Negotiating uncertain economic times: Youth employment strategies in England
Abstract
Higher education is commonly understood as the gateway to better, higher-paying jobs. This paper draws on longitudinal survey and interview data to explore how different groups of young people, those who left school at 18 and those graduating from higher education, negotiated pathways into employment or otherwise during the recent economic recessionary climate in England. While a mix of employment and unemployment featured in both groups, with temporary and unstable contracts more common than skilled and secure jobs, our evidence reveals that those with degrees were less likely to be in work at the ages of 22 to 23 than those who left school to enter employment at 18. In some contradistinction to popular discourses on the employability benefits of higher education therefore, entering paid work at 18 was a more effective strategy for being in employment five years later than proceeding into higher education.
Introduction
The economic uncertainty of the 2008–9 global recession and years of subsequent austerity served only to exacerbate the general trends in youth labour markets established at the end of the twentieth century (Harvey, 2010; France, 2016; Schoon & Bynner, 2017). In the UK, young people were particularly hard hit by the financial crisis, with high levels of youth unemployment and job insecurity being experienced by those from all educational backgrounds. In 2011–12, just after the economic recession, youth unemployment in the UK stood at about 21% for those aged 16–24, a factor of 3.7 larger than the 25 and over unemployment rate.11
This contextual descriptive data analysis was conducted by one of the authors using Eurostat unemployment data.
By 2014, youth unemployment had reduced to about 17%. However, its ratio of 3.8 compared with the 25 and over unemployment rate remained large.11
This contextual descriptive data analysis was conducted by one of the authors using Eurostat unemployment data.
Not only was the proportion of young people in employment hard hit, but so was the quality of the work they were involved in. For example, there was a significant reduction in numbers of young people in full-time employment: 68% of females and 89% of males were in full-time jobs in 2014, compared with pre-recession rates (2004) of 74% of females and 95% of males.22
This descriptive data analysis was conducted on data from the UK Labour Force study (LFS) by Golo Henseke as part of the ESRC LLAKES research project.
Levels of precariousness (measured by the combined indicator of underemployment, a temporary or zero hours contract) rose from previous low levels in 2004 of 8% to 13% in 2014. For young women, the increase stood slightly higher, at six percentage points, from 10% in 2004 to 16% in 2014.22
This descriptive data analysis was conducted on data from the UK Labour Force study (LFS) by Golo Henseke as part of the ESRC LLAKES research project.
The poor quality of opportunities for young people attempting to transition from education to work during this period led them to be dubbed ‘the lost generation’ (Mortimer, 2014: 97).
How different groups of young people fared during this critical period of economic uncertainty is thus of real importance to future policy and practice (Crosnoe, 2014). Who were the hardest hit and who were more successful in their strategies to find work or enter a desired career during this time? In this paper, we draw on a unique dataset—the Citizenship Education Longitudinal Study (CELS)—to examine these questions. Using both quantitative and qualitative data, we explore how young people from different social backgrounds and different levels of educational qualifications progressed in their attempts to secure employment during challenging economic times.
Conceptualising youth and work transitions
Several general trends are evident in the research undertaken on young people's experience of Western labour markets over the last few decades. First, in line with other transitions such as housing and family formation (Berrington et al., 2015), youth employment has been characterised as increasingly ‘precarious’ (MacDonald, 2009; Standing, 2011), with significant challenges in finding sustainable employment. Second, young people's transitions into the labour market are delayed, not only due to declining employment opportunities but also due to the mass expansion of higher education (Furlong & Cartmel, 2009). Third, it is argued that while young people have more choices than previous generations, they also have more personal responsibility for job seeking, skill development and career trajectories (Mortimer, 2009). As neoliberal contexts weaken the normative force of social structural positions and lifescripts produced through, inter alia, class, gender, ethnicity, religion, place and community, impetus is increasingly placed on young people themselves to individually scout for opportunities and tailor their own life trajectories (Price et al., 2011; Leonard et al., 2016).
