On your own within a network? Vulnerable youths’ social networks in transition from school to adult life

Abstract

This article is based on longitudinal prospective life-course data (1995–2007) about Special Educational Need (SEN) students in upper secondary school, addressing changes in these vulnerable persons’ (N=372) spare time-related social relationships at age 29 compared to five years earlier. Logistic regression analyses show that experiences of exclusion (being solely in special class) during upper secondary school have a marked negative effect on being in a small and potentially isolating social network at age 24 compared with the variables personal diagnostic characteristics and experienced psychosocial stress in the family. Applying the same explanatory model to the adaptive situation at age 29 reveals very different results: time distant variables (special class, personal characteristics at school start) loose effect. Contemporary independent variables describing a contextually changed life situation produces patterns of social integration, reducing social marginalization. The results suggest that a shift in the life situation in adulthood (having work, own family, driver's license) changes network characteristics and agency from being self-realising and individualistic towards a more collective, altruistic and self-sacrificing action pattern in social relationships. This shows a pattern of resilience. Theoretic approaches are life-course theory, theory of frame conditions, network theory, theory of disability and critical realism.

Keywords:

• vulnerable youth
• life-course transitions
• effects of attending special class
• social network
• logistic regression analysis

Notes

1. Totally, thirteen categories of disabilities/difficulties were identified (also used by Skårbrevik 1996), but restricted to the four mentioned in the present study. The other nine categories were sight, hearing, moving disabilities, motor coordination, speech/articulation, reading and writing disabilities, dyscalculia, concentration difficulties and medical problems.

2. In our model, in the logistic regression analysis, this is given the variable value 0, related to small networks. The second variable value is 1, related to large networks.

3. Myklebust, et al. (2012).

4. For a quick overview, see also Figure 1.

5. See the end note 1.

6. The results of an intensive analysis of qualitative data are reported in Kvalsund et al. (1998; Kvalsund 1999, 2004a, 2002).

7. This includes both having own children and living together with children.

8. For females (age 24) with intellectual disabilities, the probability of not becoming a member of a network comprised solely of young adults at the same age was 4.6-fold greater than for those without. For males with language and communication difficulties or psycho-social difficulties at the beginning of upper secondary school, there was a 4.6-fold greater chance of not being in a spontaneously formed network in early adult life.

9. For a unified perspective on theory of contemporary society, see Aakvaag (2008).