Tag Archives: higher education

Science About Science: More Scenarios

Since my last post I’ve been doing a lot of work on cleaning up the simulation and adding some additional scenarios to the mix.  After some in-depth discussion with colleague Nic Geard, co-author of the 2010 academic funding model that inspired this work, we decided that a good starting point for this would be to compare a more basic growing population of permanent academics with a population that includes insecure postdocs.

So that led to me getting to work on re-working some things to allow for four possible scenarios:

  1. Core academic funding model as written by Nic and Jason
  2. Simple growing population of permanent academics
  3. Population which includes postdocs, in which research quality does not increase the chances of promotion for postdocs
  4. Population which includes postdocs, in which research quality does increase the chances of promotion for postdocs

This last scenario in particular is intended to investigate how things proceed if we have an optimistic view — we know exactly how good each postdoc is, and we hire only the very best 15% of the current crop during each iteration.  Those in favour of the current structure would most likely argue that competition for limited jobs allows the cream to rise to the top, so we need to investigate whether that assumption holds.

So for the purposes of this post, I’ve done a quick run of the sim for each of these scenarios.  Note that the previous model by Nic and Jason investigates the time-management aspect of grant applications much more deeply — right now I’m just focusing on the mean research output for different groups of academics under each scenario.

Scenario 1: Core Academic Funding Model

If you alter the parameter settings of my version of this model and turn off all my additions — growing populations, promotion mechanisms, and the postdoc system — you end up with a scenario that’s nearly identical to the original model by Nic and Jason.  The only major difference is that in my version the bonus in research quality given to grant-holders is 1.5 rather than 1.25.

So what we see is that grant-holders, as you might expect, have a massive advantage in terms of research productivity:r_mean

Grant-holders are sitting pretty at the top there, although their output fluctuates given that various researchers of differing levels of research talent are jumping in and out of the grant-holders club each semester.

(NB: I’m aware that the non-grant holders are invisible in this graph and the next — I’m working on it.  This is all a work-in-progress, it’ll get there in the end!)

Scenario 2: Growing Population

In the second scenario, I’ve added a mechanism which adds a few academics to the population each semester.  Their research quality and initial level of time investment into grant proposals is randomised.  As in the last post we’re living in a generous society here where research funding stays in step with the growing academic population — 30% of applicants are always funded, regardless of the population size.

Perhaps unsurprisingly, the results look nearly the same as in Scenario 1:

r_mean

Just like in Scenario 1, grant-holders do far, far better than the overall population, particularly those applicants whose grant applications have failed.

Scenario 3: Postdocs, Random Promotions

So now things start getting more bizarre.  In this scenario we introduce the postdoctoral system outlined in my previous posts.  Postdocs are added in proportion to the number of grants that have been funded in a given semester, with a bit of random variation to spice things up.  New postdocs are assigned contract lengths between 4 and 10 semesters.  For the first two semesters their research quality is lower to account for their adjustment period into a new post; similarly, their last two semesters also see a drop in quality due to the time they must devote to finding a new post.

At the end of their contract, postdocs have a 15% chance of being promoted into a permanent position.  That may sound harsh, but that’s actually slightly more generous than reality (the figures I’ve seen have it pegged at 12%).  Research track record doesn’t count in this scenario — this is a world where promotions are entirely a lucky coincidence (some would argue that this is broadly reflective of reality).  Once promoted, they’re now permanent academics and can apply for grants.

So here’s a sample run of the latest formulation of this scenario:

r_mean_pdr

Much like the last set of early results, we see a drastic drop in mean research output amongst permanent academics who are grant-holders, and postdocs don’t do very well in terms of productivity despite allocating 100% of their time to research.  Overall we see no benefit to research output of the population with the introduction of postdocs, and both permanent academics and postdocs see significant variability in their research output.  My interpretation is that the introduction of a randomised population of insecure researchers is massively disruptive — each semester we don’t know how good our postdocs will be, so their output is highly variable, and we also don’t know how good our promoted academics will be, so again we see fluctuations at that level too.

