Tag Archives: research funding

Postdoc simulation analysis (spoiler alert: job insecurity is bad)

Once again I’ve been working with the academic job security simulation again.  Yesterday I’d finished altering the research funding model so that our poor agents no longer lived in a world of government largesse where population increases are always matched by an increase in funding to keep grant acceptance rates at 30%.

After tweaking things a lot last night and earlier today, I found that a funding level set at an initial 30% with a 2% increase per timestep led to research output levels very close to the previous version of the model.  The proportion of grants funded slowly drops over the course of 100 timesteps, heading from that starting 30% down to about 17% at the end of an average run.

I also added a simple retirement mechanism to this version: after 40 semesters, agents start to think about retirement and have a fixed chance (20% at the moment) of leaving the sector forever.  The result of this is a significant rise in the return-on-investment measure as the senior academics start to leave the sector; seems we had a lot of senior academics coasting along without producing much in the way of research!  Compared to the previous version, the older academics produce significantly less research-wise — I’m presuming this is because the rich-get-richer aspect of the increasingly competitive funding environment leads to a larger proportion of failed applicants deciding to bow out of the rat-race altogether.

Having taken a brief look at all this I decided to test the feedback given to me at Alife XV.  In the initial simulation, promotions had a huge positive impact on research output regardless of whether they were made entirely at random or based on research quality.  Several people at the conference suggested that this may no longer be the case if I implemented a more constrained funding system.

So, I ran the simulation 800 times across a range of parameter values with limited funding and retirement mechanisms both turned on.  I then used my old pal, the software called Gaussian Emulation Machine for Sensitivity Analysis (GEM-SA), to crunch the numbers and come up with a statistical model of the agent-based model, and then ran that 41,000 times.  The final output of interest is the total research produced across the agent population at the end of the simulation.  The analysis looks like this:

gemsa1-cropped

Turns out my colleagues were onto something, which I expected (and hoped for, because otherwise that might mean the simulation might have some problems).  In this version of the sim altering the chances of promotion for postdocs does little on its own, accounting for only 0.11% of the output variance.  This factor interacts with the level of stress induced by impending redundancy, however, and this interaction accounts for 11.03% of the output variance.

The largest effect here is driven by Mentoring levels — the amount of research boost given to newly-promoted postdocs.  Second-largest is the stress caused by looming redundancies.  This is a significantly different result from the previous version of the simulation — I’ll run a parameter sweep of promotion levels later as well, to get the complete picture.

For the sake of completeness, here’s the graph of the main effects produced by GEM-SA:

gemsa2-cropped2

Tomorrow I’m hoping to do a similar analysis, but this time leaving Mentoring at a lower, constant level and varying a slightly different set of parameters.  My poor laptop needs a break for a little while, it’s pumping out crazy amounts of heat after all this number-crunching.

My other, larger task is to come up with a way to measure the overall human cost of this funding/career structure.  I think I can make a good case at this point that job insecurity is not great for research output in the simulation, given that across many thousands of runs I’ve yet to find a single one in which insecure employment produces more research for the money than permanent academic jobs.  I’d to be able to compare scenarios in terms of human cost as well, so perhaps taking a look at total redundancies after 100 semesters as the final output for some analyses might give me some ideas.

That aside I think I’ve made a decent start on an extension of the conference paper.  Thanks to all those who came to the talk in Mexico and gave me some useful feedback!

 

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Returning to the postdoc simulation

I’ve been doing some tests on my postdoc simulation today. As suggested by colleagues at Alife XV I’ve implemented a funding system in which the total available funding increases at a lower rate than the population, leading to increased competition.

Total research output under these conditions does increase pretty significantly — however, return-on-investment remains negative, meaning we still would get more for our money by hiring half as many permanent researchers instead of postdocs. Postdocs are still the group producing the lion’s share of the actual scientific work, while permanent academics nearly all of their research time to grant-writing.
 