While these themes have gained a substantial place within both academic and policy literatures, it is also recognised that finer granularity is required for capturing the consequences of contemporary economic events (Mortimer, 2014). For example, while jobs for young people are marked by precarity, the form of this has changed over the last 30 years. Youth unemployment in the UK, in terms of the proportion of young people in work, was in fact at a very similar level during the recent economic crisis as in the 1980s (in 1984, the youth unemployment rate was also about 20%), when many of the current cohort's own parents were attempting to enter the labour market (Office for National Statistics, 2014). As we demonstrate later in this paper, many young people in the UK did manage to get jobs between 2008 and 2014. However, what has changed is the quality of the jobs now offered to young people and the terms of their working conditions, regularly involving experiences of under-employment, over-qualification, short-term contract working, zero hours contracts and low pay (Felstead et al., 2015). These features were more pronounced within the youth labour market than the labour market as a whole, meaning that, increasingly, young people were ‘cycling’ between jobs and spells of unemployment, facing multiple barriers to finding secure, full-time jobs and sustainable career pathways (McCollum, 2013; Tomaszewski & Cebulla, 2014).
This also suggests that the linearity conveyed within the concept of ‘delayed transitions’ must also be understood with some caution (Furlong et al., 2011). While it is undoubtedly the case that the increasing number of young people accessing higher education and the growing credentialism of work mean that the average age to enter the labour market has extended (Helve & Evans, 2013; Quintin & Martin, 2014), research also demonstrates that many young people's experiences reflect a ‘set of movements which are less predictable and involve frequent breaks, backtracking and the blending of statuses’ (Furlong et al., 2003: 24). ‘Independent adulthood’ may come and go: periods of relative stability in economic wealth and lifestyle intersected by the precarity endemic to neoliberal economies. Further, while theorists such as Bauman (1998) and Beck and Beck-Gernsheim (2002, 2009) have argued that shifts towards individualised decision-making can weaken the impact of traditional class and gender-based lifescripts to open up ‘choice biographies’, recent evidence (Tholen, 2013) confirms the ongoing traction of social background on labour market opportunities, even for those supposedly at its upper ends, such as graduates. Choice and individualism remain ‘bounded’ by social background, as young people negotiate the labour market according to their capital and resources (Evans, 2002).
In terms of responses to this complex rebus, interpretations frequently dichotomise young people's positions. On the one hand are more positive interpretations of young people's extended transitions, whereby late teens to mid-20s are conceptualised as ‘exploring’ (Krahn et al., 2015); ‘experimentally drifting’ through alternative educational, employment and lifestyle roles, exhibiting considerable agency over their transition into adulthood (Nyhagen-Predelli & Cebulla, 2011). In contrast, alternative explanations focus on the negative effects of employment instability, seeing young people as floundering (Krahn et al., 2015) while trying to translate educational credentials into satisfactory jobs. Victims of the ‘churning trap’ (Worth, 2005) of frequent spells of un/employment, their instability in the labour market portends adverse longer-term employment outcomes (Gregg & Tominey, 2005). This may become further entrenched by gender, with additional employment gaps for young women having families often scarring long-term employment and earning abilities (Loughran & Zissimopoulos, 2009), as well as by other structural features such as social class, lack of educational qualifications and regional location (Brannen & Nilsen, 2005; Roberts, 2012). In contrast, enhanced social capital such as higher education, family wealth and living in the Southeast may enable young people to negotiate transitions to adulthood more smoothly (Coffey & Farrugia, 2014).
While this binaristic framework has been widely deployed to describe youth transitions more generally over the past 15 years (Roberts, 2011), how accurate a lens is this for understanding the most recent economic hardships? In this paper, we examine a cohort of British young people's experiences as they negotiated access to the recession-hit youth labour market. Using both quantitative and qualitative data, we explore how young people from different social backgrounds and with different levels of educational qualifications managed in their attempts to find work and/or enter desired careers as the financial crisis progressed. The complexity of our findings suggests that, conceptually, we need to move beyond ‘unproductive ontological dualisms’ (Coffey & Farrugia, 2014: 469) to create a more nuanced conceptual framework by which to understand how young people fare in times of economic vulnerability.
Quantitative analysis methodology
The CELS data is unique in that it combines a panel study with a questionnaire tapping a wide range of youth attitudes and behaviours. The study includes data from a cohort of young people aged 11 and 12 (Year 7; first year of secondary school), surveyed for the first time in 2003 and then every two years until 2011 (Round 5), and finally in 2014 when the respondents were aged 22–23 (Round 6). The data was collected from a nationally representative sample of 112 state-maintained schools in England—representative in terms of region, GCSE attainment and percentage of students on free school meals (Keating & Benton, 2013). The CELS data is no different from other longitudinal datasets in that it suffered from considerable attrition: from 18,583 respondents in Round 1 to just 734 of the original cohort (4.2%) in Round 6. The database, however, includes top-ups for each data collection point to ensure a nationally representative sample and, for the longitudinal study, there are weights for the rounds following Round 1 to compensate for attrition on gender, educational attainment, ethnicity and social background, identified as the main drivers of non-response in longitudinal studies (Nathan, 1999). Applying these weightings makes the data of later waves similar to Round 1 on these variables (Keating & Benton, 2013).