Scenario 4: Postdocs, Non-Random Promotions

This scenario is particularly intriguing to me.  Nic and I had wondered whether selecting only the very best postdocs from the crop for promotion each semester would improve the picture or not.  After all if we pick the best of the best and put them in a position to get grants and thus that juicy grant-holder output bonus, surely things will go much better for our virtual scientists?

Well… not massively:

r_mean_pdr

Now you’ll see in this run that actually both the grant-holders and postdocs appear to be doing a bit better in terms of research output.  Initially this seems good, but by the end of the simulation we see that the mean research productivity for the overall population is actually slightly lower than in the random promotions case!

At first blush this seems nonsensical, but if we ponder it for a moment I think it makes sense.  While the non-random promotions do mean that we get the best of the postdoc population promoted each semester, it still means we’re highly dependent on the whims of the random-number generator — if we get a few bad crops of postdocs, in other words, we just end up with more crappy academics, and our exacting knowledge of postdoc research quality hasn’t saved us from the disruptive influence of the constant influx of new people with highly variable research output and contract lengths.

Moreover, there’s no mechanism at present for postdocs to be mentored or to mature in their research abilities — once crappy, always crappy, in other words.  In real life people may argue that the trials and tribulations of postdoc life can allow young researchers to grow into more productive academics — so that’s another aspect we need to examine.

I’ve done a bunch more runs with different random seeds and seen variations in the output that seem to support these ideas, but I’m going to spare you the 18 other graphs.  Suffice to say that the graph above seems to indicate a lucky series of postdoc recruitment drives more than anything else.  Instead I’ll keep working at it and post more when I’m more clear on my interpretations of this scenario.

SURPRISE NEW SCENARIO: Non-Random Postdoc Promotions, With Mentoring Bonus!

Wow, what a day for you lucky people!  I’ve just decided to do a quick-and-dirty scenario where we give promoted postdocs in the non-random scenario a bonus to their research quality to attempt to simulate postdocs being mentored toward success by their superiors.  Surely we’ll see a change in the fortunes of our virtual scientists now?

Well… not really:

r_mean_pdr

In fact things look almost identical, with the exception of the overall mean research output hitting a plateau rather than dropping slightly at toward the end of the sim, as we saw above.

To be fair, however, the ‘mentoring bonus’ I gave out here was not outrageously large — effectively the promoted, mentored postdocs get a 25% bonus to research quality.  What if I double that to 50%, what do we get?

r_mean_pdr

Ah-ha!  At last, a very slight positive outcome.  Mean research output overall trends ever so slightly upward over the course of this simulation run, rather than plateauing or starting to fall as above.

But I think we’d have to admit here that this is a fairly minimal outcome considering a rather generous scenario — and it’s quite likely this won’t hold in every run and some other runs may show worse results depending on the feelings of the random-number generator.  It seems reasonably consistent at a quick glance — out of 10 runs I’ve just done for this scenario, 7 out of the 10 showed a similar tiny, tiny positive trend.

So what I’ve gathered from today’s work is that increasing the average research output of academics in a postdoc scenario requires some major work: we need to recruit only the very best postdocs; and we need to ensure they get mentoring of high enough quality that they are a full 50% better than they were during their postdoc days.  Even with these powerful tools, that’s still barely enough to overcome the disruptive impact of a fluctuating population of insecure overstressed young researchers.

In real life of course, we don’t have such a transparent method of evaluating research outputs and determining the best postdocs to hire — nor do we have a population of super-mentors who can massively improve the productivity of every single postdoc.  So, if we believe the underlying assumptions of this model, then perhaps we should start to think about whether insecure research posts are a good thing for science or not.

Of course there’s a human dimension here as well — over the many runs I’ve done with the postdoc mechanism running, most simulations top out around 500 active academics at the end of the simulation, and between 5-600 total postdocs hired over the 100 semesters.  Out of those we’ll see between 70-90 postdocs get promoted, while the rest all get the sack and leave academia forever.  Do we really want to be sending these vast numbers of PhD graduates out of the academy and lose all that potential research talent?  That seems like an incredible waste, and even more so when we see how difficult it is to get a positive impact on productivity out of this structure.