The return-on-investment is less negative than under the previous funding condition, but bear in mind the simulation currently doesn’t account for redundancy payments or training costs for new postdocs.  In these runs results were showing a return of -2.5 papers per unit of funding invested as compared to a postdoc-free scenario; in the unlimited-funding condition with the same settings, the figure averaged -3.6/unit.  Redundancies were higher in this condition, about 150 more each run than in the unlimited funding condition.  This could change significantly, however, depending on the final formula I use for year-on-year research budget increases, given that postdocs’ fates are directly tied to how much research money is available.
 
The big question is whether under this condition we still see no improvement in research output or return-on-investment when candidates for promotion to permanency are selected by quality rather than randomly. At this early stage there’s little difference — I’ve only done a few runs, but non-random promotions have not demonstrated a significant difference from random ones in either total output or ROI.  We’ll see if that changes when I do a larger sequence of runs.

My next test after that will be to try this version of the simulation with much longer runs to see if things stabilise at all, or whether the uncertainty introduced by the high-turnover postdoc population continues to drown out any attempts at rewarding high achievers with more grants.  We’re already looking at 50-year runs here, though, so if after two centures of terrible job security we see hugely better cost efficiencies I’m still not sure that’s a massive win for the postdoc side of things.  But I suppose that rests on whether you care about the human costs or not.

There’s a lot of tweaking to be done so these are very early days, but it’s an interesting first result.
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Funded PhD opportunity at Teesside

Fully-funded PhD opportunity available! I’m looking for someone interested in working on agent-based modelling for healthcare applications. No fees and £20K stipend. These are four-year positions and you will be asked to contribute up to six hours per week of teaching (tutorials/demonstration only, no lectures), which is more work but also good for the CV. Click here and filter under ‘Computer Science’ to see my project.  For more about me, check out the various pages on this blog or my staff profile at Teesside.

Project description: This research will focus on the application of Agent-Based Modelling techniques to human social systems, with particular emphasis on digital health applications. In the context of public health, agent-based models can help us understand the complexities of health policy implementation and service delivery by modelling the multiple interacting processes underlying the health system. These models will investigate challenges in health and social care service delivery across a variety of spatial and temporal scales – from short-term studies of demands on accident and emergency services, to longer-term explorations of the pressures facing social care over the next several decades. Our multi-disciplinary team will work with members of the School of Health and Social Care here at Teesside, along with external collaborators and stakeholders. The project would be suitable for a graduate with a background in Computer Science, Artificial Intelligence, Statistics or Complexity Science with an interest in Public Health/Healthcare applications.

ACADEMIC FRIENDS: Please tweet/share this as widely as you can!

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Paper Submitted To Alife XV

I’m happy to report that I’ve recently submitted a first paper on the postdoc simulation I’ve been plugging on these pages for some time.  I’ve been working in collaboration with Nic Geard of the University of Melbourne and Ian Wood, my officemate at Teesside.

The submitted paper is titled Job Insecurity in Academic Research Employment: An Agent-Based Model.  Here’s the abstract:

This paper presents an agent-based model of fixed-term academic employment in a competitive research funding environment.  The goal of the model is to investigate the effects of job insecurity on research productivity.  Agents may be either established academics who may apply for grants, or postdoctoral researchers who are unable to apply for grants and experience hardship when reaching the end of their fixed-term contracts.  Results show that in general adding fixed-term postdocs to the system produces less total research output than adding half as many permanent academics.  An in-depth sensitivity analysis is performed across postdoc scenarios, and indicates that promoting more postdocs into permanent positions produces significant increases in research output.

The paper outlines our methodology for the model and analyses a number of different sets of scenarios.  Alongside the comparison to permanent academic hires mentioned above, we also look closely at unique aspects of the postdoc life cycle, such as the difficult transition into permanent employment and the stress induced by an impending redundancy.  For the sensitivity analysis we used a Gaussian process emulator, which allows us to gain some insight into the effects of some key model parameters.

