notes on social mobility and hierarchy in HE

This is a long post. It was written whilst listening to Springsteen’s Nebraska, which somehow became Springsteen’s The Rising, before I noticed.

ONE. Open intensity.

Elsewhere I have argued against teaching intensity that

The [Treasury Productivity Plan] places universities squarely in the frontline of [] restructuring around service redesign, workforce [efficiencies], and technology/data. Here the key is productivity that emerges from a freeing up of the market, so that capital and labour can flow between sectors or across sectors, and so that new associations of capitals or businesses emerge. Here service redesign is a function of HE providers working in partnership with hedge funds, publishers, technology corporations, and so on, so that capital can be reallocated. Productivity also emerges from efficiencies that emerge inside and across existing providers, whereby human capital might be reallocated. Critically, for the health of the economy as a whole, the Plan supports

disruptive innovators and ensures competitive pressure on the tail of low productivity firms. This requires an open economy with flexible and competitive markets, where expanding firms can access the labour, land and finance they need (p. 81).

Open intensity. A productive life. Life as work. The new normal.

What then followed was the proposed structural adjustment of HE to meet the needs of the Treasury’s Productivity Plan, as articulated through the HE Green Paper and the proposed TEF. This was rooted in the need to drive productive labour and entrepreneurial activity by institutions and individuals/families, in the generation of their own social and cultural capital. However, it was also grounded in the need to overcome ability bias that affects the decision made by employers (of the work-readiness of graduates), and the ways in which market/marketable signals are transmitted between individuals, HE providers and employers. Here the State’s ability to sponsor privatisation by opening up access to, and flows of, its aggregated data (in loan-books, tax data), is crucial.

Information about the quality of teaching is also vital to UK productivity. In an increasingly globalised world, the highest returns go to the individuals and economies with the highest skills. However, the absence of information about the quality of courses, subjects covered and skills gained makes it difficult for employers to identify and recruit graduates with the right level of skills and harder for providers to know how to develop and improve their courses. (p. 19)

TEF should also prove a good deal for employers and the taxpayer. The aim is to improve the teaching that students receive, which in turn should increase their productivity and help them secure better jobs and careers. It should enable employers to make more informed choices about the graduates they recruit… (p. 21)

This deterritorialises and then creatively destroys both the classroom and the relationships that exist within it.

It is impossible to reconcile the central conditions of the Green Paper and the [HM Treasury] Productivity Plan to non-marketised/financialised pedagogic relationships. This is the prescribed direction of travel that frames the classroom economically though relations of production that subjugate people, as human capital that can be made productive through discipline.

And Warwick for Free Education also called this out.

Student choice’ is rendered little more than a token appeal and performative platitude within this context: which in truth reflects not an autonomy to manoeuvre within Higher Education as one wills, in pursuit of passions, creativity and personal flourishing, not a democratic control over the content of one’s education, but an ability to differentiate a selection of University options from a range of sophisticated branding and varying fees, functionalized by a value-for-money, career prospects oriented calculation.

Warwick for Free Education. 2016. On the Politics of Consultation.

TWO. Variable human capital and the rule of money.

The market-driven possibilities have been crystallising since the Browne Review. The desire for comparisons between academic abilities, and to evidence how participation in higher education contributes to human capital development, is almost overwhelming. However, comparisons between individuals, courses, institutions on a national and global scale reduce our pedagogy to their financialised data. For some time now, we have been informed that the market will decide, once the market has the data, grounded in student outcomes (learning gain), learning environment and teaching quality (excellence/intensity).

Learning gain measures… can also be used to support accountability, promote transparency and enable comparability of the outcomes of higher education (pp. xii-xiii)

Changes in financing of higher education have also served both to underline the importance of quality in higher education, and position student choice as a key concern for the sector. Students’ expectations in terms of their course and experience are increasingly becoming a concern of universities and policy makers, and institutions have sought to provide more information to prospective students on the value of degrees… (p. 2)

McGrath, C..H., Guerin, B., Harte, E., Frearson, M. and Manville, C. 2015. Learning Gain in Higher Education. Cambridge: Rand Corporation.

As McGettigan argues this is translated into policy that seeks to parasitise the idea of higher education by hyper-financialisation:

the transformation of higher education into the private good of training and the positional good of opportunity, where the returns on both are higher earnings. Initiation into the production and dissemination of public knowledge? It does not appear to be a concern of current policy. Such an anti-vision of higher education – let the market determine what should be offered – unfortunately meshes with a stratified higher education sector which mirrors an increasingly unequal society. (p. 2)

Potential applicants to colleges and universities will in future benefit from information on the ‘employability and earnings’ of each institution’s alumni and alumnae. I quote:

[The measures] will also help to create an incentive and reward structure at universities by distinguishing the universities that are delivering the strongest enterprise ethos and labour market outcomes for their students. (pp. 2-3)

If different degrees from different institutions result in very different levels of earnings for students with similar pre-university qualifications and from similar socio-economic backgrounds, then this might affect both student choice and policies designed to increase participation and improve social mobility. (p. 3)

McGettigan, A. 2015. The Treasury View of HE: variable human capital investment. Goldsmiths: PERC.

