regard to age, we found not only that younger adolescents attached significantly greater

importance to the mobile phone as a status object, but also that these attitudes were more strongly

predicted by their attitude towards school (resistance) and by their academic self-concept

(compensation). In line with earlier (qualitative) research (e.g., Green, 2003), our findings thus

suggest that it is particularly during early and mid-adolescence that having a cool mobile phone

matters as a means to gain status in the peer group. Older adolescents with a positive attitude


towards the mobile phone as a status object, on the other hand, were significantly more likely to

own a high-status mobile phone, which is likely due to their higher expenditure.

Finally, with respect to ethnicity, a striking difference between majority and minority youths is

the direct negative relationship between academic self-concept and ethnic minority youths

attitude towards the mobile phone as a status object (compensation), while a positive

relationship was found between attitude towards school and attitude towards the mobile phone as

a status object (thus, rejecting the resistance hypothesis). Moreover, parental SES was found to

directly and positively predict ethnic minority youths smartphone ownership. The latter finding

may indicate that, while high status mobile phones are no longer an adequate object of distinction

for majority youths from higher parental SES, they may still serve this function within the ethnic

minority subgroup. Additional research among this particular group that takes into account the

intersectionality between ethnicity, SES and gender is necessary to further clarify these

patterns of relationships.

In conclusion, the results presented in this article can be seen as providing further evidence for

Bourdieus (1979 [1984]) claim that, independent of adolescents social origin, the educational

system determines cultural practices by manipulating the pupils self-image through ascribing

identities of success or failure to them. Although the status signaling features of the mobile phone

cannot be considered culturally deviant in the same sense as, for example, heavy metal music

or violent or pornographic media contents, our findings indicate that the mechanisms expressed

in Bourdieus cultural capital theory are also relevant for popular cultural artifacts, such as the

mobile phone.

The current study documents youths attitudes towards and their ownership of a smartphone in

a time of flux. In 2010, the year in which our data were collected, mobile phones were still

becoming commonplace; smartphone ownership was out of reach for most youths. Today,

however, smartphones have become the standard among youths, with 81% of them owning such a

phone in Flanders according to the most recent figures. Given that the media landscape is

currently undergoing fundamental changesas we witness the convergence of almost all media

forms into a multitude of personal mobile devices such as mobile phones, tablets and

notebooksa pertinent question, then, is whether our results are not already outdated. The

continuous advances in technology do not make research on youths use of them obsolete,

however. On the contrary, answering questions with regard to how and why adolescents choose

and use particular media technologies within their personal identity projects enables us to better

understand not only how youths deal with their position in society and the developmental

changes they undergo, but also the features of these technologies and how they enable and

constrain human action. It is clear from the current study, for instance, that the personalness of

mobile devices (see also Campbell and Park, 2008) attracts youths to incorporate these objects

into their social image.

Our results are relevant to the ongoing debate over the theoretical bases of Bourdieus cultural

capital theory. Three of the major criticisms of this theory have been (1) that an ongoing process

of individualization renders class differences irrelevant, (2) that even when lifestyle differences

are found between social classes, differences in life styles no longer serve as a means for social

exclusion or symbolic dominance, and (3) that highbrow culture has lost its significance

(Prieur et al., 2008). With regard to the first criticism, the findings from our study make clear that

the preference for a fairly functional object such as the mobile phone is not merely an individuals

choice: adolescents preferences were linked to their performance in school, and thereby to their

social class background. Social class background and the educational system are thus still

powerful determinants of peoples cultural practices.


The results of this study also strongly argue against the second criticism that any cultural

differences found do not reflect symbolic dominance. That the elitedespite their financial

resources, and in line with what the educational system deems appropriate for themprefers a

more modest mobile phone can convincingly be interpreted as a rejection of an element of

popular consumer culture. Conversely, adolescents who experience lower social standing will

seek out popular culture as a means to conform to, compensate for, and sometimes even resist, the

social position that the school, and society at large, assigns them.

The third criticismthat cultural capital theory overly emphasizes highbrow culture, while in

reality todays elite tends to be rather omnivorous in its cultural consumption (Peterson and Kern,

1996)can also be recognized in our results. The mobile phone is not totally rejected by the

elite, but ways are sought through which distinction can still be achieved. Prieur et al. (2008, p.

