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Who excludes? Young People’s Experience of Social Exclusion

Published online by Cambridge University Press:  24 February 2022

GERRY REDMOND
Affiliation:
College of Business, Government and Law, Flinders University email: gerry.redmond@flinders.edu.au
GILL MAIN
Affiliation:
School of Education, University of Leeds
ALEXANDER W. O’DONNELL
Affiliation:
School of Psychological Sciences, University of Tasmania, Launceston
JENNIFER SKATTEBOL
Affiliation:
Social Policy Research Centre, University of New South Wales, email: cm.thomson@unsw.edu.au
RICHARD WOODMAN
Affiliation:
College of Medicine and Public Health, Flinders University
ANNA MOONEY
Affiliation:
Faculty of Medicine, Health and Human Sciences, Macquarie University
JOANNA WANG
Affiliation:
School of Mathematical and Physical Sciences, University of Technology, Sydney
SABERA TURKMANI
Affiliation:
University of Technology, Sydney
CATHERINE THOMSON
Affiliation:
Social Policy Research Centre, University of New South Wales, email: cm.thomson@unsw.edu.au
FIONA BROOKS
Affiliation:
Auckland University of Technology, New Zealand
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Abstract

Existing policy research has not comprehensively examined the processes by which young people experience social exclusion: that is, the relationships among different risk factors for exclusion, their actual experiences of exclusion, and outcomes that matter for their life chances. Drawing on data from a survey of Australian 13-14 year olds (N=3,535), this paper adapts the Bristol Social Exclusion Matrix to examine pathways from young people’s personal and family resources, their experience of participation (school engagement; bullying victimization; teacher support), and their life satisfaction – a predictive indicator of wellbeing and mental health in adulthood. The effects of other characteristics or risk factors for young people’s social exclusion (living with disability, being a young carer, identifying as Indigenous, and speaking a language other than English at home), are also examined. This paper shows that experience of exclusion mediates the relationship between young people’s personal and family resources and life satisfaction. Controlling for characteristics or risk factors does not change this relationship, suggesting that processes of social exclusion, enacted in interpersonal encounters, are driven by overarching structural factors. These findings are relevant for policy in Australia, and in other countries with similar policy regimes.

Type
Article
Creative Commons
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press

1. Introduction

After a brief heyday in the first decade of this century, the social exclusion paradigm is no longer used in liberal welfare regimes such as Australia as an organizing framework for social policy design. Nonetheless, academic research – for example, by Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007) – has proposed social exclusion frameworks that not only focus on relative disadvantage, but also on processes through which people experience disadvantage, and outcomes associated with these processes. Issues of process give rise to the questions of who (or what) excludes, by what processes and how social and policy factors facilitate these processes (Atkinson, Reference Atkinson, Atkinson and Hills1998; Popay, Reference Popay2010).

We argue in this paper that the question of ‘who excludes?’ is especially important for the understanding of young people’s experiences of social exclusion. As Ridge (2002) eloquently shows, their experiences need to be understood in the context of their position as ‘dependent’, but also as agents who engage across multiple settings: at home, in the community, and especially at school. The ‘who excludes’ we consider, therefore, refers not only to individuals, but also to ‘weaknesses in the social infrastructure’ (Commission of the European Communities, 1993, p. 1), which form the context of social exclusion. In this paper, we aim to show that these weaknesses are evident in the Australian school system, which like many school systems in rich countries, is now infused with neoliberal marketised approaches that foreground accountability at the level of the school and the individual teacher, and responsibility at the level of the student and their family. There is currently little consistent evidence on the processes through which risks for exclusion are transmitted through acts of exclusion to outcomes that matter for both policy and young people’s life chances (Ermisch et al., Reference Ermisch, Jantti and Smeeding2012). In this context, risks for exclusion can be defined as characteristics or states that may be attached to individual young people, or the households they live in. Acts of exclusion can be seen as comprising young people’s own experiences, suggesting the need to directly engage with young people as expert informants on their lives.

In this paper, we use the Bristol Social Exclusion Matrix (B-SEM), developed by Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007), as the basis for our analysis of pathways from resources, through lived experience in education settings, to outcomes that matter for young people’s life chances, and for policy. Using a national survey of Australian adolescents, we explore relationships between material disadvantage, experiences of social exclusion, and life satisfaction – an important outcome for wellbeing in the present and future life chances. We control for recognised risk factors for social exclusion in the Australian context – being with disability, a young carer, Indigenous, or from an ethnic minority. While the experiences we examine relate to school, our aim is to provide a theoretical pathway between social exclusion at the micro level and wider structural factors that drive young people’s experiences of exclusion, and to consider policy approaches to addressing structural factors, as well as more immediate experiences of exclusion.

2. Social exclusion

2.1. Social exclusion in policy discourse

Social exclusion was originally used in the early 1970s by the French political advisor René Lenoir as a blanket term for those who lacked economic resources and the citizenship rights associated with social protection. The concept of social exclusion, and its antonym, social inclusion, are currently used both by UN agencies (United Nations, 2016) and the European Union (http://ec.europa.eu/social/main.jsp?catId=751) as a framework for monitoring and analysing inequality and disadvantage. However, the term is now not widely used in policy discourses in ‘liberal’ welfare regimes such as Australia. When it was more widely used in the first decade of this century (see Australian Government, 2009), ‘social inclusion’, similar to in the UK, was broadly interpreted in enacted social policy as promotion of paid employment (Deeming and Smyth, Reference Deeming and Smyth2015; Saunders, 2013).

The focus on employment and on individual responsibility or ‘self-reliance’ (Australian Government, 2009), driven by often paternalistic policy interventions (Taylor et al., Reference Taylor, Gray and Stanton2016), is an ongoing theme in social policy discourses that long predate the social inclusion agenda. This is also notable in schooling systems that privilege parental choice, especially for those who can afford it (Keddie, Reference Keddie2017). In common with other English-speaking OECD countries, Australian social policy is characterised by a weak ‘social investment’ approach (Deeming and Smyth, Reference Deeming and Smyth2015) that has combined minimalist means-tested welfare with limited policies since the early 2000s that aim to reduce inequities in educational outcomes, expand access to preschool education and tertiary education, close the gap in educational, health and employment outcomes between Indigenous and non-Indigenous Australians, expand funding for disability services, and provide (limited) bursaries to young carers to support their education.