Next time: I’ll keep poking at this simulation and see whether these results hold up, and I’ll be doing some other comparisons on other measures, including total research output across different groups.  Early indicators: postdocs increase total research output, and research quality across the population becomes highly unstable.  More later.

 

 

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More Science about Science

After a good few hours working on the simulation yesterday — and by ‘a few’ I mean ’15 hours’ — I have things working in a more stable configuration now.  The original simulation I’m working from was structured around a stable population, but in this simulation I’m using a dynamic population — a very dynamic one, in fact, as postdocs shuffle in and out constantly.

This has meant that I’ve been working a lot on re-writing some of the code to facilitate the addition of postdocs to the virtual research community.  Yesterday I ended up learning some new skills when I found that I needed lists of agents that retained the order of the elements within, so that was an interesting opportunity to learn more about ordered dictionaries in Python.  Presumably I might be able to make use of those in future models too, so that’s very helpful.

So, at the moment we have a nicely dynamic population of simulated academic agents in which postdocs enter the population every semester as grants are disbursed to tenured academics.  Tenured academics spend their time doing research and applying for research grants; they learn from experience and change their time allocation strategies regularly to try to maximise their success in these arenas.  The simulation starts with 100 tenured academics, and after 50 years in a typical run we end up with about ~1200 academics in total, with about a third to a half of those being postdocs, depending on the parameter settings.

These results are based on a generous virtual society though, at least compared to reality: 25% of postdocs get promoted to tenured posts at the end of their contracts; research funding is available to about 30% of academics even as the population grows massively over the years; and tenured academics holding grants get a 50% boost to their research output.  Initially I had included a ‘management penalty’ to research quality for grant-holders, to account for the time spent line-managing postdocs and administering projects rather than actually doing research, but in this generous situation I left that penalty out completely.

So, in this relatively happy situation compared to the real world, do we see any productivity gain from the mass introduction of non-tenured, research-only staff?

Well… no, not quite:

r_mean_pdr

As you can see above, once postdocs are introduced we see a relatively precipitous drop in research productivity.  Grant-holders in particular suffer a great deal on this front, despite having that 50% research output bonus.  Tenured academics not holding grants (in purple) and failed grant applicants (yellow) also dip significantly, but then rebound slightly as they adjust their time allocation strategies between grant-writing and pure research.  Postdocs enter at a lower point and then settle at a middling level of productivity, necessitated by the lowered research productivity they experience at the beginning/end of their contracts.  Their output tends to be more ‘spikey’ in general, as they shuffle in and out of the population very frequently.  Toward the end of the simulation everyone begins to converge between the 0.3 – 0.5 range or so — and in this run we can see the postdocs just overtaking the grant-holders in productivity.

Another interesting aspect here is that in a no-postdoc situation there’s a reasonable positive correlation between research quality and grant disbursement — better researchers tend to get the money, in other words.  When postdocs are introduced that breaks down completely, and there’s little to no correlation between the two; in fact on more than a few runs I’ve seen slight *negative* correlations, this in spite of the fact that in the simulation research quality is used in the ranking of applications.

So — at this stage it seems like introducing a highly volatile, insecure population of researchers into the mix creates a large amount of uncertainty, reduces overall research output, and in general disrupts things significantly.  Even in a ‘generous’ research environment we see these problems clearly.

What about in a more challenging funding environment?  Let’s imagine we’re working in biology or something, one of those fields were grant applications only succeed 10-15% of the time, and money is scarce so permanent positions are even more difficult for postdocs to achieve:

r_mean_pdr

The population is much smaller, sustaining 605 academics in this particular run and just 96 postdocs — but the research output stats look extremely similar.  Grant-holders suffer a huge drop in overall productivity, punctuated by periods of high output when they’re holding that grant, and dipping again when they dump research time into grant-writing to try to get the next one.  Failed applicants and non-grant-holders still hover around the bottom edges, de-emphasizing research as they’re trying desperately to get research money through writing bids.  Postdocs, meanwhile, wobble around the 0.4 mark most of the time, never quite in post long enough to settle in  — and given that they’re not able to apply for grants, they never can benefit from that 50% bonus to output like the senior academics can.