In this paper we focus on young people between the ages of 17–18 and 22–23 (Rounds 4 to 6 of the CELS dataset). This cross-sectional data includes: Round 4 (2009) N = 1,283 aged 17–18: Round 5 (2011) N = 1,509 aged 19–20; and Round 6 (2014) N = 945 aged 22–23. For the longitudinal data analysis, we used Rounds 4–6 N = 322 and Rounds 5–6 N = 811. We then conducted both quantitative analysis on the findings of the survey and qualitative analysis on the interviews which, for clarity, we discuss in turn.
Quantitative data analysis
Measures
The independent variable for the quantitative logistic regression analysis is employment. In Rounds 4–6, all participants in the survey were asked what their main activity was and for the descriptive statistics we used the binary response categories of ‘working’, ‘studying’ and ‘not in education or employment’ (NEET). For the logistic regression analysis, we used the outcome of employment and the binary response to the item on ‘main activity’ from Round 6: ‘working’. From Round 5 we used the same item and the binary response: ‘working’, ‘doing a degree’, ‘at college’ and ‘NEET’. Thus, for the logistic regression, we have separated the education category into those undertaking degrees and college education (usually European Qualification Levels 1–3) for more accurate evaluation of the learning experience undertaken. To control for social background, we added the measure of ‘books at home’, found to be strongly correlated with parental income (Schuetz et al., 2008; Baird, 2012), making it a good stand-in for parental income and other more obvious measures of social background that are unavailable in CELS (Keating & Benton, 2013). We also added the measure ‘gender’. Both these items are drawn from the first round of participant response to the survey.
Descriptive statistics
In Round 6 in 2014 (ages 22–23), about three-quarters of the young people were employed, about 15% were NEET and about 10% were in some form of education (see Figure 1). When participants were aged 19–20 in 2011, almost 60% were still in education and 30% were employed, with slightly fewer than 15% not in education or work. Three-quarters of those in education were studying for undergraduate degrees, with the next highest category (just under 20%) on a college course. From those in the NEET category, 68% were ‘looking for a job’. At the youngest age, when the young people were 17–18 (in 2009), over 90% were in education, either at school or college; 5% were in work and 5% were NEET. This compares with the national average for 2009 of about 80% of 17–18-year-olds in education or training and about 20% NEET (Department for Education, 2010). The just over 10% difference from the national average can be attributed to the fact that CELS was a school-based study and, despite the best efforts of those conducting the research, many of those who dropped out of education were unfortunately lost at this stage.
Following those who participated in Rounds 4–6, the most common trajectory, involving more than half of the young people, was to be in education at 17–18, then proceed into higher education and, by age 22–23 (in 2014), to have found employment (Figure 1). We classify this group as Graduates in work. A similar group are the Graduates not in work, a group that followed a similar trajectory but, at 22–23, were still without work. This is a small group, making up 7% of cases. However, interestingly, most young people who were not in education or employment at 22–23 had followed this graduate pathway, critically questioning assumptions that higher education acts as a protection mechanism from unemployment (Ball, 2016).
The next largest trajectory was the School leavers in work, which included the 20% of students who progressed from school directly into work either after secondary or tertiary level education and who were still in work aged 22–23. Finally (slightly less than 8%) were the School leavers not in work group, who left education at 17–18 but were not in education or work at age 19–20. Encouragingly, very few remained in this situation (slightly more than 1%), as most of the NEETS group at age 19–20 had found their way into work by 22–23 in 2014 (slightly more than 5%).
Logistic regression model
The next step in the analysis was to evaluate, in the context of the economic crisis, how successful the young people's varying entry routes were for employment at age 22–23. To increase the sample size, we used the longitudinal data from Rounds 5 (aged 19–20) and 6 (aged 22–23), only N = 811.33
Having removed Round 4 data from the analysis, the data becomes more representative of the population as the dataset now also includes people who left school before the age of 18.