There is little evidence that this policy mix has reduced inequities among children and young people in Australia. Child poverty rates are about average by OECD standards and similar to those in the UK and New Zealand, but have not declined substantially since the turn of the century (Davidson et al., Reference Davidson, Saunders, Bradbury and Wong2020). Inequality in educational outcomes is high by international standards (UNICEF Office of Research, 2018), and gaps in learning achievement between those in the highest and lowest SES quartiles have not narrowed since 2000, while gaps in learning achievement between Indigenous and non-Indigenous 15 year olds have only slightly narrowed (Crato and Thomson, Reference Crato and Thomson2020). Emerson and Llewellyn (Reference Emerson and Llewellyn2014) show that inequalities between young adults with and without disability on a wide range of health and wellbeing measures have not diminished since 2000. Evidence also suggests that young carers experience considerable disadvantage compared with non-carers with respect to both school engagement and wellbeing (Hamilton and Redmond, Reference Hamilton and Redmond2020; Warren and Edwards, Reference Warren and Edwards2017). On the other hand, while some research shows that migrant students perform better academically than non-migrant students (OECD, 2019), other research suggests that young Australians from diverse ethnic backgrounds experience high levels of poverty, as well as racism, discrimination and bullying which in turn are associated with increased risks of mental health problems (Katz and Redmond, Reference Katz and Redmond2010; Priest et al., Reference Priest, Kavanagh, Bécares and King2019).

2.2. Academic discourse on social exclusion

While there is little agreement on precise definitions of social exclusion in academic discourse, there is broad concurrence on three core elements: multidimensionality (covering risks, assets and outcomes across a range of dimensions); relativity (focusing on comparison between ‘the excluded’ and ‘the average’ or as gradations of exclusion); and process (the dynamic nature of exclusion, expressed through institutional and social relationships, which can have an intergenerational character) (Atkinson, Reference Atkinson, Atkinson and Hills1998; Popay, Reference Popay2010). While intergenerational risk features strongly in policy debates, it is often pathologised in terms of risks for intergenerational welfare receipt (Bubonya and Cobb-Clark, Reference Bubonya and Cobb-Clark2021). The issue of process on the other hand has been notably absent from national policy discourse in Australia, and in most liberal welfare regimes (Redmond, Reference Redmond2015).

Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007) propose the following process-oriented definition of social exclusion:

Social exclusion is a complex and multi-dimensional process. It involves the lack or denial of resources, rights, goods and services, and the inability to participate in the normal relationships and activities, available to the majority of people in a society, whether in economic, social, cultural or political arenas. It affects both the quality of life of individuals and the equity and cohesion of society as a whole. (Levitas et al., Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007, p.9)

In Levitas et al.’s concept, denial of resources is an important element in social exclusion. It implies a process by which structures, and the agents who are acting within these, orchestrate or secure a person’s (or group’s) exclusion. The second key element in the above definition is inability to participate – being prevented from doing something that one wants to do, and that most people achieve without difficulty. People may adapt their expectations to suit their circumstances, and these adaptive responses are commonly revealed in research with children and young people (Ridge, 2002; Skattebol et al., Reference Skattebol, Saunders, Redmond, Bedford and Cass2012). However, Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007) also introduce a third element in their definition – quality of life – that seeks to capture concrete impacts of non-participation on individuals who experience exclusion, as well as impacts on social cohesion more broadly. Therefore, even if expectations are adapted and a person does not overtly state that they have been excluded, negative effects on quality of life may be observable. Implicit in the model is a pathway from multifaceted risk factors for exclusion to non-participation among individuals, which in turn is associated with negative quality of life outcomes related to health, wellbeing, and life chances. Figure 1 shows that the three elements of resources, participation and quality of life comprise the overarching domains of the B-SEM proposed by Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007), within which numerous sub-domains are situated.

Figure 1. Model of pathways for social exclusion from risk factors to outcomes as proposed by Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007)

2.3. Application to children and young people

In policy discourse, social exclusion is commonly seen as associated with ‘adult’ or family-level risk factors such as low income or household joblessness. The concept of social exclusion has been applied to children and young people in somewhat arbitrary ways, with children most commonly seen as members of households or families that experience exclusion (Gross-Manos, Reference Gross-Manos2015), or are subject to poor parenting skills (Levitas, Reference Levitas2004). Such an approach cannot differentiate young people according to their individual characteristics or provide an adequate account of their participation or quality of life. Qualitative research (see for example Ridge, 2002) provides a rich account of how poverty experienced by young people was associated with exclusion in school and community settings. More recently, Gross-Manos (Reference Gross-Manos2015) used survey data to identify three dimensions of exclusion as they impacted on twelve year-olds in Israel: area and services, school, and participation in social activities (based on children’s reports of their satisfaction with these life domains), with young people’s perceptions of how they are treated by doctors, teachers and peers among the items included. She found that children who she identified as materially deprived and socially excluded were less satisfied with their health, more worried about things, more likely to be bullied and less satisfied with family relationships. They also reported lower subjective wellbeing (Gross-Manos, Reference Gross-Manos2015; Gross-Manos and Ben-Arieh, Reference Gross-Manos and Ben-Arieh2017).

In another study of the subjective well-being of twelve year-olds in 16 countries, Crous and Bradshaw (Reference Crous and Bradshaw2017) operationalised the B-SEM to measure young people’s satisfaction with seven dimensions of life within three domains: resources (material resources, social resources, and access to services), participation, and quality of life (health and wellbeing, housing and local environment, social harm). While they found considerable international variation in satisfaction across the three domains, they also found that across all countries, social participation was the strongest predictor of satisfaction in the other domains. This led them to conclude that: “material deprivation is not a good proxy for other aspects of child social exclusion” (p.136).

Figures 2 and 3 show how Gross-Manos (Reference Gross-Manos2015) and Crous and Bradshaw (Reference Crous and Bradshaw2017) respectively theorise associations among the different domains in their models. Gross-Manos theorises exclusion as the average of a range of feelings of satisfaction with the area children live in, their school, and indicators of participation. She theorises assault, being left out, safety and satisfaction with health as correlates of social exclusion or material deprivation, while characteristics of gender, religion and country of birth are used as categories or risk factors for the analysis of exclusion. Crous and Bradshaw on the other hand focus on overlaps between domains (resources, participation and quality of life), with country the main characteristic variable for comparing children. However, neither study explicitly theorises pathways between resources, participation and outcomes. Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007) propose that ‘estimating or tracking social exclusion depends on the prior understanding of the causal relationship between domains’ (p.118), taking account of ‘risk factors’ such as ethnicity in analysis of social exclusion. And while they do not propose any specific causal pathways, they do argue that ‘income, poverty and material deprivation constitute a driver for most other domains of exclusion’ (pp.120-1).