53) mention in this regard that the character of the most valued cultural forms is changing.

Among these changes is a decreasing value attributed to classical compared to scientific culture.

Bourdieu (1979 [1984], p. 6) originally referred to elitist taste as the primacy of forms over

function. Given that new media technologies are instrumental objects that leave little room for

intellectual refinement in terms of the materiality of the device, we appear to be witnessing a

reversal of function over form, whereby the elite differentiates itself by the ways in which they

are used (e.g., Robinson, 2009); in the case of the mobile phone, then, the elite may proclaim only

to need the technology to arrange their everyday lives. Indirect support for this idea can be

found in a number of recent studies that point towards time poverty (e.g., Jackel and

Wollscheid, 2007) and voraciousness (a high frequency of leisure participation in a range of

activities; e.g., Sullivan and Katz-Gerro, 2007) as new ways in which the elite differentiates itself

in contemporary society. The harriedness of everyday life, then, acts as a status symbol of the

elite, which can be displayed by the frequent use of ones mobile phone to make the necessary

arrangements to support this life.

While this study offers valuable insights into how adolescents experiences in the school

system structure their attitudes and use of the mobile phone as a status object, some limitations

should be acknowledged. First, we need to point out the temporal and cultural specificity of this

study. With respect to temporal specificity, smartphone ownership appears to have risen

dramatically among Flemish teenagers over the past few years, and the dividing line between a

smartphone and a regular mobile phone with multimedia features is gradually dissolving.

The question thus arises whether the findings of this study can still be replicated today, and/or

whether distinction is reflected in other aspects of mobile phone use (e.g., having access to

mobile internet and/or a tablet PC). Additionally, we also need to take into account the fact that

the mobile phone is just one feature among a wide range of potential status objects such as

clothing and music. Future research is needed in order to clarify to what extent particular mobile

phone preferences and practices occur in combination with other status markers that demarcate

boundaries between social reference groups among youth. In addition, it remains to be seen

whether, and to what extent, the status oriented uses of new media technologies such as the

mobile phone replace older displays of compensation and resistance (such as involvement in

visible subcultures and preference for socially disvalued music types) or whether these use

patterns are merely incorporated alongside them.

Cultural specificity may also be at stake. What is considered the standard of good taste can

vary from one culture to the other. Given the differential uptake of mobile phone technology

across the world, it is possible that in other cultures, particularly in the South, mobile phones

themselves are still considered cutting-edge technologies with which the elite achieves

distinction, although Peterson (2005) remarks that cultural standards tend to spread across


geographical boundaries before atrophying. Cultural specificity is certainly also at play with

respect to the Flemish school systemwithin which the waterfall mechanism, for example, is

deemed typical (Goedeme and Verbist, 2007).

An important limitation of this study is the selection and operationalization of measures. The

large number of missing values for parents educational and occupational level is unfortunate,

particularly given that these missing values were not randomly distributed in our sample.

Ethnicity is a complex and multi-dimensional concept, hence a measure that consists of multiple

questions rather than a single-item on the languages spoken at home is advisable (Burton et al.,

2010). With respect to adolescents attitude towards school, a more specific measure of sense of

futility could have provided a better insight into resistance motives.

Finally, we only included parental education level as a measure of adolescents cultural capital

in our questionnaire, thereby not asking respondents about other important markers of cultural

capital such as parental cultural participation and/or the cultural participation of youths

themselves. DiMaggios (1982) study on cultural mobility and subsequent studies (e.g.,

Aschaffenburg and Maas, 1997) on this matter have shown that adolescents cultural

participation is a consistent and even better predictor of educational attainment than parental

cultural participation. The evidence in support of cultural mobility may point towards a historical

shift, where cultural participation now provides resources for children from less privileged

backgrounds with which they can gain access to more privileged societal positions. In the light of

the findings of the current study, it remains to be seen, however, whether certain kinds of

involvement with new media technologies such as the mobile phone may present new avenues for

cultural participation, and, as a result of that, for cultural mobility.

Appendix A. Supplementary material

Supplementary material associated with this article can be found, in the online version, at

http://dx.doi.org/10.1016/j.poetic.2013.03.001.

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