We then ran a binary logistic regression analysis using the longitudinal data for Rounds 5 (aged 19–20) and 6 (aged 22–23). As being in work in Round 5 had appeared as the most promising category in our previous analysis for being in work in Round 6, we applied this group as the reference category in order that all other groups are compared to this one. The model included 811 cases and the Nagelkerke R2 indicates that 12% of the variance in the model is explained, although affect sizes can differ due to the size of the dataset and the types of variables used (12% of variance explained is a reasonable level for social science research; Fichman, 1999).
The results of the model in Table 1 show that being in work at age 19–20 in 2011 (the reference category) in Round 5 is the most effective method for being in work in Round 6 at age 22–23 in 2014. The probabilities indicate that there is a 72% chance of this group being in work. This is the group that we refer to as School leavers in work.
| Logit coefficient | S.E. | Absolute odds ratio | Probability in work | Probability out of work | |
|---|---|---|---|---|---|
| Books 1–10 | 0.610 | 0.64 | 4.75 | 83% | 17% |
| Books 11–50 | 0.963 | 0.62 | 6.77 | 87% | 13% |
| Books 51–100 | 1.468**
The results note the logits, the significance levels *p < 0.05, **p < 0.01, ***p < 0.001, the absolute odds ratios and probabilities for being in work.
|
0.63 | 11.22 | 92% | 8% |
| Books 101–200 | 1.498*
The results note the logits, the significance levels *p < 0.05, **p < 0.01, ***p < 0.001, the absolute odds ratios and probabilities for being in work.
|
0.64 | 11.56 | 92% | 8% |
| Books >200 | 0.950 | 0.62 | 6.68 | 87% | 13% |
| Female | −0.119 | 0.18 | 2.29 | 70% | 30% |
| R5Degree | −0.519*
The results note the logits, the significance levels *p < 0.05, **p < 0.01, ***p < 0.001, the absolute odds ratios and probabilities for being in work.
|
0.25 | 1.54 | 61% | 39% |
| R5NEET | −1.709***
The results note the logits, the significance levels *p < 0.05, **p < 0.01, ***p < 0.001, the absolute odds ratios and probabilities for being in work.
|
0.28 | 0.47 | 32% | 68% |
| R5College | −1.09***
The results note the logits, the significance levels *p < 0.05, **p < 0.01, ***p < 0.001, the absolute odds ratios and probabilities for being in work.
|
0.29 | 0.87 | 46% | 54% |
| Constant (R5work/male/no books) | 0.949 | 0.62 | 72% | 28% |
- The results note the logits, the significance levels *p < 0.05, **p < 0.01, ***p < 0.001, the absolute odds ratios and probabilities for being in work.
Doing a degree at 19–20 in 2011 is significantly less effective for being in work at age 22–23 in 2014 than being a School leaver in work in Round 5. However, it is still effective, with a 61% chance of becoming a Graduate in work and a 39% chance of becoming a Graduate not in work. Being a School leaver not in work and going to college at age 19–20 was also significantly less effective for being in work at 22–23 compared with the School leavers in work group. The School leavers not in work group had a 32% chance of being in work and the college group had a 46% chance of being in work in 2014.
The control variables show that, as the number of books in the home increases, so do the chances of being in work increase, suggesting an effect of parents’ socioeconomic background. This becomes significant from 51–200 books at home. The largest number of books (over 200) is no longer significant, and this could well be because there was a very small number of participants in this group. There is no significant gender difference for being in work in Round 6 at age 22–23 in 2014.
Before discussing these findings, it is necessary to acknowledge: (i) the levels of unemployment in the CELS dataset are lower than the national average; and (ii) fewer young people are represented as NEET. We also need to acknowledge that the situation regarding employment status is only for young people aged 22–23 in 2014, and does not allow claims as to what will happen through their life course. In addition, our groups of young people are likely to have had different experiences regarding the duration of their transition from full-time education into full-time employment. For both School leavers groups, this is likely to be 4–5 years’ experience of the labour market (whether employed or not), whilst the two Graduate groups are likely to have had 1–2 years’ experience of full-time work in the labour market (although they may well have had part-time jobs while undertaking their degree). This difference may well be a factor contributing to the differences in employment levels in 2014. Building from this, a key issue for graduate employment is not only securing a first job, which is often described as ‘temporary’ and with the immediate aim of securing some income, but also the quality of work gained over time and whether this progresses into a graduate-level career (Connor et al., 2004: 97). While the qualitative analysis later in this paper addresses this issue for the initial early years of entering the labour market, the type of longitudinal data needed for quantitative analysis regarding the longer-term employment experience after graduation (e.g. 6 years after graduation) is not yet available for this cohort. It must be acknowledged that, usually, by the time the data is available, the socioeconomic and education policy context regarding youth transitions may have changed—a limitation of quantitative analysis in this field (Smetherham, 2005).