Figure 2. Model of pathways for social exclusion from risk factors to outcomes as proposed by Gross-Manos (Reference Gross-Manos2015)

Figure 3. Model of pathways for social exclusion from risk factors to outcomes as proposed by Crous and Bradshaw (Reference Crous and Bradshaw2017)

Understandings of social exclusion in the social psychology literature largely eschew material disadvantage as a contributory factor, and focus instead on experience of interpersonal and intergroup exclusion (Killen et al., Reference Killen, Mulvey and Hitti2013). Many young people themselves discuss exclusion in interpersonal terms (Redmond et al., Reference Lietz, O’Grady, Tobin, Murphy, Macaskill, Redmond and Thomson2016; Ridge, 2002; Skattebol et al., Reference Skattebol, Saunders, Redmond, Bedford and Cass2012). While the quantitative analyses by Gross-Manos (Reference Gross-Manos2015) and Crous and Bradshaw (Reference Crous and Bradshaw2017) mostly focus on satisfaction, the present study aims to focus more directly on young people’s experiences of exclusion in a school setting.

3. Data and method

3.1. Conceptual approach

In the present analysis, consistent with the B-SEM framework which places considerable emphasis on material disadvantage as a key factor in social exclusion, a pathway from resources, through participation to quality of life was theorised (Figure 4). This pathway was hypothesised to be significant, even when young people’s characteristics (disability, young carer, Indigenous, ethnically diverse background) were taken into account. From a policy perspective (and in the B-SEM framework), these characteristics are different from resource issues. Elimination of poverty – for example, through resource transfers – is a legitimate policy objective; however, policy objectives with respect to characteristics such as disability, ethnicity or carer status are to act on attitudes, environments and practices that disable, discriminate or disadvantage (e.g. see with respect to disability: O’Grady et al., Reference O’Grady, Pleasence, Balmer, Buck and Genn2004). Resources (indicators of low family affluence and a young person’s personal deprivation) were hypothesised to be associated with experiences of exclusion: participation at school (proxied by an indicator of school engagement), and social interaction at school (proxied by indicators of teacher support and bullying by peers). These in turn were theorised to be associated with quality-of-life outcomes. Experiences of participation were therefore expected to at least partially mediate the relationship between resources on the one hand, and quality of life on the other. Note that although a clear pathway from risks and resources, through participation leading to quality of life, was hypothesised, causal directions could only be theorised, not empirically tested.

Figure 4. Model of pathways for social exclusion from risk factors to outcomes as operationalised in this analysis

Evidence exists for most of the associations proposed in Figure 4. For example, not having the possessions and resources that other children value was shown to be associated with low subjective wellbeing (Main and Bradshaw, Reference Main and Bradshaw2012); experience of bullying was negatively associated with young people’s school engagement, health and wellbeing (García-Moya et al., Reference García-Moya, Brooks, Morgan and Moreno2015; Rothon et al., 2011); and characteristics of living with disability, being a young carer or living in a low income household were positively associated with experience of bullying (Redmond et al., Reference Lietz, O’Grady, Tobin, Murphy, Macaskill, Redmond and Thomson2016). What the present study adds is an analysis of the extent to which participation mediates the relationship between low family affluence and young people’s personal material disadvantage on the one hand, and their quality of life on the other, taking into account identification as being with disability, or being a young carer, Indigenous or ethnically diverse.

3.2. Survey data

Data were drawn from a survey conducted as part of the Australian Child Wellbeing Project (www.australianchildwellbeing.com.au). The survey instrument was developed following direct consultations with 97 young people on what contributes to a ‘good life’. Most of these young people came from marginalised backgrounds, and included groups of Indigenous young people, young people with learning difficulties, young people from ethnically diverse backgrounds, young people living in remote Australia, and young people in out-of-home care. Their reflections helped shape the dimensions of a ‘good life’ included in the instrument, as well as the issues covered within each dimension. Following a field trial, a multi-stage stratified probability sample (states/territories, sectors and schools) was used to arrive at a nationally representative sample of students in Years 4, 6 and 8 (approximately, 9-10, 11-12 and 13-14 years old). Active parental and student consent were required for students to participate. The survey was administered online, took approximately 20-30 minutes to complete, and could be completed over any number of sessions. Audio functionalities were available for students with reading difficulties (Lietz et al., Reference Lietz, O’Grady, Tobin, Murphy, Macaskill, Redmond and Thomson2016). Ethics approval was obtained from university human research ethics committees, from Australian state and territory education departments, and from Catholic diocesan school authorities.

The final sample comprised 5,440 valid student responses from 180 state, Catholic and independent schools in every state and territory in Australia (data can be downloaded from the Australian Data Archive - doi:10.26193/MGM2TM). This represents a response rate of 38% among schools, and 33% among students in participating schools (Redmond et al., Reference Lietz, O’Grady, Tobin, Murphy, Macaskill, Redmond and Thomson2016). The present analysis is restricted to 13-14- year-olds as the survey instrument administered to this group contained some items that were not included in the instruments administered to younger people.

3.3. Measures

Latent indicators of school engagement, teacher support, bullying and life satisfaction were derived using Item Response Theory (IRT) methodology from multiple survey items, with five plausible values derived for each latent indicator and with missing data imputed (Lietz et al., Reference Lietz, O’Grady, Tobin, Murphy, Macaskill, Redmond and Thomson2016). School engagement is acknowledged as important for learning and positive educational outcomes (Fredricks et al., Reference Fredricks, Blumenfeld and Paris2004, p. 61). It was captured in this analysis with a satisfaction with school scale that aimed to capture emotional engagement in school. This scale was derived from a longer validated ‘engagement with school’ scale (Gemici and Lu, Reference Gemici and Lu2014) and contained six items: ‘My school is a place where: I feel happy; I really like to go to each day; I find that learning is a lot of fun; I feel safe and secure; I like learning; I get enjoyment from being there’. Responses ranged from 0 (strongly disagree) to 3 (strongly agree), with some data missing for 2.2% of observations prior to the application of IRT. This scale had high reliability (α=0.90; factor loadings = 0.63 to 0.82).