THREE. Towards the quantified curriculum

This offers some context for this week’s Institute for Fiscal Studies report (Britton et al.) on How English domiciled graduate earnings vary with gender, institution attended, subject and socio-economic background. The report highlights its own methodological constraints, and these are noted by Louisa Darian: the researchers only explore institutional differences across Russell Group universities that agreed, [and] had sufficient sample, to analyse (19 out of the 24 total); the researchers did not ask universities outside of the Russell Group if they would participate; the research covers a sample of just 10 per cent of all borrowers since 1998 and cannot control for the location that the graduate is now located (important given local labour market variations); it doesn’t take account of those who drop-out of university, and excludes the 15 percent of students who don’t take out a student loan; it is unable to capture which graduates in the study undertook further education or training after graduation; it is unclear how less selective institutions, that pride themselves on the support they provide students to succeed in employment, compare against more selective ones; and there is limited exploration of the lower earnings of Creative Arts students.

However, the IFS’s research demonstrates a critical moment in developing a methodology to explore, and potentially further monetise, the connections between Government-owned student loan book data and income tax records, through an emerging connection to subject of study and institution, as well as demographic data about students. In this way it develops the work proposed by the Department for Business, Innovation and Skills (DBIS) in its Small Business, Enterprise and Employment Act: Education Evaluation fact sheet. Thus, Britton et al. argue that:

For the first time we use these administrative data to characterise the properties of earnings for sub-populations of borrowers (graduates) and shows how they vary by gender, degree subject and higher education institution.

This second approach can be used to provide a conditional estimate of the earnings of graduates from different institutions or taking different degree subjects, after controlling for differences in some key characteristics of the individual or the institution and is our approximation of a value-added measure of the university by subject. We are mindful however, that selection into degree courses will mean that our estimates are not going to tell us about the causal impact of a particular degree on earnings. Further we do not have detailed information about the education achievement or other characteristics beyond gender and age of non-graduates and hence, whilst we can compare graduate earnings to non-graduate earnings, we cannot calculate a formal rate of return on a particular degree. Instead we focus on measures of variation in graduates’ earnings that are themselves of considerable value.

Britton, J., Dearden, L., Shephard, N., and Vignoles, A. 2016. How English domiciled graduate earnings vary with gender, institution attended, subject and socio-economic background. Institute for Fiscal Studies, pp. 3-4.

As Liz Morrish notes elsewhere about the DBIS Education Evaluation Fact Sheet this approach enables policy-makers to display

a discursive masterstroke, with a chaining of ‘learning outcomes’, ‘performance data’, ‘accountability’, ‘interventions’, and then serving the whole salad up as a solution to ‘social mobility’. And [this] re-designates universities as mere factories for the production of labour inputs…

Morrish, L. 2015. It’s Metricide: Don’t Do It.

However, as Britton et al. highlight, the next step is to differentiate between such factories, and their value-added contribution. A critical issue is one of unintended consequences in that policy-making that is allegedly about the interrelationship between human capital and social mobility may tend to reinforce establish hierarchies and dominant positions.

researchers have not thus far been able to assess adequately how graduate earnings vary according to the university attended. Theoretically we would expect that different institutions may add different amounts of human capital value and hence influence students’ success in the labour market.

the current information available to students strongly under reports the diversity of graduate earnings across subject and institutional choices. This is likely to be more damaging for students who come from families and communities who are less informed about potential HE choices.

A second issue is one of ability bias and signalling (people who exhibit characteristics that the labour market values like a strong work ethic or sense of conformity tend to get more education). Havergal highlighted the importance of getting better data on the relationship between education, earnings and ability bias, in order to enable employers to make more informed judgements about who exactly had work-ready skills, rather than those who merely signal the possibility.

The generic, non-subject-specific exams will be trialled by the Higher Education Funding Council for England to evaluate whether they could be used to measure undergraduates’ “learning gain” – the improvement in skills and competencies made by students during their time at university.

The results of any nationwide standardised test could also be used to compare institutional performance, and may form a key metric in the planned teaching excellence framework.

Havergal, C. 2015. HEFCE to pilot standardised student tests. Times Higher Education.

As Britton et al. note, this matters because:

Estimating the causal impact of education on earnings is challenging, due problems with ability bias driving degree choice and the difficulty in separating the productivity value of education from its signalling value.