The paper will be under review for the Alife XV conference very shortly, so I don’t want to pre-empt the conference by posting the full text here.  If — fingers crossed — it gets accepted, I’ll post a PDF as soon as it’s appropriate.  If you want a preview or are interested in collaborating on future versions of the model, please get in touch!

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Science about Science: Does Promoting More Postdocs Help?

Just a brief one today — I’ve been playing with parameter settings on the funding/careers model, particularly the impact of postdoc promotions.  In the base scenario, postdocs (referred to as PDRs here: Post-Doctoral Researchers) have about a 15% chance of getting promoted to a permanent position.  Here’s a sample run at the base settings (which includes the mentoring bonus added last time):

r_mean_pdr2

I’ve finally worked out how to fix the legends on these graphs!  Now let’s compare to a scenario in which 50% of postdocs get promoted:

r_mean_pdr2

 

Note that the mean productivity of grant-holders (the green line) is overall a bit higher than in the 15% case.  The productivity of promoted postdocs (the orange line) also tracks higher over time than in the 15% scenario.

Now let’s try 100% promotion chance:

r_mean_pdr2

Here the productivity of grant-holders and promoted PDRs is higher than in either the 50% case or the 15% case.

So does this mean that promoting more postdocs is our ticket to a more productive research community?  Well, in this virtual academia it seems to help — but still we’re seeing a lower level of productivity than in the postdoc-free scenario.  Not to mention that there’s still quite a bit of statistical work here to be done to determine how significant these effects are — but it’s an interesting result from today’s work and one I hope to address in the paper, assuming that the analysis bears it out.

 

 

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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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Modelling Research Careers: Very Early Results

I’ve managed to get that research careers simulation up and running today — a very early version, mind you.
Each time grants are disbursed to our simulated academics, the top 10 applicants receive a postdoc.  Postdocs work full-time on research and do not apply for grants.  At the beginning and end of their contracts (which range from 2-5 years long) their output is reduced significantly to account for stress caused by entering a new job or searching desperately for a new one, respectively.  Postdocs have a 10% chance of being made permanent at the end of their contracts; if they’re unlucky then they simply drop out of the system altogether (I haven’t implemented multiple contracts yet).
So what we have is a very volatile situation right from the beginning — we’ve got lots of people on short contracts, most of whom are under significant stress for part, or even all, of said contracts.  Postdocs are constantly being shuffled out of the system and replaced with new postdocs, so the research environment is being filled up with stressed-out people with highly variable levels of research talent — and talented ones are just as likely as crappy ones to be booted out the door at the end of their contracts.  Permanent academic jobs are in short supply, so most postdocs never get a chance to contribute to grant applications.
The results are rather more drastic than I anticipated.  Here are the results for mean research output from a quick run of the simulation including postdocs:r_mean
Contrast that with the below, which shows the mean research output from a run with the same initial conditions but without postdocs in the simulation:
r_mean
 
Mean research output across all categories, no postdocs: ~0.61
Mean research output across all categories, postdocs added: ~0.34
 
Given I wrote all this code in a day, these results are highly speculative at best — but I’m hoping that the final version will give us a decent representation of the impact of competitive funding systems and job instability on academic research quality.   At this point I’m just pleased to see it up and running!
There’s still a ton of work to do: double-checking everything, adding in detailed stats collection on the postdocs, then revamping the funding disbursement functions to tie grants and postdocs together explicitly so I can measure output by project/PI.  There’s a few other bits I really want to do, like implementing multiple contracts, etc.
I’ll keep posting progress reports as I go… please wish me luck!
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Modelling Research Careers: early thoughts

As some of you know already, because I keep going on about it, or worse, trying to drag you into it, I’m hoping to kick off a major project on simulating the research career structure and its effect on scientific productivity.  Having done my time as a postdoc, like many of us, I’m pretty convinced that the current pyramid-scheme structure of academia is not only sub-optimal, but fundamentally damaging, particularly toward academics from marginalised groups.