Again these are early results and a very cursory analysis, but it seems like what’s happening here is pretty stable even with fairly significant changes to parameter settings (I’ve done many more runs on my own to check this).  This suggests that in order to escape these problems, future versions of the simulation will need to look at more drastic changes to the research career/funding structures in order to try to address these problems.

Next time, I’ll be adding some more analytical tools to the simulation, and developing some experiments to test alternative funding disbursement methods and career structures.  As ever please do get in touch with me if you have ideas or suggestions — I’m very keen to have more people to speak to about this kind of work!

 

 

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Rethinking UK Research Funding: Presentation Slides

A bit more content on Wednesday’s Rethinking UK Research Funding meeting.  The organisers have just posted the speakers’ slides, so do check them out if you have a moment and are interested in the topic.

For my part I’ve started working on the framework for a simulation model of the impact of short-term contracts and researcher stress on productivity.  In the first instance we’ll be constructing a very simple model just so we have a system to play around with — later on we will gather data from surveys of real-world post-docs to give our simulated researchers more realistic strategies.  Then we’ll see how our agents go about coping with the stresses of trying to bid for funding while also trying to get themselves a job and some semblance of security.

Watch this space 🙂

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Rethinking UK Research Funding: Report, Part I

Yesterday I attend the Rethinking UK Research Funding conference at the University of Manchester.  We had quite a full day with plenty of interesting talks and discussion.  Since I’m starting some substantive work on this question now I kept some detailed notes during the course of the day, and I’m posting my thoughts here in case anyone finds it interesting.

I’m going to start by summarising the contents of the talks in the morning sessions.

Prof Adisa Adapagic, University of Manchester

Adisa opened the day with a look at how short-term funding affects research outcomes and integrity.  On a broader level, we know that the short-term nature of research finding has a number of effects on our research efforts:

  • Proposal preparation becomes a major time sink
  • Finding good researchers to join your projects can be difficult
  • The short timelines mean you may have a steep learning curve to climb in a short period
  • Publication pressure becomes even higher due to the time constraints
  • Reproducibility and reliability can suffer
  • Staff turnover increases
  • No continuity/job security for researchers

Reproducibility can suffer due to gaps in the data, or incomplete data, which can be difficult to deal with during a short project.  The quantity and reliability of your data may also be in question, but again that can be time-consuming to address.  These difficulties can then cause further problems during publication efforts, as the headlong rush to print can lead groups to take shortcuts.  Then we can end up with poorly-presented results based on incomplete data, and abstracts that oversell the paper’s contribution in order to make the project look good.

In order to improve these issues, Adisa proposed a few ideas:

  • Standardisation of data between disciplines
  • Use more open databases — stop clinging to your data!
  • Develop quality control methods

On the funding side, she argues that changes must be made to reduce these pressures that can lead to breaches of ethics.  Research funding is said to be ‘impact-driven’, but funding is short-term and impact is long-term (10+ years).  This leads to ethics pressures:

  • Chasing money means changing research direction — even into areas we don’t know that well
  • Publication pressures, particularly for young researchers
  • Publications suffer as we seek quantity over quality
  • Frequent self-plagiarism to produce papers faster
  • Reproducibility suffers due to poor quality/presentation of results

So what can we do to improve this situation?  Adisa offered a few suggestions on a general level:

  • Change from ‘short-termism’ to ‘long-termism’ — offer funding for longer-term projects
  • Change funding models completely to alleviate the pressure to get big grants all the time
  • Consider quality and integrity in assessing results
  • Develop ways to self-regulate our ethics
  • Push journals to get involved — their practices can exacerbate these problems

Peter Simpson — Director, N8 Research Partnership

Next up was Peter Simpson from the N8 Research Partnership, which focuses on fostering collaboration between academia and industry.  As a result his presentation focused more on funding considerations for interdisciplinary collaborations with businesses, which is not something I worry about too much but could certainly be relevant for other colleagues.