Considering the limitations of the CELS data, we can suggest that, in the context of the economic crisis, in order to have a job at 22–23 in 2014, the most effective route was to have progressed straight into work from higher secondary level (School leavers in work). An initial descriptive exploration of the cross-sectional data from the Labour Force Survey (LFS) for 2014 supports this analysis,22
This descriptive data analysis was conducted on data from the UK Labour Force study (LFS) by Golo Henseke as part of the ESRC LLAKES research project.
also identifying that 22–23-year-olds with A-levels were more likely to be in employment, and more stable employment, than graduates. However, the LFS analysis also shows that if the aspiration was to acquire a more highly skilled occupation with greater financial return, then a young person was wiser to undertake a degree. However, this said, the chance of achieving such jobs directly on graduation was severely limited; the types of employment undertaken by graduates remained more precarious. Only 30% of Graduates in work managed to progress directly into highly skilled jobs. The 39% chance of being in the Graduates not in work group in 2014 may not have been clear to young people entering higher education in 2010 at age 18 or 19! What is also evident from the LFS data, and building on the CELS analysis, is the importance of gaining a Level 3 qualification. This is demonstrated to be crucial to job opportunities and stability, with Level 2 qualifications and below resulting in lower employment levels, less job security and low occupational status.
As noted above, one challenge with the quantitative data is that general trends may not fully represent the complexity and fluidity of young people's transitions, nor provide a holistic picture of their experiences (Helve & Evans, 2013). However, a real advantage of the CELS data is that we can also draw on the interviews to give a richer account of the young people's strategies towards work and careers.
Qualitative analysis methodology
Interviews were conducted with a sample of the young people in the CELS dataset (n = 50) topped up with interviewees recruited via snowballing, twitter and partnership with a youth organisation (N = 51) across the four groups described above. Their social characteristics are detailed in Table 2. Capturing social class was complex, compounded by our mixed-methods approach which produced differences in available information. The quantitative data, and the 50 interviewees recruited via the survey, include indicators of social class: books in the home, parental education and occupation. However, the top-ups were not asked about books in the home, and 26 were unsure about parents’ occupations or qualifications and/or were estranged from family. The aim of the top-up recruitment was to access ‘harder to reach’, disadvantaged young people and, though not a representative sample, the spread of social backgrounds in each group of our sample is evidenced in Table 2.
| Graduates in work | Graduates not in work | School leavers in work | School leavers not in work | Total | ||
|---|---|---|---|---|---|---|
| N | 23 | 21 | 24 | 33 | 101 | |
| Gender | Male | 9 | 7 | 16 | 19 | 51 |
| Female | 14 | 14 | 8 | 14 | 50 | |
| Ethnicity | Asian other | 1 | 1 | 0 | 1 | 3 |
| Black African | 7 | 1 | 2 | 4 | 14 | |
| Black British | 0 | 0 | 0 | 1 | 1 | |
| Black Caribbean | 1 | 0 | 0 | 3 | 4 | |
| British Indian | 0 | 2 | 0 | 0 | 2 | |
| British Pakistani | 2 | 4 | 3 | 5 | 14 | |
| Kurdish | 0 | 0 | 0 | 1 | 1 | |