Teacher support was captured from three items: ‘At my school, there is a teacher or another adult: who really cares about me; who believes that I will be a success; who listens to me when I have something to say’ (Constantine and Bernard, Reference Constantine and Bernard2001). Responses ranged from 0 (Not at all true) to 4 (Very much true), with missing data for 1.5% of observations, α=0.84 and factor loadings = 0.75 to 0.80.

For Covert Bullying, students were asked to select the frequency with which they had experienced each of the following six events: ‘Students deliberately ignored or left me out of a group to hurt me’, ‘I was teased in nasty ways’, ‘I had a student tell lies about me behind my back, to make other students not like me’, ‘I’ve been made to feel afraid I would get hurt’, ‘I had secrets told about me to others behind my back, to hurt me’, and ‘a group decided to hurt me by ganging up on me’ (Cross et al., Reference Cross, Shaw, Hearn, Epstein, Monks, Lester and Thomas2009). Frequency could be selected from one of five options: (1) ‘this did not happen to me’, (2) once or twice this term, (3) every few weeks this term, (4) about once a week this term, (5) several times a week or more. Prior to application of IRT, 2.4% of observations had missing data for at least one of these responses with α=0.90 and factor loadings = 0.74 to 0.83.

Life satisfaction, an indicator of subjective wellbeing, was measured using a five item scale developed by Huebner (Reference Huebner1991), adjusted by Rees et al. (2010). Respondents were asked to rate the following statements on a five point scale from 1 (strongly disagree) to 5 (strongly agree): My life is going well; My life is just right; I wish I had a different kind of life (reversed in the calculation of the scale); I have a good life; I have what I want in life (missing data for 1.8% of observations; α=0.84; factor loadings = 0.57 to 0.82).

The Family Affluence Scale (FAS) indicator was used to identify the level of affluence in young people’s households. The scale was derived from responses to six questions which are used together in the international Health Behaviour in School Aged Children survey to derive the FAS, as a proxy for socioeconomic status in surveys of young people: how many cars the participant’s family owned (0, 1, 2 or more); whether the participant had their own bedroom (0 or 1); how many times they travelled away on holiday with their family in the past year (0, 1, 2, 3 or more); how many computers the family owned (0, 1, 2, 3 or more); whether there was a dishwasher in the home (0 or 1); number of bathrooms in the home (0, 1, 2, 3 or more) (Torsheim et al., 2016). These indicators were aggregated to a score in the range 0-13; young people with a score of 0-7 were defined as materially deprived (n=476).

In order to capture young people’s personal experience of deprivation, a number of items were included in the ACWP survey on personal possessions and resources, drawn from Main and Bradshaw (Reference Main and Bradshaw2014), and validated in qualitative research with Australian young people during the ACWP survey development phase (Redmond et al., Reference Lietz, O’Grady, Tobin, Murphy, Macaskill, Redmond and Thomson2016). Respondents were asked, ‘Here is a list of items that some young people of your age have. Please tell us whether you have each item on the list or whether you’d like to have it’: Some money that you can save each month, either in a bank or at home; The right kind of clothes to fit in with other people your age; An iPod or music player; Your own mobile phone; and My family has enough money for me to go on a school camp. In the Australian context, most schools have an annual school camp program for students in Years 4-9. Parents are expected to contribute towards the cost of the school camp; in some cases, schools subsidise these costs for disadvantaged students. Exploratory factor analysis suggested that the indicators on school camp, clothes, pocket money, mobile phone, and iPod could be aggregated into a single factor (eigenvalue=1.76). While the Cronbach Alpha for this latent factor was low (α=0.48), it had good predictive validity in terms of its relationship with the Family Affluence Scale. Over half of the respondents (n=1,932) reported not being deprived on any item while 6% (n=225) reported being deprived on three or more items.

Indicators of characteristics or risk factors for exclusion were captured by manifest survey variables. Young people with disability (n=364) self-identified through responses to items asking whether they had a disability and whether their disability made it hard for them to, or stopped them engaging in, one or more activities that other young people engaged in (Clark et al., Reference Clark, Fleming, Bullen, Denny, Crengle, Dyson and Utter2013). Young people were identified as carers if they reported having a family member with disability, mental illness or drug/alcohol addiction, and also reported that they provided care for this person (n=319). Young people were also able to self-identify as Indigenous (n=119), or as speaking a language other than English at home (n=249). Some young people identified as being in more than one ‘at risk’ group. Three quarters of respondents (n=2,633) did not identify as being in any of these groups. It is worth noting that the small size of the Indigenous sample is associated with wide confidence intervals in several of the results presented.

While missing values were imputed for each of the latent indicators used in the analysis, missing values for remaining items were not imputed. Nine percent of the full sample of 13–14-year-olds was dropped from the analysis, giving a final analysis sample of 3,535.

3.4. Analytical approach

Descriptive analysis was conducted using Stata 16.0. The framework proposed in Figure 4 was applied with a saturated path model in MPlus 8.0 (Muthén and Muthén, Reference Muthén and Muthén2017), allowing analysis of pathways between resources and quality of life outcomes. All analyses were conducted on weighted data to improve representativeness with respect to gender, average socioeconomic status of the school and region (analysis on unweighted data showed broadly similar results). Standard errors were tested with bootstrapping (1,000 replications).

Following the estimation of the full path model, indirect effects were computed using the Delta approach (MacKinnon, Reference MacKinnon2008). Total effects reflect the relationship between both family affluence and child deprivation with life satisfaction, irrespective of the participation indicators. Total indirect effects determined whether the relationship between the two indicators of resources and life satisfaction was at least partially mediated by the three participation indicators. Specific indirect effects explicated the processes from resources to quality-of-life outcomes by examining the mediating effects of school engagement, teacher support, and bullying separately. Total and indirect effects were also calculated for the characteristics or risk factors included in the model (with disability, carer, Indigenous, language background other than English).

4. Results

Table 1 shows mean values of the school satisfaction, teacher support, bullying, and life satisfaction scale scores by family affluence and child deprivation score. The Table shows that young people in low affluence families reported significantly lower levels of teacher support and life satisfaction compared with young people in medium and high affluence families. The Table also shows that bullying increased with child deprivation, while teacher support, school satisfaction and life satisfaction all decreased (although differences in school satisfaction were not statistically significant). Table 2 shows that young people with disability reported significantly higher levels of bullying, and lower levels of school satisfaction and teacher support than young people who were not in any of the marginalised groups. Measures of bullying were also significantly higher for young carers. Average measures of life satisfaction were significantly lower for young people in all four marginalised groups compared with young people who were not in any marginalised group. Table 3 shows that young people in all four marginalised groups were significantly more likely than young people not in any marginalised group to be living in a low affluence family, and more likely to have a child deprivation score of three or more, although 95% confidence intervals for Indigenous young people are wide, and therefore differences are not statistically significant.