Peter summarised some of the challenges inherent to academia-industry collaboration:

  • Long-term partnerships are critical
  • First projects are often difficult, so long-term work allows better ideas to develop and flourish
  • Each side has different levels of urgency — businesses often seek quicker results
  • Openness and trust have to grow over time
  • Short-term funding can make these challenges more acute

The N8 Research Partnership itself seeks to promote research partnerships in the North of England.  The motivation here is to develop northern universities into ‘anchor institutions’ for regional economies.  In a post-industrial landscape where the former manufacturing powerhouses of the North are looking to rebuild their economies around research and innovation, the N8 sees itself as a key facilitator in building collaborations that can move this process forward.

In doing so, however, some challenges come to the foreground:

  • Culture clashes between academia and business
  • Unrealistic expectations from the business side
  • Frequent personnel changes and project closures can slow progress
  • Transparency can be an issue for the academics (we don’t like dealing with corporate secrecy!)
  • Business sometimes view academia as a cheap source of research (but less so nowadays)

In order to alleviate these issues, Peter suggested that academics should reinforce their innovative contributions by not just ‘doing what we’re told’ but suggesting and championing new ideas for these projects.  He proposed that ‘long-term thinking on short-term projects’ can remind businesses that academics are in a unique position to understand the research landscape and look further ahead to issues that will be important to businesses years down the line.

In terms of funding concerns, Peter suggested a few ways that funders could support this kind of work:

  • Undertake regular collaboration ‘health checks’
  • Ensure the continuity of lab-based scientists and project leads
  • Support the involvement of researchers with broader skill sets
  • Incorporate industrial collaboration in early-career researcher (ECR) training
  • Facilitate face-to-face meetings with higher-ups for junior research staff

Elizabeth Bohm — Senior Policy Advisor, The Royal Society

Elizabeth spoke to us about the culture of research in the UK, which was the subject of a major report from the Nuffield Council on Bioethics.  The aim of this project was to develop a constructive debate on the culture of research in the UK.  The final report was based on numerous discussion events and surveys performed in various areas of the UK research community.

When UK scientists were asked what words define good research, these were the top 5:

  1. Rigorous
  2. Accurate
  3. Original
  4. Honest
  5. Transparent

However the report also revealed a great deal of trepidation amongst the UK research community.  A few worries in particular topped the list:

  • Excessive competition
  • Funding issues
  • Research assessment methods
  • Research integrity
  • Career progression
  • Workload

In general we feel that science is extremely competitive, and that this brings out some of the best in us and also a great deal of the worst.  Funding in particular is an issue for UK academics:

  • Current trends lead to loss of creativity and innovation
  • Funding is too short-term
  • Funders are often risk-averse
  • Funds are disproportionately awarded to already-established scientists
  • Transparency issues — why are some projects not funded?

Research assessment is also a major concern, with some 58% of UK scientists stating that either they or their colleagues have been under pressure to compromise their research ethics in order to publish or receive research funds.  Young scientists under the age of 35 in particular report very high pressure in this area.  Elizabeth suggested that research institutions should provide training in good research practice from the very start of our academic careers, since it seems that the pressures of trying to establish oneself in science while under pressure to achieve quickly can lead to temptations to break ethics.

Career issues are another major area of concern:

  • Women in particular find it difficult to advance their careers
  • Culture of short-term results and productivity creates high pressure
  • Lack of time to think and start innovative projects
  • Very high stress levels in general
  • 54% of respondents think promotion systems have a negative impact on science in the UK

These results suggest that broader assessment criteria for promotion, mentoring practices within institutions, and developing good gender equality standards and guidance are critical to pushing back against these trends.

In general these core issues were reported by a very broad range of respondents, and there appears to be widespread agreement that these problems negatively impact UK science.  The report concludes that competition in science is a double-edged sword — it can push researchers to pursue loftier goals, but it also creates a great deal of stress, negative working environments, and a disproportionate focus on short-term results and quick publication.

Elizabeth points out that many of the stakeholders in UK research expressed a belief that these problems are out of their control — academics blame funders or managers, funders blame government, institutions blame academics, etc.  Thus in order to find a way forward, the entire community needs to engage in productive discussion about these problems and develop solutions that we can all get behind.