What is required in order to modernise higher education is more than the quantification of the student, in her relationship with their institution and course, but the quantification of her whole social and educational life history, so that her productivity/learning gain, and work readiness can be made available to prospective employers. A knock-on is the quantification of the curriculum, including the labour that flows through it and from which derives the surplus value (and profitability or productivity) of the institution.

One step that would be particularly helpful would be to link HMRC data to the National Pupil Database and data from the Higher Education Statistics Agency to enable us to compare students with identical school achievement who come from higher/lower income households and reduce ability bias. With this additional data will we be able to estimate models that better control for the individual’s own level of pre higher education achievement.

FOUR. Social mobility as self-exploiting entrepreneurial activity

The social capital of the family, as the purchaser of educational services commodified as a positional good, is central to the development of policy that asserts the importance of social mobility. This means more transparency over the flows of data about individuals and their own performance, and access to those data by service innovators and entrepreneurs. These latter include the individual student and her family, which needs to build its own social and intellectual capital, in order to succeed in an increasingly competitive market. This is not just the cognitive skills that HE provides, but is also the work-ready skills that are not measured by HE.

Over and above differential access to different types of HE, individuals’ socioeconomic background may also continue to have an effect on their labour market outcomes after graduation. This might be because students from more advantaged backgrounds have higher levels of (non-cognitive) skills (see for example Blanden et al. (2007)) skills that are not measured by their highest education level, or by their degree subject or institution. Alternatively, advantaged graduates may earn more because they have greater levels of social capital and are able to use their networks to secure higher paid employment. The literature on this is quite limited in the UK but does suggest that graduates from more advantaged backgrounds, particularly privately educated students, achieve higher status occupations and earn a higher return to their degree.

In order to succeed, the student and her family must become ever-productive, self-exploiting entrepreneurs.

This appears to be especially the case for women. In comparing Cambridge, Warwick and Southampton, it was noted that:

graduates from the University of Cambridge have the highest earnings for the upper part of the earnings distribution, with more bunching across institutions at the 50 percentile level. There is much more variation at the higher quantiles. The gaps between the universities seem more pronounced for men than for women…, an effect which we will see holds up for a wider set of [Russell Group] HEPs.

With caveats, Britton et al. then uncover emergent findings related to the following.

The differences between institutions are expected when we account for the differences in the background variables that influence earnings. Mean differences in earnings across most institutions are not sizeable once we take account of the fact that different types of student sort into different institutions. (p. 35)

The quantity of variation in graduates’ earnings within an institution. (p. 35)

The figures also illustrate the large gender gap prevalent for many institutions, particularly at the top end of the earnings distribution. (p. 35)

The very low earnings of graduates from most institutions at the 20th percentile of the distribution, although this low earning share is lower than we see in the non-university population. (p. 36)

A major issue for those concerned with improving social mobility is the extent to which students from lower income families are disproportionately likely to be found in these groups of much lower earning graduates. (p. 36)

Some very locally focused institutions may struggle to produce graduates whose wages outpace England-wide earnings, which include those living in London etc. (p. 36)

There are subjects where institutions matter a great deal in immunises the student against low earnings through their subject choice. For some institutions, subject choice really does matter, while for others, less so. (p. 38)

Within institutions, subject group choice is important, especially for higher earners, with LEM (law, economics and management) graduates having higher earnings than graduates in STEM or in OTHER subjects. (p. 39)

Although institutional effects are large in these data, institution choice does not fully insure people against low earnings. (p. 39)

Subject choice matters a lot in some cases, but much less so in others. Medicine and Economics stand out in particular in terms of their higher earnings (both are subjects with relatively few graduates), while graduates of Creative Arts and – to a lesser extent – Mass Communication tend to go on to achieve lower earnings. (p. 41)

The differences in earnings across subjects get compressed once we take account of the fact that graduates with different characteristics take different degree subjects at different institutions. (p. 45)

We conclude that there is clearly less variation in graduate median earnings by institution group once one takes account of student characteristics and degree subject. (p. 47)

Darian highlights three implications for policy related to: funding (the market responsiveness of institutions in subjects offered with implications for RAB charges); student choice (the information available through the TEF and Key Information Sets as a proxy of teaching quality and value-added); and social mobility (the role of social and cultural capital, disadvantage, and admissions policies). It also appears that there are class-based implications that intersect with issues of gender, ethnicity (and racial discrimination), and regional labour market disparities (see, Britton et al., pp. 48-52).

NOTE: the class-based implications that intersect with issues of gender and racial discrimination, feed into issues like UCU’s work on gender pay gaps and the work of collectives like Rhodes Must Fall. It is here that issues of hierarchy and hegemony need to be challenged as hyper-financialisation exacerbates social injustice in the university and the curriculum.