TABLE 1. Average scores on bullying, teacher support, school satisfaction and life satisfaction scales, by affluence and deprivation status (means)

Note: 95% confidence intervals in square parentheses. Asterisks denote significance of difference between means with (1) medium/high and low family affluence; and (2) means with a child deprivation score of 0 and with a child deprivation score of 1-3+. *** p<.001; ** p <.01; * p<.05.

TABLE 2. Average scores on bullying, teacher support, school satisfaction and life satisfaction scales, by marginalisation status (means)

Note: 95% confidence intervals in square parentheses. Asterisks denote significance of difference between proportions in marginalised groups and proportions not in any of these groups. *** p<.001; ** p <.01; * p<.05.

TABLE 3. Affluence and deprivation status, by marginalisation status (proportions)

Note: 95% confidence intervals in square parentheses. Asterisks denote significance of difference between proportions in marginalised groups and proportions not in any of these groups. *** p<.001; ** p <.01; * p<.05.

Table 4 shows coefficients from the path model, indicating the relationship between resources and characteristics, indicators of participation and quality of life for young people. Relationships between school engagement, teacher support and bullying on the one hand, and life satisfaction on the other, were all relatively strong and significant. The relationship between living in a low affluence family and teacher support was also significant, as was the relationship between child deprivation, teacher support and bullying. Neither of the material disadvantage indicators was significantly associated with school engagement. However, both material disadvantage indicators were significantly associated with life satisfaction. Among the characteristics/risks, disability was significantly associated with school engagement, teacher support, bullying and life satisfaction. Young carer was marginally associated with bullying and significantly associated with life satisfaction. Language background other than English was marginally associated with Life satisfaction.

TABLE 4. Standardised Path coefficients from resources and risk factors to life satisfaction

Note: N=3,535. Path model was estimated using maximum likelihood with robust standard errors. Results shown are for clustered model (100 schools with Year 8 students). Covariances are not shown: School engagement with Teacher support: 0.391, p<.001; School engagement with Bullying -0.148, p<.001; Teacher support with Bullying -0.089, p=.010.

Mediation analyses (Table 5) revealed a significant total effect of low family affluence on life satisfaction. This overall effect was partially mediated by the participation indicators, especially teacher support. The total effect of child deprivation on life satisfaction was partially mediated by teacher support and bullying. In sum, the mediating participation indicators of school engagement, teacher support and bullying explain about a third of the total association between family affluence and life satisfaction, and about a quarter of the association between child deprivation and life satisfaction.

TABLE 5. Standardized Total and indirect effects from resources and risk factors to life satisfaction

Table 5 also shows that for young people with disability, total and indirect effects were large and significant, with indirect effects accounting for over a third of total effects. For young carers, only total effects were significant, while for Indigenous young people and young people with a language background other than English, neither total nor indirect effects were significant. However, these findings need to be interpreted in the context of findings in Tables 2 and 3. These show that young people in all four groups also reported lower life satisfaction and were more likely to experience material disadvantage than young people who were not in any marginalised group.

5. Discussion

Existing research shows an association between social relations with peers and teachers at school, and wellbeing (Bond et al., Reference Bond, Butler, Thomas, Carlin, Glover, Bowes and Patton2007; García-Moya et al., Reference García-Moya, Brooks, Morgan and Moreno2015; Rothon et al., 2011). A number of studies also show that young people with particular characteristics – for example, disability, being a caregiver or identifying as Indigenous – experience exclusion at school (Coffin et al., Reference Coffin, Larson and Cross2010; Hamilton and Redmond, Reference Hamilton and Redmond2020). By linking these discourses within a social exclusion framework, this paper has sought to highlight broader structural factors associated with processes of exclusion: young people’s experience of exclusion enacted by identifiable agents (teachers and peers) who are acting within a framework that facilitates exclusion.

Our contribution, extending the work of Gross-Manos and colleagues (Gross-Manos, Reference Gross-Manos2015; Gross-Manos and Ben-Arieh, Reference Gross-Manos and Ben-Arieh2017), and Crous and Bradshaw (Reference Crous and Bradshaw2017) is to theorise a pathway from risk factors for social exclusion to quality of life outcomes, as proposed by Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007), that encompasses young people’s lived experience. The number and types of risk factors, and of lived experiences, that we use in our model is by necessity limited. Our data nonetheless allow us to tentatively propose that particular risk factors, experiences and outcomes are dynamically related as elements in processes of exclusion.

Consistent with the hypothesis of Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007) and Gross-Manos (Reference Gross-Manos2015), the analysis showed that material disadvantage, whether at the family or personal level, was associated with increased exclusion at school and lower life satisfaction. Experiences of exclusion were also associated with other recognised indicators of marginalisation. Young people in all four marginalised groups were over-represented among young people experiencing material disadvantage. Moreover, low family affluence and child deprivation remained strong predictors of exclusion and low life satisfaction when indicators of marginalisation were taken into account.

The findings presented here suggest that school engagement (getting satisfaction from school and learning) was less of an issue for materially disadvantaged young people than experience of social interactions with teachers and peers. It is not surprising that social interaction is a key vehicle for direct experience of social exclusion. However, the question of who excludes (and why they do it) has only entered policy discussion as a problem that requires remediation at the individual level. The data presented here suggest that material disadvantage impacts life satisfaction through the conduit of exclusion. Social exclusion itself is argued to be psychologically damaging (Wilkinson and Marmot, Reference Wilkinson and Marmot2003). Low life satisfaction (or subjective wellbeing) is a predictor of mental health problems (Keyes, Reference Keyes2002).

The definition of social exclusion proposed by Levitas et al. (Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007), and operationalised in this analysis, has been widely applied in academic research (including Crous and Bradshaw, Reference Crous and Bradshaw2017, discussed above). However, as Levitas (Reference Levitas2005) has noted, policy formulation and implementation to address social exclusion has taken a different course. Much of the focus has been on a social integration discourse, where exclusion is broadly equated with joblessness (or in the case of young people, disengagement from education). Neoliberal discourses of the kind that have guided Australian social policy in recent decades place people’s responsibility for their social inclusion squarely on their own shoulders (Marston et al., Reference Marston, Cowling and Bielefeld2016). This is also evident in Australian education policies (echoed in those of other countries) that emphasise the importance of parental and family resources in supporting young peoples’ educational outcomes (Education Council, 2019). Even though education policy formally recognises low income, disability, diverse ethnicity, Indigenous and young caregiver status as issues for equity focused interventions, support for young people in these groups is curtailed by an overarching marketised approach to social policy (Deeming and Smyth, Reference Deeming and Smyth2015) where young people who are excluded, and their families, are positioned as responsible for securing their own inclusion.