My first attempt at building an early-stage model of research careers is taking inspiration from Geard and Noble’s paper on Modelling Academic Research Funding as a Resource Allocation Problem.  In this paper the authors construct an agent-based model in which simulated academics attempt to obtain grant funding — frequently a prerequisite for any kind of decent job security these days — by devoting a certain portion of their time to writing proposals for competitive funding bids.  Agents have an underlying research productivity level which influences the perceived quality of their proposal when it comes under review.  At the review stage, top-ranked proposals are funded, and funding is then given to agents (which manifests as an increase in their research productivity).  Agents produce research outputs according to their productivity, whether or not they are holding a grant, and how much research time they have available (given that some period of time must be spent writing grant proposals).

In the end the paper demonstrates that the current system of grant funding is inefficient — huge amounts of time are spent on obtaining grants, which takes away from research productivity, and since most grant proposals are unsuccessful we end up with a lot of time wasted.

What I’m proposing at this stage is to modify this framework to include agents who are on fixed-term research contracts.  Now, presenting a simplified version of the post-doc experience would require a few changes:

  • Agents should be on fixed-term contracts — in the UK about 2/3 of all research-active academics are on FTCs, so the model should reflect this
  • Many postdocs are given much more time to devote to research in general, being largely free of time-consuming teaching or administrative duties
  • Postdocs need to spend significant time during the end of their contracts looking for a new job
  • New postdocs may lose some productive time due to needing to acclimatize to their new working environment
  • Postdocs are often tied to specific projects, and their contracts live and die as the project does

At the moment I’m envisioning a version of the model where we add significant new elements to try and work postdocs into this:

  • FTCs can vary in length from 2 to 10 semesters — as do projects
  • FTC agents don’t contribute to grant proposals, nor do they submit proposals for review (in reality some do contribute, but at least here in the UK postdocs are not considered proper academics by the Research Councils and thus cannot apply)
  • When the postdoc first starts work, 30% of their time is spent adjusting to the new environment, getting to know people and the work that needs doing
  • When the postdoc’s contract is due to end, again they lose 30% of their time due to job-hunting, interviews, and general stressing out
  • When grants are disbursed, the top 10 funded projects are allocated a postdoc with a contract length matching the grant length
  • Postdocs add their research productivity to the academic holding the grant
  • When a postdoc’s contract ends, at the end of the current semester they’re given a 10% chance of being made permanent — allowing them to then conduct their own research programmes, apply for grants and get their own postdocs
  • Postdocs who don’t get made permanent can transfer to another project if one gets funded and needs a postdoc.  If that doesn’t work they drop out of the research population

At the end of a run — say, 100 semesters like in the original model — I’d be looking at overall research productivity, research productivity in postdocs vs permanent faculty, the career history of the postdocs, and the distribution of grant income across the population.

What I’d expect to see is an elite set of agents who started collecting post-docs early, then snowballed their way into a series of successful grants and even more postdocs, while the rest of the population flounders, and is at a serious disadvantage compared to faculty members on the exploiting-the-postdocs train.  As for the postdocs, only a tiny number would be made permanent and thus benefit from their efforts, while a large number would end up on multiple FTCs or dropping out of the population altogether.  All of this would be broadly reflective of reality.  If that were to happen then perhaps this model could provide a good platform for investigating alternative methods of organising research careers, and for examining how different funding disbursement methods affect the fate of postdocs.

What I’m hoping to get out of this in the main is a model which demonstrates the interplay between precarious employment in academia and our current competitive methods of disbursing funding.  Modelling research as a resource allocation problem fits this well, I think, because postdocs are placed under particular pressure to find their next posts in a limited time while being expected to produce substantial research output.

Now as I write this I’m very aware there’s a lot of things at play here and this model is already in danger of being over-complicated.  Even still there’s a number of other factors I’d like to try to address at some later stage, most particularly the impact of stress on research output (from failing to get a grant, worrying about job security, etc.) but let’s just see if this works at all first!