| Mixed | 2 | 1 | 0 | 0 | 3 | |
| White British | 10 | 12 | 19 | 18 | 59 | |
| Age | 18 | 0 | 0 | 0 | 1 | 1 |
| 19 | 0 | 0 | 0 | 2 | 2 | |
| 20 | 0 | 0 | 1 | 3 | 4 | |
| 21 | 1 | 3 | 0 | 4 | 8 | |
| 22 | 13 | 12 | 10 | 10 | 45 | |
| 23 | 4 | 4 | 9 | 8 | 25 | |
| 24 | 3 | 1 | 1 | 5 | 10 | |
| 25 | 1 | 0 | 0 | 0 | 1 | |
| 26 | 1 | 1 | 3 | 0 | 5 | |
| Highest | GCSE/left at 16 | 0 | 0 | 2 | 11 | 13 |
| qualification | FE/HND | 0 | 0 | 17 | 14 | 31 |
| A-levels | 0 | 5 | 8 | 13 | ||
| Degree | 21 | 17 | 0 | 0 | 38 | |
| Postgraduate | 2 | 4 | 0 | 0 | 6 | |
| Status | Employed | 20 | 0 | 17 | 0 | 37 |
| Employed part-time | 2 | 0 | 2 | 0 | 4 | |
| Apprenticeship | 1 | 0 | 1 | 0 | 2 | |
| Study and work | 0 | 0 | 4 | 0 | 4 | |
| Studying | 0 | 11 | 0 | 16 | 27 | |
| Unemployed | 0 | 10 | 0 | 15 | 25 | |
| Homeless | 0 | 0 | 0 | 2 | 2 | |
| Father's education | Left full-time education at 15 or 16 | 8 | 7 | 10 | 10 | 35 |
| Left after college or sixth form | 5 | 7 | 5 | 3 | 20 | |
| Studied at university | 6 | 7 | 3 | 2 | 18 | |
| Missing | 4 | 0 | 6 | 18 | 28 | |
| Mother's education | Left full-time education at 15 or 16 | 10 | 9 | 10 | 9 | 38 |
| Left after college or sixth form | 6 | 8 | 4 | 3 | 21 | |
| Studied at university | 6 | 4 | 2 | 3 | 15 | |
| Missing | 1 | 0 | 8 | 18 | 27 | |
| Father's occupation | Professional or higher technical work | 7 | 6 | 2 | 3 | 18 |
| Manager or senior administrator | 2 | 2 | 2 | 2 | 8 | |
| Clerical | 1 | 1 | 1 | 0 | 3 | |
| Sales or services | 1 | 0 | 3 | 1 | 5 | |
| Small business owner | 2 | 6 | 1 | 1 | 10 | |
| Foreman or supervisor of other workers | 0 | 0 | 0 | 0 | 0 | |
| Skilled manual work | 4 | 1 | 5 | 4 | 14 | |
| Semi-skilled or unskilled manual work | 1 | 4 | 3 | 5 | 13 | |
| Homemaker/carer in the home | 0 | 0 | 0 | 0 | 0 | |
| Never worked | 0 | 0 | 1 | 0 | 1 | |
| Other | 0 | 0 | 2 | 1 | 3 | |
| Missing | 5 | 1 | 4 | 16 | 26 | |
| Mother's occupation | Professional or higher technical work | 4 | 5 | 1 | 4 | 14 |
| Manager or senior administrator | 3 | 0 | 2 | 0 | 5 | |
| clerical | 4 | 4 | 2 | 3 | 13 | |
| Sales or services | 4 | 2 | 3 | 3 | 12 | |
| Small business owner | 0 | 2 | 1 | 0 | 3 | |
| Foreman or supervisor of other workers | 0 | 0 | 1 | 0 | 1 | |
| Skilled manual work | 2 | 1 | 1 | 0 | 4 | |
| Semi-skilled or unskilled manual work | 1 | 0 | 3 | 4 | 8 | |
| Homemaker/carer in the home | 3 | 4 | 6 | 2 | 15 | |
| Never worked | 0 | 0 | 0 | 1 | 1 | |
| Other | 0 | 3 | 0 | 1 | 4 | |
| Missing | 2 | 0 | 4 | 15 | 21 |
Interviews were all recorded and transcribed, and initially coded using Nvivo into broad themes of ‘employment’, ‘unemployment’ and ‘entry routes and practices’. These three themes (over 300 pages of transcript extracts) were then read individually by the team and submitted to closer textual and thematic analysis via selective coding: how the young people described their routes into employment, the types of jobs they had undertaken over the course of their lives, paid and unpaid, and how they represented these in terms of choices, careers and future aspirations. As we now turn to discuss, we used the four categories established in the quantitative methodology to explore the similarities and differences between the young people according to trajectory taken.
School leavers in work: Securing the future
… in a very secure job, obviously… Just a normal life really and hopefully secure job and secure home…
I am thinking long term. I want like an office job where it's 9 to 5, get weekends off, I want it to be permanent, I want a pension, I've started to think that way.