A focus on individual responsibility (in turn dependent to a large extent on family resources) is consistent with the portrayal by policy of agents of exclusion, not as institutions or structures, but as individuals who wield power over those they exclude. This is inherent in the characterisation of teachers as ‘pastoral agents’ (McCuaig et al., Reference McCuaig, Woolcock, Stylianou, Ng and Ha2020) whose role is to transform their students into self-governing subjects who strive towards academic achievement. Teachers (and schools) in Australia and several other OECD countries are rendered accountable for their performance in this regard through national testing regimes and international comparative surveys of student academic achievement. In a national context, schools that can show above average test results can attract more students, while schools with below average results can be branded as ‘failed’ schools and attract fewer students and resources (Polesel et al., Reference Polesel, Rice and Dulfer2014, p. 652). In an international context, education systems that show high average achievement are seen as promoting stronger economic growth (Jensen et al., Reference Jensen, Hunter, Sonnemann and Burns2012). Support for students who encounter difficulties or who experience bullying is often provided through individual-focused programs which portray bullying as an individual problem “rather than acknowledging the complex and multifaceted nature of bullying and the larger societal and systematic forces at play” (Winton and Tuters, Reference Winton and Tuters2015, p. 127). Policy focus remains firmly fixed on individuals (whether excluded or excluding), rather than on societal structures which create, perpetuate, and legitimise particular forms of exclusion.

As Gross-Manos (Reference Gross-Manos2015) notes, it is important that young people’s own voices are heard in debates on social exclusion. A focus on agents of exclusion suggests the need to identify both the immediate experience of exclusion, and the broader context in which this process of exclusion is enacted. The present analysis shows a strong relationship between material disadvantage and life satisfaction, mediated through the pathway of young people’s experience of teacher support and bullying. While educational interventions that directly focus on bullying or teaching practice can produce positive impacts, they do not address material disadvantage as a causal factor (Lampert et al., Reference Lampert, Ball, Garcia-Carrion and Burnett2020). In the Australian context, as in other countries in recent years under austerity policies, policies that impact material disadvantage among families with children have focused on reducing the generosity of payments – for example, by freezing means tested payments to families, and shifting increasing numbers of lone parents from the Parenting Payment to the considerably less generous Jobseeker Allowance (Davidson et al., Reference Davidson, Saunders, Bradbury and Wong2020). The last time (in 1987) the Australian Government pledged to address child poverty, child poverty rates fell significantly; however they have not fallen significantly since, and Australia remains mid-table in the OECD child poverty rankings (Davidson et al., Reference Davidson, Saunders, Bradbury and Wong2020; OECD, 2021; Redmond et al., 2013).

6. Conclusion

Significant gaps in this research agenda remain to be addressed. First, the lived experiences discussed in this paper mainly refer to the school setting. Research on exclusion in other settings – for example, in neighbourhood and community settings – is also needed, as is research with respect to access to services or outside-school activities that many young people take for granted, and research that focuses on young people of different ages and with diverse family contexts (such as living in out-of-home care or in lone parent families). This research needs to privilege young people’s own voices. Second, more work is needed on other aspects of marginalisation and exclusion. While young people in all four marginalised groups are shown to experience high levels of material disadvantage, pathways through indicators of participation to life satisfaction require closer analysis especially in the case of Indigenous young people, where the relatively small sample size may influence significance of findings reported in this paper. Third, this paper has highlighted relationships and pathways between material disadvantage, lived experience and life satisfaction. However, more research is needed on other policy-relevant factors that drive these relationships, not least the role of intergenerational disadvantage (Atkinson, Reference Atkinson, Atkinson and Hills1998), income inequality, and paternalistic policy settings (Marston et al., Reference Marston, Cowling and Bielefeld2016) that marginalise people (and their families) who depend on highly targeted and means-tested services.

What the present study adds is that experiences of participation mediate the relationship between low family affluence and young people’s personal deprivation on the one hand, and their quality of life on the other; this relationship remains when belonging in a marginalised group is considered. One factor that sets young people in the marginalised groups apart from other young people is the increased likelihood that they will experience material disadvantage and low life satisfaction, a predictor of mental health problems (Keyes, Reference Keyes2002). There is a need to investigate the role of other exogenous factors as key drivers in the processes of exclusion that young people in all the marginalised groups experience. Engagement with a social exclusion discourse by policymakers in Australia and other countries in the late 1990s and early 2000s created an opening for debate on these processes. However, this opening was never fully explored in policy applications (Saunders, 2013). This paper has attempted to operationalise the B-SEM (Levitas et al., Reference Levitas, Pantazis, Fahmy, Gordon, Lloyd and Patsios2007) on a sample of young people as a means of re-opening this debate.

Acknowledgements

The authors are grateful for funding provided by the Australian Research Council (Grant numbers LP120100543 and DP190100247).

Competing interests

The authors declare none.