But first: please do chime in if you can and let me know what you think, where I’ve gone wrong, etc.

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Rethinking UK Research Funding, Part II: The Vengeance

Time for another long blog post summarising yesterday’s Rethinking UK Research Funding conference.  After the first session we had another set of speakers covering a range of topics, including a representative from UCU and our perennial nemesis, UCEA (Universities and Colleges Employers Association).  As you might expect there were some interesting divergent viewpoints.

Dr Ruth Gilligan — Athena SWAN Manager, Equality Challenge Unit

Ruth began her talk by talking us through the basics of the Athena SWAN charter, which is about creating a commitment to gender equality across higher education institutions.  She laid out some core principles for institutions to follow:

  • Recognise the talents of all
  • Advance gender equality
  • Recognise disciplinary differences
  • Tackle the gender pay gap
  • Remove obstacles to sustainable careers
  • Address short-term contract issues
  • Tackle discrimination against trans-gender people
  • Demonstrate commitment at senior levels in the institution
  • Make necessary structural and cultural changes
  • Consider intersectionality

Institutions are expected to collect data on all these elements and critically analyse the results.  They should work to identify reasons why certain groups may be excluded or underrepresented in the institution, develop action plans to address these reasons, and show progress over time.

Of particular interest here is the requirement to address short-term contracts.  I have seen evidence in the past that short-term contracts affect female academics more severely than males, and so when addressing gender equality concerns short-term contracts become a crucial ingredient.  Funding organisations have a crucial role to play here — the focus on predominantly short-term funding initiatives pushes the number of short-term contract staff higher and higher, so moving away from this short-termism at the funding council level could have a strong impact.

Ruth also showed some current figures, which showed the number of institutions and departments which have been awarded Athena SWAN Bronze, Silver, or Gold awards.  Quite a few institutions and departments have Bronze awards, far fewer have Silver, and only seven departments in the whole of the UK have reached Gold level — and no institutions at all.  So there’s still quite a lot of work to be done here.

I couldn’t help but think during this talk that later in the session we would have a representative from UCEA.  This is an organisation that has decided to try to force academics to accept a 1% pay rise yet again, on the back of a threat to refuse to work with us on addressing the significant gender pay gap in the sector unless we accept the offer without protest.

Given that UCEA represents all the employers, then if they refuse to work with us on the pay gap, the employers would all be dismissing a core principle of the charter as Ruth had outlined.  So surely, if that were to happen, the awards granted across the sector to date should be removed, and any funding linked to those awards rescinded?

Iain Cameron — Head of Research Careers and Diversity, Research Councils UK

Iain started off with a chart listing ‘pros and cons’ for short-term funding programmes.  I could summarise by saying the ‘pros’ column consisted of points that benefit employers and the research councils — ‘agility’ in the sense of being able to respond to research demands, flexibility for the employers, etc.  The ‘cons’ raised points that we’re all quite familiar with by now — career uncertainty, lack of career development and training time, research time lost to job searches for short-term researchers, and the general unreliability of redeployment arrangements in universities.

Iain acknowledged that the sector is packed to the gills with short-term workers with uncertain futures (21,000 PhDs granted each year, 45,000 post-docs around at any given time).  He laid out the RCUK vision for post-docs which he feels would improve their lot:

  • An overarching aim to support excellent researchers
  • Career support from beginning to end of a contract
  • Mentoring from senior colleagues
  • Networks to enable sharing of experiences
  • Broadening the definition of ECRs to ensure this assistance is widely available
  • Encouraging development of independence in research
  • Pushing institutions to treat post-docs as ‘proper employees’

Note that none of these points really involves RCUK changing anything about their funding structures or tying their funding to progress on short-term contracts from institutions or similar.  In my view these actions are far from sufficient and do not demonstrate a real commitment to addressing the problem.