Higher education does not therefore appear to have eliminated differences in earnings between students from lower and higher income backgrounds… while the impact of coming from a high income background is strong right through the distribution, in particular it helps protect against low earnings, and provides much greater opportunity for much higher earnings. We reiterate that our approach here does not allow us to necessarily assign causality to these relationships, due to unobservable characteristics we are unable to control for, such as intelligence or degree classification. However, on the other hand, we believe our crude measure of parental income almost certainly biases the impact down.

This process of reinforcing hierarchy and hegemony and the individual, family, subject and institutional levels, is an echo of the warning of Wilsdon et al., in terms of research metrics. In particular, where institutions are competing for fine margins in income through selective student recruitment (a form of signalling), the indicators used to separate them may drive changes in academic supply and discipline academic labour with unforeseen circumstances.

[T]he use of such indicators is felt by many to risk reinforcing a hierarchical system of institutions that may lead to simplistic comparisons. Such comparisons are hard to justify when aggregate scores show statistically insignificant differences – indeed, an over-emphasis on a small set of indicators risks encouraging perverse behaviour within and across institutions. Comparisons between institutions may lead to an unhelpful focus on the ‘top’ universities worldwide and foster a narrow definition of excellence; such a focus is not likely to be relevant to the institutional goals of universities, where the balance of research and teaching, the geographical focus and disciplinary distinctiveness may vary considerably.

Wilsdon, J., et al. 2015. The Metric Tide: Report of the Independent Review of the Role of Metrics in Research Assessment and Management, pp. 75-6. DOI: 10.13140/RG.2.1.4929.1363

FIVE. The disciplining of academic labour

The labour rights of those who work in HE (students as well as staff) for whom earnings-related data further quantifies the curriculum through performance management, is becoming the defining issue inside the university. Britton et al. make a clear point in summary about supply-side issues and the flexibility of the academic labour market.

[I]nstitutions preferring to offer more places for lower cost courses since fees do not typically vary by subject. Staffing creative arts degrees is likely to be much cheaper than staffing degrees in Economics, Law and Maths and Computer Science. These findings have implications for our understanding of the nature of subsidy of higher education. Given the relatively low earnings of graduates with degrees in some subjects, the level of public subsidy for these graduates is likely to be greater than for other graduates in other subjects, such as economics, even given the lower costs of provision for some subjects as compared to others. Making this explicit when considering the shape of higher education and in particular where any further expansion might take place would seem important.

This brings us back to the DBIS Education Evaluation Fact Sheet, which noted that the process of linking datasets would enable “a much richer understanding of the impact of education and family income on labour market outcomes and develop a better understanding of social mobility”, alongside broadening “the range of information available to parents and students”. Crucially:

The measures will enable information on earnings and employability to be evaluated more effectively which will inform student choice. This data, presented in context, will distinguish universities that are delivering durable labour market outcomes and a strong enterprise ethos for their students.

DBIS. 2015. Small Business, Enterprise and Employment Act: Education Evaluation fact sheet

This signals the subsumption of academic labour under a barrage of new public management techniques for internalising control and producing value. This catalyses ongoing sets of research outcomes that are predicated on, and which further predicate, the financialisation of education, through the ongoing market-orientation of pedagogic practice. This foregrounds the generation of a bureaucracy for impact, learning gain, teaching excellence, underpinned by strategies for enterprise and employability, with new forms of quality assurance rooted in those same predicates.

The issue then is whether teachers accept the enforced internalisation of value-added related to employability and enterprise. A risk here is that academics are led towards learning gain, and fail to notice the noose of financialisation that is being prepared, and that our hopes for enriched learning outcomes form the market’s means of hedging against future performance. Equally, there is a risk that they are disabled in addressing the ongoing reproduction of hierarchies across society and within the HE sector. Here the ramifications that HE reinforces dominant positions that are gendered, racialized and class-driven needs to be confronted. Against this, existing and emerging corporate work on learning gain, productivity and value-added, enterprise and employability, and teaching excellence, underpin the process of hyper-financialising education. If they fail to address this fact, academics risk forgetting that this is about the labour rights of students as well as themselves.

This matters because, as McGettigan notes

the coming wave of ‘education evaluation’, threatens to supplant traditional understandings of universities as communities advancing public knowledge. Current regulations governing the awarding of degrees aver that standards are maintained and safeguarded only by the critical activity of the academic community within an institution. It will be harder and harder to recall that fact

McGettigan, A. 2015. The Treasury View of HE: variable human capital investment. Goldsmiths: PERC, p. 7.

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notes on social mobility and hierarchy in HE

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