References

Atkinson, A. B. (1998), Social Exclusion, Poverty and Unemployment. In Atkinson, A. B. and Hills, J. (eds.), Exclusion, Employment and Opportunity (pp. 1-20), London School of Economics: Centre for the Analysis of Social Exclusion.Google Scholar
Australian Government. (2009), A Stronger, Fairer Australia. National Statement on Social Inclusion. Retrieved from Canberra: https://vital.voced.edu.au/vital/access/services/Download/ngv:45844/SOURCE201 Google Scholar
Bond, L., Butler, H., Thomas, L., Carlin, J., Glover, S., Bowes, G. and Patton, G. (2007), Social and School Connectedness in Early Secondary School as Predictors of Late Teenage Substance Use, Mental Health, and Academic Outcomes. Journal of Adolescent Health, 40(4), 357.e359-357.e318. doi:https://doi.org/10.1016/j.jadohealth.2006.10.013 CrossRefGoogle ScholarPubMed
Bubonya, M. and Cobb-Clark, D. A. (2021), Pathways of Disadvantage: Unpacking the Intergenerational Correlation in Welfare. Economics of Education Review, 80, 102066. doi:https://doi.org/10.1016/j.econedurev.2020.102066 CrossRefGoogle Scholar
Clark, T. C., Fleming, T., Bullen, P., Denny, S., Crengle, S., Dyson, B., … Utter, J. (2013), Youth’12 Overview: The health and wellbeing of New Zealand secondary school students in 2012. Retrieved from Auckland, New Zealand:Google Scholar
Coffin, J., Larson, A. and Cross, D. (2010), Bullying in an Aboriginal Context. Australian Journal of Indigenous Education, 39, 7787.CrossRefGoogle Scholar
Commission of the European Communities. (1993), Background Report: Social Exclusion – Poverty and Other Social Problems in the European Community (ISEC/B11/93), retrieved from Luxembourg:Google Scholar
Constantine, N. and Bernard, B. (2001), California Healthy Kids Survey Resilience Assessment Module: Technical Report. Retrieved from Berkeley, CA: http://crahd.phi.org Google Scholar
Crato, N. and Thomson, S. (2020), Australia: PISA Australia—Excellence and Equity? Improving a Country’s EducationPISA 2018 Results in 10 Countries, 2547.Google Scholar
Cross, D., Shaw, T., Hearn, L., Epstein, M., Monks, H., Lester, L. and Thomas, L. (2009), Australian Covert Bullying Prevalence Study (ACBPS), Retrieved from Perth:Google Scholar
Crous, G. and Bradshaw, J. (2017), Child social exclusion. Children and Youth Services Review, 80(Supplement C), 129139. doi:https://doi.org/10.1016/j.childyouth.2017.06.062 CrossRefGoogle Scholar
Davidson, P., Saunders, P., Bradbury, B. and Wong, M. (2020), Poverty in Australia 2020: Part 1, Overview. Retrieved from Sydney: http://povertyandinequality.acoss.org.au/wp-content/uploads/2020/02/Poverty-in-Australia-2020_Part-1_Overview.pdf Google Scholar
Deeming, C. and Smyth, P. (2015), Social Investment after Neoliberalism: Policy Paradigms and Political Platforms. Journal of Social Policy, 44(2), 297318. doi: 10.1017/S0047279414000828 CrossRefGoogle ScholarPubMed
Education Council. (2019), Alice Springs (Mparntwe) Education Declaration. Retrieved from Carlton South (Vic.): https://docs.education.gov.au/system/files/doc/other/final_-_alice_springs_declaration_-_17_february_2020_security_removed.pdf Google Scholar
Emerson, E. and Llewellyn, G. (2014), Left behind 2014: Monitoring the social inclusion of young Australians with disabilities 2001-2012 (Technical report 1, 2014), Retrieved from https://ses.library.usyd.edu.au/bitstream/handle/2123/13529/Left_behind_2014%20Technical%20Report_FINAL.pdf?sequence=1 Google Scholar
Ermisch, J., Jantti, M. and Smeeding, T. (eds.) (2012), From Parents to Children: The Intergenerational Transmission of Advantage. New York: Russell Sage Foundation.Google Scholar
Fredricks, J. A., Blumenfeld, P. C. and Paris, A. H. (2004), School Engagement: Potential of the Concept, State of the Evidence. Review of Educational Research, 74(1), 59109.Google Scholar
García-Moya, I., Brooks, F., Morgan, A. and Moreno, C. (2015), Subjective well-being in adolescence and teacher connectedness: A health asset analysis. Health Education Journal, 74(6), 641654. doi: 10.1177/0017896914555039 CrossRefGoogle Scholar
Gemici, S. and Lu, T. (2014), Do schools influence student engagement in the high school years? (Longitudinal Surveys of Australian Youth Research Report No.69), Retrieved from Adelaide: https://www.ncver.edu.au/__data/assets/file/0016/8026/schools-influence-2745.pdf Google Scholar
Gross-Manos, D. (2015), Material deprivation and social exclusion of children: lessons from measurement attempts among children in Israel. Journal of Social Policy, 44(1), 105125. doi: 10.1017/S0047279414000646 Google Scholar
Gross-Manos, D. and Ben-Arieh, A. (2017), How Subjective Well-Being Is Associated With Material Deprivation and Social Exclusion in Israeli 12-Year-Olds. American Journal of Orthopsychiatry, 87(3), 274290. doi: 10.1037/ort0000160 Google ScholarPubMed
Hamilton, M. and Redmond, G. (2020), Are Young Carers Less Engaged in School than Non-Carers? Evidence from a Representative Australian Study. Child Indicators Research, 13(1), 3349. doi: 10.1007/s12187-019-09647-1 CrossRefGoogle Scholar
Huebner, E. S. (1991), Initial Development of the Student’s Life Satisfaction Scale. School Psychology International, 12(3), 231240. doi: 10.1177/0143034391123010 CrossRefGoogle Scholar
Jensen, B., Hunter, A., Sonnemann, J. and Burns, T. (2012), Catching up: learning from the best school systems in East Asia. Retrieved from Melbourne: https://grattan.edu.au/wp-content/uploads/2014/04/130_report_learning_from_the_best_detail.pdf Google Scholar
Katz, I. and Redmond, G. (2010), Review of the Circumstances Among Children in Immigrant Families in Australia. Child Indicators Research, 3(4), 439458. doi: 10.1007/s12187-010-9069-z CrossRefGoogle Scholar
Keddie, A. (2017), School autonomy reform and public education in Australia: implications for social justice. The Australian Educational Researcher, 44(4), 373390. doi: 10.1007/s13384-017-0243-x CrossRefGoogle Scholar
Keyes, C. L. M. (2002), The Mental Health Continuum: From Languishing to Flourishing in Life. Journal of Health and Social Behavior, 43(2), 207222. doi: 10.2307/3090197 CrossRefGoogle ScholarPubMed
Killen, M., Mulvey, K. L. and Hitti, A. (2013), Social Exclusion in Childhood: A Developmental Intergroup Perspective. Child Development, 84(3), 772790. doi: 10.1111/cdev.12012 CrossRefGoogle ScholarPubMed