I've been in work since 2009 working at a care home, laundry and cleaning… I want more, because I'm growing up now, I want more hours, earn more money, more things. I'm young, I need to get out there, working hard and earning a good living. (Louise, White British, 22)
I love to work. I LOVE to work. I do up to 96 hours in a row… We do 12 hour shifts, 8 til 8, so I can do up to 13 days in a row, maybe have a weekend off. We've got this house recently, two weeks ago, so I've got a mortgage – quite scary, bit creepy, so a lot more responsibility. (Emma, White British, 22, Nursing Home Carer)
Rather than either exploring or floundering, therefore, this group of school leavers can perhaps better be conceived as strategically ‘securing’, the content of their work appearing less important than their earning potential, security and prospects for the future. While the uncertain economic climate meant that such security could not usually be accessed immediately on leaving school, members of this group sought to negotiate their economic stability through long hours and hard work, albeit in sometimes poor-quality jobs.
School leavers not in work: Thwarted and unsupported
The School leavers not in work left school between the ages of 15 and 18 and are not currently working. It must be noted here that, because the number of young people within this category in the Round 6 CELS dataset was very small, our sample was boosted in part by working with a charity that worked with vulnerable young people. As such, we do not make any claims for representativeness in our discussion of this group. Rather, we explore the trajectories of a particular subset within the larger cohort of School leavers not in work.
I would like to get a good job but I don't have the education to get it… obviously there isn't enough places so you have to go to your catchment school, which normally isn't the best one that you'd wish to go to. In a way it is discrimination because you can't go to that school because you can't afford to live in the posh area, so… (Jasmine, White British, 24)
…you were lied to… they said you would find employment from it if you stuck with it… I didn't though, all what happened was you work for 30 hours a week and if you didn't you were homeless… People wouldn't have minded so much if they said ‘you do this for a month and then you're guaranteed a place’.
I had no other means of getting money… so I had to do what I had to do. I've been in and out of jobs, like warehouse jobs, agencies but… Yeah I want a full time job, anything, a full time job, yes…
…we all have less opportunity from people that live in these big fancy areas like Chelsea,… companies won't give you a job because you are from a certain area and think that you are a bad person. (JT, 23)
It is harder if you're poorer to get out because you're surrounded by other poor people with similar mentalities… Well that's what they know and that's what they expect and want from life isn't it? (Dean, White British, 24)
For these young people, rather than identifying the recessionary climate as a key barrier to their work prospects, it was the broader package of structural and individual features which were highlighted as preventing them from accessing employment. Lacking the family support, networks and contacts needed to get by in poor neighbourhoods (MacDonald et al., 2005), and any positive outcomes from the Job Centre, this group felt thwarted and unsupported in their quest for stable and secure working lives.
Graduates in work: Biding time
There's a lot of people that work, have jobs, but it's plainly necessarily because they need the money. And that's what I do right now… (Imran, British Pakistani, 22)
…my position here at home is that I need to bring in a full time wage,… as much as I'd like to have this time now to just be able to do internships and then find my way, my mum needs me to bring in a proper wage, so I'm willing to take anything – the plan now is work full time now,… then leave to go to a grad scheme next year. (Sophia, Black Carribean, 22)
The job, I started when I was in college, just Saturdays. As soon as I finished last year my job became a full-time post, so I thought until I get something in my field I might as well take this opportunity, and I don't regret it at all because I would have been without a job. (Parveen, 22)
The job search – I haven't struggled luckily. I mean I'm struggling for my career job, but just a general job I've not found it hard. (Dalia, Black African, 22)
…I feel brilliant that I finally have a salary, that's really exciting… having a permanent wage to feel like I've got a grown-up job. When I finally made it to £10 an hour I was ‘oh! This is a decent hourly rate now, I don't feel like I'm still a teenager’. (Samantha, mixed, 26)
…it's been disheartening, because still it's hard to get a job, even though I may now have a Masters and much more experience, it's still really difficult to get a job in terms of what I want to do. (Jamelia, Black African, 24)
Far from seeing youth as an exciting period of exploring alternative sets of lifestyle choices, therefore (Beck, 2000; Krahn et al., 2015), this group are faced with the harsh reality of biding time, accepting low-level work to survive economically and putting higher-level dreams and ambitions on hold. However, nor, on the other hand, can they be seen to be floundering; many demonstrated a clear-sighted strategy that work and CV building was ‘the way in’ to, eventually, securing a job in their chosen field. This said, the dilemma was whether to ‘get stuck’ in any job which pays, or attempt to survive a succession of unpaid work to gain experience in a chosen field.