He moved on then to a discussion of the post-doc academic fellowships available at some universities, in this case Leeds and Birmingham.  These fellowships are generally for five years and include substantial mentoring and career support as well as protected research time.  He called them ‘tenure-track equivalent’, which is of course not true, as tenure is a real thing with a legal framework behind it which does not exist in the UK at all (thanks, Thatcher).  Personally I’d be more excited about these fellowships if they were commonplace, rather than being offered at only two of the many dozens of HE institutions in the country.

After this Iain discussed the PhD situation for a little while, noting that PhDs are being granted to many more people now than even a few years ago, and that there is concern about where these people can make use of these skills when academic jobs are so incredibly scarce and competitive.  He pointed out some figures from businesses, who seem moderately enthused about hiring PhD grads, who they say provide innovative perspectives and valuable skills.  I don’t doubt that this is true, but unfortunately the great majority of PhD students take on the challenge because they want an academic job, not so they can become a juicier prospect in the business world.

In general my personal reaction — as you’ve probably gathered — is that this presentation seemed to acknowledge the problems presented by short-term funding regimes and their effect on the research career structure, but offered very little in the way of solutions on the RCUK side of things.

Michael MacNeil, National Head of Bargaining and Negotiations, University and College Union

Next up is Michael MacNeil, long-time high-level UCU official and a nice chap who I’ve spoken to a number of times about fixed-term contracts in UK academia, so I was pleased to see him focusing on that topic during this talk.  He set out to discuss the HE sector record in supporting sustainable research careers (spoiler alert: it’s not good), and to lay out the case for moving away from fixed-term contracts in universities and for institutions to take responsibility for their researchers.

He noted that higher education is the third worst sector in the UK for insecure employment, coming in just below the hospitality industry and retail.  Two-thirds of the sector’s entire research base is employed on fixed-term contracts, and out of those 57% are for two years or less, and 29% are for one year or less.  While the Fixed-Term Contract Regulations 2002 do provide some protection for fixed-term workers, in practice they’ve made very little difference, as it remains straightforward for employers to deny permanency to fixed-term employees (I can vouch for this fact personally).

Michael then outlined why this issue matters, and why it creates enormous waste and inefficiency in the sector:

  • The human cost in stress and ill health, which also affects productivity
  • Unfairness, particularly towards women and minorities who are disproportionately affected by these trends
  • Great deal of time wasted as fixed-term researchers need to spend time searching for jobs or begging for a contract extension
  • Time and funds wasted on providing training for a constant influx of new researchers rather than retaining talented people within the institution

He also described a few possible actions that could be taken by funding councils and employers to reduce the wastage here:

  • RCUK could fund longer grants to reduce short-termist thinking
  • Tie the disbursement of funds to institutions providing ‘bridging funds’ to carry researchers between projects
  • Institutions themselves can move to open-ended contracts
  • Redeployment procedures exist at many institutions but are notoriously ineffective — fix them!

He noted as well, as Elizabeth Bohm said in the previous session, that the sector as a whole needs to stop pointing fingers and work together in concert to address the impact of short-termism on research and researchers.  He asked for employers to:

  • Work with UCU to push for stable funding and thus stable employment
  • Abandon their efforts to undermine the employment rights of fixed-term researchers
  • Negotiate policies that mitigate insecurity and promote continuity of employment
  • Stop passing the buck — all parts of the sector need to take responsibility

The second point above relates to when UCU discovered that UCEA reached out to government in secret to push for the removal of bargaining rights for workers reaching the end of a fixed-term contract, effectively making it far easier to make fixed-term researchers redundant.  They did this without discussing the issue with UCU, and at the same time as they were receiving Freedom of Information requests from UCU asking for details on their fixed-term workforce.