Andrew Miller — Former MP for Ellesmore Port and Chair of the House of Commons Science and Technology Select Committee

Andrew gave an interesting talk which was quite different in tone from the previous speakers.  As a former MP he spoke in the style of a politician — discussing some of the intricacies of government, relating stories and experiences while he was in government, and leaving aside the PowerPoint slides and bulleted lists.  As a consequence of this my notes here are rather less detailed, so I’ll just outline some generalities here.

Andrew seemed very aware about the issues posed by short-term funding pressures in science.  He argued that this focus on short-term results makes the research structure less robust overall — perhaps because this kind of funding environment leads to a focus on ‘safe’ research that relates to currently-fashionable problems, rather than leading the way on larger issues that await our society in the future.  He echoed previous speakers’ calls for reducing this time pressure, and expressed his belief that easing this pressure would make it easier for scientists to maintain their ethical frameworks rather than compromising themselves to obtain funding for their projects.

He spoke for some time as well about the need for researchers to engage more effectively with elected officials.  While the research councils are the people who actually disburse the funding, the structure of that system is imposed by central government — so when we have major concerns with how that structure operates, we need to lobby Parliament and government to raise our concerns.  In relation to this he discussed how the current government will be publishing a green paper soon on a proposed reorganisation of research funding in the UK.  Unfortunately this may mean some rather sweeping changes, including the consolidation of all the research councils into a single council, and of course the rumoured massive cuts in funding.  This would be a disaster, given that already the UK only spends 1.3% of its GDP on research — as compared to 7.8% in South Korea, 4.4% in Japan, etc.

I have to say I very much agree with Andrew’s statements on this front.  I’ve been very concerned that the only advocates we seem to have for universities and for research funding are our Vice-Chancellors and our research council leaders, neither of whom seem at all inclined to challenge the order of things in government.  Our union, UCU, works hard to lobby Parliament on these issues, but given the constant, sweeping, highly-damaging changes to UK higher education which the government imposes upon us all too frequently, it is difficult for the union to address research issues in sufficient depth.  With that in mind I feel we as academics need to organise some campaigns which express our discontent with the way things are going, and we must be prepared to stand up for ourselves if research funding is cut yet again.

Panel Discussion

At this point the speakers all gathered at the front of the room, where we had a brief panel discussion with questions from the audience.  Part of this was a discussion about publication norms, as a colleague in the audience (Dr Adam Glen, an outspoken advocate for post-docs) challenged Prof Adapagic on her status as an editor for two Elsevier journals — Elsevier being a highly-controversial academic publisher that charges exorbitant fees for journal subscriptions while posting absolutely enormous profit margins (by exploiting free academic labour that provides content and peer review).  She responded by expressing regret but saying that our research culture at the moment requires a certain amount of acceptance of these evil publishers so that we may advance our work.

I followed up by asking an admittedly aggressive question, pointing out that my two favourite journals at the moment (JASSS and Demographic Research) are both entirely open-access and charge no article publication fees.  I asked why we need for-profit publishers at all, when we live in the year 2015 in which server costs are minimal and basically anyone who wants to could start an open-access journal online and charge nothing for subscriptions or publication as long as they can stump up £10/month.  Prof Adapagic replied that she agreed with me entirely (!), but that she remained in a relationship with Elsevier despite being fully aware of how her work and expertise is being exploited because ‘we have to deal with this’ in our current research culture.  Elizabeth Bohm then jumped in to say that The Royal Society is hoping to improve things by experimenting with new modes of online publishing.  She said that for-profit publishers should remain in the sector because they have produced innovation in publication models in the past.

I strongly disagreed with this last point, because for-profit publishers have been completely behind the times in terms of open-access and Creative Commons publishing since their inception, and any ‘innovation’ they have produced was purely designed to allow them to continue to receive profits on the back of labour funded by the public purse while giving our community as few concessions as possible.  The chair of the session wanted to move on, however, so we left it there.

After this we had a tea break before the second session of talks, so I’m going to do the same now!  Tune in later for the second part of my excessively long summary of the conference.