Graduates not in work: Trying to find a balance
When I was 16 I thought I'd finish my degree, get a good job just like that and start earning. But now I've actually got out there and started looking for a job, it's a lot harder than I expected. (Athula, Asian other, 21)
It's a huge part of journalism. I've already done two months of work experience, unpaid. It's just expected for journalists to do unpaid work experience, and there's just never any talk about getting paid for it, you just naturally assume it's unpaid. (Ailsa, White British, 21)
It's not even about whether you've got a degree now, or like how hard you've done this. If you know the right people and if you get that opportunity where you know you can get it, then you just kind of do. (Humera, British Pakistani, 21)
Loads of employers are just expecting to have loads of unpaid interns… people from working-class backgrounds can't afford to go in… There was a notion that unpaid internships should be banned – I supported that. (Daniel, White British, 22)
The problem is I have no money, so I'm stuck between getting a part-time job in somewhere like Sainsbury's and then doing something else to try and get into publishing at the same time, or to stick with unpaid work experience. I'm on Jobseeker's Allowance at the moment, I'm kind of torn between the two at the moment, I'm trying to find a balance, because obviously I need the money but I want to do what I want to do…
Discussion and conclusion
Our findings provide an interesting contribution to existing understandings of young people and work in late modernity. First, the results of both the quantitative and qualitative analyses demonstrate that, for many of the young people in our sample, from a range of social backgrounds, finding a job was not that difficult, even within the restricted labour market and economic climate. This provides further support to a more nuanced understanding of the nature of contemporary youth precarity: while some form of paid work may be relatively accessible, finding a job with a career pathway in an occupation of choice and with long-term security is far less easy. This is a significant change in the youth labour market in the UK compared to a generation ago (Green, 2017).
Second, our research confirms that most young people are delaying their transition into the labour market by pursuing higher educational qualifications and, in the main, the young people across our sample explained that these are undertaken with the specific aspiration of improving their job prospects. However, both the quantitative and qualitative findings show that the process of finding a job, especially one which met their expected career pathways and skills levels, was sometimes harder for young people with degrees, regardless of social background, compared with those who went straight into work after upper secondary education. Clearly, we cannot be certain about the long-term effects of the challenges of finding work for young people with degrees. Current research regarding the prospective careers of graduates is somewhat outdated and contradictory (Smetherham, 2005), making it difficult to establish whether their relative struggle can be attributed to differences in the duration of the transition period from full-time education into work for this cohort of young people (4–5 years for school leavers compared with 1–2 years for graduates). However, it must be acknowledged that the long-term employment opportunities for graduates are likely to mean that they will still fare better economically over the whole of their life course (Avery & Turner, 2012). Future research is urgently needed to address these questions.
Nevertheless, our research does pose some challenges to the dominant understandings about the economic value of higher education, specifically in the immediate term and in the context of recession. The qualitative analysis provides some explanation of why this may be the case. With the contraction in the number of graduate-entry careers available, those young people who lacked the vital work experience required to enter more desirable careers, or the social and economic capital needed to access the unpaid work experience demanded by employers, found it hard to access work, or at least the kind of work they aspired to. While some chose to remain unemployed, others opted for work outside their chosen field or below their skills level. Perhaps unsurprisingly, these experiences left many of the young people with degrees rather disheartened.
Alternatively, those young people who did not delay their transition into the labour market, going straight into work from school, often seemed to enjoy having a wage and working, viewing this as the transition to becoming an adult. From the quantitative analysis, this was the most successful strategy for being in work at the age of 22–23 in 2014. In sharp contrast, however, were those who left school but did not find work, often from more vulnerable social groups coping with multiple disadvantages in terms of lack of family support, housing hardship and mental health issues.
Third, this paper contributes to our understanding of how young people are negotiating the risks and choices of neoliberal economies, in the UK in particular. In some contestation to earlier theorisations of young people polarising into two oppositional groups of either ‘exploring’ or ‘floundering’, a more nuanced picture has emerged. For many, both those school leavers and those recently graduated, ‘securing’ the future was a priority. If the cost was to work in a ‘dead-end job’, this was accepted in return for a steady income and the hope of more rewarding work down the line. For those whose ambitions to work in a particular niche were supported by parental income or job seekers’ allowance, ‘strategising’ with a period of unpaid work was often undertaken, regarded as an inevitable route in. Many in the graduate group were just ‘balancing’: juggling career aspirations with daily economic realities. For those who lack social capital, dreams and prospects continue to be ‘thwarted’ by the structures of opportunity in their neighbourhood.
Acknowledgements
This research was funded by the ESRC as part of the ESRC LLAKES centre (grant number ES/J019135/1).