Personally speaking, the ‘stop passing the buck’ comment applies to our own community as much as it does to RCUK or UCEA.  While I was heavily involved in my union branch, I saw time and time again how academics in positions of power felt perfectly capable of denying help to young researchers on fixed-term contracts who were doing good work and were asking for some security.  That indicates to me that we are also quite happy to pass the buck.  That needs to stop if we are to have our sector regain its health.

Michael alluded to this at the end of his talk, when he discussed the gap in opinion and action between senior, established academics and younger academics seeking to build a career.  Established academics often don’t really see the fixed-term contract issue as relevant to themselves, even despite the obvious impact of lost research time and productivity due to this nonsensical structure.  As Michael said we need to band together as a community and understand that this issue affects the health of our entire sector and our research productivity, and that by addressing it we all benefit.

Laurence Hopkins — Head of Research, Universities and Colleges Employers Association

Laurence’s talk got off to an auspicious start when the chair of the session introduced him as a ‘colleague’, prompting laughter from the room.  “‘Colleague’ might be a bit of a stretch!’ remarked someone in front of me, causing more chuckles.  People simmered down after a moment, leaving Laurence to get started.  He opened by saying ‘I’m from UCEA… I’d explain more about what we do, but you might start booing me’.

Laurence started by discussing the massive increase in research-only staff compared to research/teaching staff (lecturers and above).  Since 2006 there has been a 14% increase in the number of research-only staff.  Out of these researchers some 19% take home a salary above £42k, compared to research/teaching staff where 80% take home more than £42k.

From here he started talking about the situation in some other countries.  UCEA apparently undertook some work with trade unions and employers associations in HE elsewhere to compare how badly researchers are faring worldwide.  As it happens the situation in Italy looked particularly bad — researchers average 6.2 fixed-term contracts before moving on or getting a permanent job, and 10% of researchers have between 13 and 30 contracts (!).  In a survey 63% of researchers in Italy said they ‘can’t imagine their professional future’.  Salaries are also significantly lower in Italy than in the UK, similar to other continental European nations.

While it was certainly striking to see those figures, I couldn’t help but think Laurence was doing his best to distract us from exactly how poor the UK figures are.  It may be true that other places have it even worse, but that doesn’t make what we’re doing excusable.  Similarly, he noted that Finland seemed to be the one place that has avoided an explosive growth in fixed-term researchers — they’ve kept a more balanced division in HE between researchers and permanent staff.  Of course he neglected to mention that Finland has worked to introduce tenure-track pathways which carry researchers smoothly into permanent posts, which is something UCEA could do, but clearly they have no interest in taking that step.

Now we diverged slightly into a discussion around the overproduction of PhD graduates, a topic which had popped up briefly in some earlier talks.  He noted that the current oversupply is not sustainable — we’ve had a 46% increase in doctoral grads since 2006, and the majority of these grads want an academic career.  Unfortunately, as we all know, academic careers are incredibly difficult to come by — the last figures I saw showed that only 12% of PhD grads get a post-doc, and out of those less than 10% are able to obtain a permanent academic job.  Meanwhile, despite Iain’s positive words about PhD graduates’ suitability for the business world, there are very few PhD-level researchers in business in the UK, and the numbers have actually dropped recently from 2.9% to 2.6% of PhD graduates.

As the talk meandered back toward researchers, Laurence shared the recommendations made by the UCEA report:

  • Review contractual arrangements for researchers
  • Manage researcher expectations
  • Ensure balance between research duties and teaching/admin duties
  • Improve status of research staff within institutions
  • Establish platforms for dialogue about research careers

Again these recommendations are profoundly disappointing.  None of these require any substantive action from UCEA itself — they’re just ‘reviewing’ or ‘improving’, no new solutions are being presented, no changes to the current arrangements are suggested.  I also suspect that ‘managing researcher expectations’ basically boils down to warning researchers ‘Hey, you know the conditions of your job will be terrible, right?  Better prepare yourself for that!’  Again one can’t look at these recommendations and believe that UCEA has any interest in actually addressing short-term contracts beyond a few token gestures.