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Rethinking UK Research Funding

This Wednesday I’ll be traveling to Manchester for a conference titled Rethinking UK Research Funding which is part of the University of Manchester’s Policy Week 2015.  The speakers include representatives from UCEA and Research Councils UK — I hope they are prepared for rather pointed questions from the academics in the room!  The University and College Union is also supporting the conference (Michael MacNeil will be there, for those of you familiar with the union’s names and faces).

Today the blog for the conference updated with a reading list which includes a number of interesting papers.  I wrote to the organisers with two additional citations from the ‘Simulating the Social Processes of Science’ angle, in the hopes that we might gain some more interested parties on the back of this:
Modelling Academic Research Funding as a Resource Allocation Problem

Innovation Suppression and Clique Evolution in Peer-Review-Based, Competitive Research Funding Systems: An Agent-Based Model

Update: The organisers have just written to say they will add these two papers to the website as well.

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Higher education as a consumer good

I wrote this rant some time ago, when I felt the need to write something about the current state of UK higher education.  I don’t believe I ever put it elsewhere, so I’ll put it here.

——-

While the current financial crisis looms large, the immediate consequences seem devastating enough: high unemployment; the European debt crisis; collapsing banks and governments.  Yet off in the distance, something insidious lurks: a disastrous and irrevocable change in how we view the most essential elements of our society.

We have all seen and heard by now of the student loan problem that continues to worsen in America.  As it stands now, American higher education has to face the more than $1 trillion in unpaid student loan debt that has accumulated, a staggering figure that begs the question: what happens if it never gets paid?  How, in fact, do we expect new graduates to pay, when youth unemployment continues to skyrocket and increasing numbers of new degree-holders are forced to move back home to save money?

Underlying this, however, is a deeper assumption about the value and the place of education in society.  Education is not a birthright, not something to which anyone of sufficient cleverness is entitled; education is instead a bonus, an indulgence which requires significant financial resources.  

Until very recently, this was not the way higher education was provided in Britain.  University-level education was for many years provided for free, and students were given a small stipend on which to live.  Education was viewed as an investment, the cost society should pay to produce a vital and vigorous younger generation prepared for the challenges ahead.

In the last decade, this noble ideal has eroded away.  Starting with Tony Blair’s controversial introduction of tuition fees, and now culminating in David Cameron’s tripling of those fees, students are now consumers, taking on enormous debt on the promise of receiving a marketable education.  

At the same time, further changes to higher education will alter the criteria used to approve degree-granting institutions, allowing private education providers — the very same currently plaguing America, preying on the disenfranchised and the vulnerable to get student loan money flowing in — to gain a foothold in these isles.  Meanwhile, academic staff are losing their pension benefits, watching their pay stagnate, and seeing their most valued colleagues and assistants culled, all in the name of preserving the bottom line.

All of this is worrying, but more worrying perhaps is our complacency.  We academics sit and watch, wringing our hands fitfully; at best we attempt to fight back in our usual manner: lengthy, wordy diatribes written to an audience of our peers.

But this educational crisis demands more of us than that.  For once we have to crawl out from our laboratories, our studios and studies and basements full of computers, and emerge blinking into the sunlight.  We need to stamp our feet, make some noise, and stop the further degradation of higher education into yet another venue for consumerist greed and bitter, needless competition.

Otherwise we will be left with a system built entirely on the back of student debt, providing our expertise and knowledge for the benefit of an elite who do not care about education or research or discovery.  They will shed no tears for the unprofitable arts department that is cut (or the social work department, in the case of my university).  They will think nothing of cutting unpopular subjects that do not attract sufficient students with their juicy loan checks.  They, like the bankers and the politicians, will bow before the gods of the market in supplication — caring nothing for the students who pay their salaries, and the lecturers, professors and researchers that bring in grants, publish respected papers, and attract well-moneyed students, all while working for peanuts with no retirement plan to speak of.

I moved to Britain some years ago to get my PhD, feeling a certain excitement to be entering a society where education was actually viewed as a public good.  Now, less than a decade later, British higher education stands in the balance.  I like to think that most Britons feel a justifiable pride in the educational achievements of their forebears, and yet here we are in the midst of a government that sees fit to ensure that this venerable education system will be changed forever — and for the worse.  Now, do we sit calmly and suffer in silence — or will we stand up?

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