Lampert, J., Ball, A., Garcia-Carrion, R. and Burnett, B. (2020), Poverty and schooling: three cases from Australia, the United States, and Spain. Asia-Pacific Journal of Teacher Education, 48(1), 6078. doi: 10.1080/1359866X.2019.1602863 CrossRefGoogle Scholar
Levitas, R. (2004), Let’s Hear It For Humpty: Social Exclusion, the Third Way and Cultural Capital. Cultural Trends, 13(2), 4156.CrossRefGoogle Scholar
Levitas, R. (2005), The inclusive society?: social exclusion and New Labour: Springer.CrossRefGoogle Scholar
Levitas, R., Pantazis, C., Fahmy, E., Gordon, D., Lloyd, E. and Patsios, D. (2007), The Multi-Dimensional Analysis of Social Exclusion. Retrieved from Bristol: http://dera.ioe.ac.uk/6853/1/multidimensional.pdf Google Scholar
Lietz, P., O’Grady, E., Tobin, M., Murphy, M., Macaskill, G., Redmond, G., … Thomson, S. (2016), Australian Child Wellbeing Project: Technical Survey Report. Retrieved from www.australianchildwellbeing.com.au Google Scholar
MacKinnon, D. P. (2008), Multivariate applications series. Introduction to statistical mediation analysis: Taylor & Francis Group/Lawrence Erlbaum Associates.Google Scholar
Main, G. and Bradshaw, J. (2012), A Child Material Deprivation Index. Child Indicators Research, 5(3), 503521. doi: 10.1007/s12187-012-9145-7 Google Scholar
Main, G. and Bradshaw, J. (2014), Child poverty and social exclusion: Final report of 2012 PSE study. Retrieved from https://www.york.ac.uk/inst/spru/pubs/pdf/PSEfinal.pdf Google Scholar
Marston, G., Cowling, S. and Bielefeld, S. (2016), Tensions and contradictions in Australian social policy reform: compulsory Income Management and the National Disability Insurance Scheme. Australian Journal of Social Issues, 51(4), 399417. doi:https://doi.org/10.1002/j.1839-4655.2016.tb01240.x CrossRefGoogle Scholar
McCuaig, L., Woolcock, L., Stylianou, M., Ng, J. Y. Y. and Ha, A. S. (2020), Prophets, pastors and profiteering: exploring external providers’ enactment of pastoral power in school wellbeing programs. Discourse: studies in the cultural politics of education, 41(2), 223237. doi: 10.1080/01596306.2020.1722425 Google Scholar
Muthén, L. K. and Muthén, B. O. (2017), Mplus User’s Guide (Eighth ed.), Los Angeles, CA.Google Scholar
OECD. (2019), PISA 2018 Results (Volume I): What Students Know and Can Do. Retrieved from Paris: https://www.oecd-ilibrary.org/content/publication/5f07c754-en Google Scholar
OECD. (2021), OECD Family Database. Retrieved from: https://www.oecd.org/els/family/database.htm Google Scholar
O’Grady, A., Pleasence, P., Balmer, N. J., Buck, A. and Genn, H. (2004), Disability, social exclusion and the consequential experience of justiciable problems. Disability & Society, 19(3), 259272. doi: 10.1080/0968759042000204158 CrossRefGoogle Scholar
Polesel, J., Rice, S. and Dulfer, N. (2014), The impact of high-stakes testing on curriculum and pedagogy: a teacher perspective from Australia. Journal of Education Policy, 29(5), 640657. doi: 10.1080/02680939.2013.865082 CrossRefGoogle Scholar
Popay, J. (2010), Understanding and tackling social exclusion. Journal of Research in Nursing, 15(4), 295297. doi: 10.1177/1744987110370529 CrossRefGoogle Scholar
Priest, N., Kavanagh, A., Bécares, L. and King, T. (2019), Cumulative Effects of Bullying and Racial Discrimination on Adolescent Health in Australia. Journal of Health and Social Behavior, 60(3), 344361. doi: 10.1177/0022146519868847 CrossRefGoogle ScholarPubMed
Redmond, G. (2015), Social inclusion in Australia – what has it achieved? Australian Journal of Social Issues, 50(2), 115117. doi: https://doi.org/10.1111/spol.12038 CrossRefGoogle Scholar
Skattebol, J., Saunders, P., Redmond, G., Bedford, M. and Cass, B. (2012), Making a difference: Building on young people’s experiences of economic adversity: Final Report. Retrieved from Sydney: http://www.sprc.unsw.edu.au/media/File/Making_a_Difference_Building_on_Young_Peoples_Experiences_of_Economic_Adversity.pdf Google Scholar
Taylor, D. R., Gray, M. and Stanton, D. (2016), New conditionality in Australian social security policy. Australian Journal of Social Issues, 51(1), 326. doi: https://www.unicef-irc.org/publications/pdf/an-unfair-start-inequality-children-education_37049-RC15-EN-WEB.pdf CrossRefGoogle Scholar
United Nations. (2016), Leaving no one behind: the imperative of inclusive development. Report on the World Social Situation 2016 (ST/ESA/362), retrieved from New York: http://www.un.org/esa/socdev/rwss/2016/full-report.pdf Google Scholar
Warren, D. and Edwards, B. (2017), Young Carers. In Australian Institute of Family Studies (ed.), The Longitudinal Study of Australian Children Annual statistical report 2016 (pp. 85-118), Melbourne: AIFS.Google Scholar
Wilkinson, R. and Marmot, M. (2003), Social Determinants of Health - The Solid Facts. Geneva, SWITZERLAND: World Health Organization.Google Scholar
Winton, S. and Tuters, S. (2015), Constructing bullying in Ontario, Canada: a critical policy analysis. Educational Studies, 41(1-2), 122142. doi: 10.1080/03055698.2014.955737 CrossRefGoogle Scholar
Figure 0

Figure 1. Model of pathways for social exclusion from risk factors to outcomes as proposed by Levitas et al. (2007)

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Figure 2. Model of pathways for social exclusion from risk factors to outcomes as proposed by Gross-Manos (2015)

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Figure 3. Model of pathways for social exclusion from risk factors to outcomes as proposed by Crous and Bradshaw (2017)

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Figure 4. Model of pathways for social exclusion from risk factors to outcomes as operationalised in this analysis

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TABLE 1. Average scores on bullying, teacher support, school satisfaction and life satisfaction scales, by affluence and deprivation status (means)

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TABLE 2. Average scores on bullying, teacher support, school satisfaction and life satisfaction scales, by marginalisation status (means)

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TABLE 3. Affluence and deprivation status, by marginalisation status (proportions)

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TABLE 4. Standardised Path coefficients from resources and risk factors to life satisfaction

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TABLE 5. Standardized Total and indirect effects from resources and risk factors to life satisfaction