Finally, Laurence finished up by asking whether our sector wants research-only careers that are distinct from academic careers.  Given that this would officially split fixed-term researchers into an exploited underclass with no hope of real advancement or prestige, I’d like to offer a resounding ‘NO’ in response to that question.

Panel Discussion

As the morning drew to a close our speakers gathered at the front again for questions.  One that caught my attention was a gentleman in front of me who asked Ruth what sort of ‘teeth’ are embedded in the Athena SWAN awards — in other words, what actually happens when an institution violates the principles they’re supposed to uphold?  Ruth said that so far no institutions or departments have had their awards rescinded, and that institutions are asked to send progress reports and analyses and demonstrate how they’re moving forward on gender equality and related issues.

Having seen what I’ve seen while working for the union, I suspect that said institutions and departments have got their spin doctors working overtime here.  I’ve seen more than my share of actions which should surely result in the loss of an Athena SWAN award, if departments truly are supposed to act on short-term contracts and so forth.  I wonder if there should be a campaign within the union to begin reporting these incidents directly to the Equality Challenge Unit?  Perhaps that would lead to a greater actual adherence to the principles laid out in the charter if there was an actual threat of awards being rescinded due to exploitative behaviour from departments and institutions.

There was also some discussion about why post-docs are not treated like academics when it comes to grant applications (a question posed by Dr Adam Glen again, who came wearing a home-made T-shirt saying ‘Why can’t a post-doc be a PI?’ on the front and ‘Post-docs are academics!’ on the back).  There was general agreement in the audience that there’s no reason why post-docs shouldn’t be allowed to submit grant applications.  Concerns were also raised that this strange restriction persists because the research councils are so dedicated to the idea of disbursing money almost exclusively to large, established groups who are seen as ‘safe bets’, and that keeping post-docs out of the running fits this agenda.  Adam suggested that small grants which have been cut in recent years should be re-established, as they allow post-docs to develop an independent research programme and become experienced academics.

Another member of the audience proposed that the Research Council could make progress on the fight against fixed-term research contracts by actually employing the researchers themselves on open-ended contracts as a sort of talent pool.  Projects that were funded would then be given researchers from the pool with the requisite domain knowledge, who would then return to the pool at the end of the project and await their next assignment.  This idea came up a few times during the day, and while it does have some attractive elements, I do wonder whether it just serve to divide permanent academics and post-docs even further.  I’d much rather see a system put in place which facilitates a transition from post-doc to established academic, and that allows researchers to remain as part of an institution independent of grant funding.  The system he was proposing would allow institutions to freely exploit researchers while taking no responsibility whatsoever, which is not a power I’d particularly like to give UCEA at this time.

Thoughts

In general the day provoked some vigorous discussion, and I enjoyed hearing what people had to say on these issues.  Most of all I was pleased to see how much people were engaging with the issues facing post-docs and fixed-term researchers in general, which is a topic I was focusing on in my previous work for the union.

However, the responses from some of the speakers were sadly rather predictable.  RCUK and UCEA both seemed to pay mere lip-service to the problems raised at the conference, offering nothing more than discussion forums and mentoring arrangements rather than actual significant, structural change.

I guess these talks reinforced the scale of these problems, and how they seem to be getting worse rather than better.  As several speakers said during the day, the research community as a whole needs to start taking responsibility if we are to make any progress, rather than passing the buck and pretending we’re all powerless to stop any of this.  Funding councils are in a position of great power, where they can demand change of institutions who seek to receive funding; UCEA could stop undermining researcher’s employment rights and engage with UCU in tackling short-term contracts and gender inequalities; and academics ourselves could stand up for each other and stop just putting our heads down and pretending the post-docs are doing just fine and they should really stop whining.

Put like this it all sounds pretty dire, but in fact I felt the day provides a bit of hope.  At least we had people representing all these parts of the research community in one room talking about these issues and challenging one another to develop new ideas.  That’s a start, and something worth building on.

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