Initial Reactions to HEFCE’s ‘Initial decisions on REF 2021’

This lunchtime HEFCE have announced some more “Initial Decisions” on REF 2021, which I’ve summarised below.

Slightly frustratingly, the details are scattered across a few documents, and it’s easy to miss some of them. There’s an exec summary,  a circular letter (which is more of a rectangle, really), the main text of the report that can be downloaded from the bottom of the exec summary page (along with an annex listing UoAs and further particulars for panel chair roles)… and annex A on a further consultation staff return and output portability, downloadable from the bottom of the circular letter page.

I’ve had a go at a quick summary, by bullet point theme rather than in the order they appear, or in a grand narrative sweep. This is one of my knee-jerk pieces, and I’ve added a few thoughts of my own. But it’s early days, and possibly I’ve missed something or misunderstood, so please let me know.

Outputs

  • Reserve output allowed where publication may not appear in time
  • Worth only 60% of total mark this time (see scoring system)

I think the reduction in the contribution of outputs to the overall mark (at the expense of impact) is probably what surprised me most, and I suspect this will be controversial. I think the original plan was for environment to be downgraded to make way, but there’s a lot more demanded from the environment statement this time (see below) so it’s been protected. Great to have the option of submitting an insurance publication in case one of the in-press ones doesn’t appear by close of play.

Panels/Units of Assessment

  • Each sub-panel to have at least one appointed member for interdisciplinary research “with a specific role to ensure its equitable assessment”. New identifier/flag for interdisciplinary outputs to capture
  • Single UoA for engineering, multiple submissions allowed
  • Archaeology split from Geography and Environmental studies – now separate
  • Film and Screen Studies to be explicitly included in UoA 33 with Dance, Drama, Performing Arts
  • Decisions on forensic science and criminology (concerns about visibility) due in Autumn
  • Mapping staff to UoAs will be done by institutions, not HESA cost centres, but may ask for more info in the event of any “major variances” from HESA data.

What do people think about a single UoA for engineering? That’s not an area I support much. Is this just tidying up, or does this has greater implications? Is it ironic that forensic science and criminology have been left a cop show cliff-hanger ending?

Environment

  • Expansion of Unit of Assessment environment section to include sections on:
    • Structures to support interdisciplinary research
    • Supporting collaboration with “organisations beyond higher education”
    • Impact template will now be in the environment element
    • Approach to open research/open access
    • Supporting equality and diversity
  • More quant data in UoA environment template (we don’t know what yet)
  • Standard Institution level information
  • Non-assessed invite only pilot for institution level environment statement
  • Expansion of environment section is given as a justification for maintaining it at 15% of score rather than reducing as expected.

The inclusion of a statement about support for interdisciplinary work is interesting, as this moves beyond merely addressing justifiable criticism about the fate of interdisciplinary research (see the welcome addition to each UoA of an appointed ‘Member for Interdisciplinarity’ above). This makes it compulsory, and an end in itself. This will go down better in some UoAs than others.

Impact

  • Institutional level impact case studies will be piloted, but not assessed
  • Moves towards unifying definitions of “impact” and “academic impact” between REF and Research Councils – both part of dual funding system for research
  • Impact on teaching/curriculum will count as impact – more guidance to be published
  • Underpinning work “at least equivalent to 2*” and published between 1st Jan 2000 and 31st Dec 2020. Impact must take place between 1st Aug 2013 and 31st July 2020
  • New impact case study template, more questions asked, more directed, more standardised, more “prefatory” material to make assessment easier.
  • Require “routine provision of audit evidence” for case study templates, but not given to panel
  • Uncertain yet on formula for calculating number of case study requirements, but overall “should not significantly exceed… 2014”. Will be done on some measure of “volume of activity”, possibly outputs
  • Continuation of case studies from 2014 is allowed, but must meet date rules for both impact and publication, need to declare it is a continuation.
  • Increased to 25% of total score

And like a modern day impact superhero, he comes Mark Reed aka Fast Track Impact with a blog post of his own on the impact implications of the latest announcement. I have to say that I’m pleased that we’re only having a pilot for institutional case studies, because I’m not sure that’s a go-er.

Assessment and Scoring system

  • Sub-panels may decide to use metrics/citation data, but will set out criteria statements stating whether/how they’ll use it. HEFCE will provide the citation data
  • As 2014, overall excellence profile, 3 sub-profiles (outputs, impact, environment)
  • Five point scale from unclassified to 4*
  • Outputs 60, Impact 25, Environment 15. Increase of impact to 25, but as extra environment info sought, has come at the expense of outputs.

There was some talk of a possible necessity for a 5* category to be able to differentiate at the very top. but I don’t think this gained much traction.

But on the really big questions… further consultation (deadline 29th Sept):

There’s been some kicking into the short grass, but things are looking a bit clearer…

(1) Staff submission:

All staff “with a significant responsibility to undertake research” will be submitted, but “no single indicator identifies those within the scope of the exercise”.  Institutions have the option of submitting 100% of staff who meet the core eligibility requirement OR come up with a code of practice that they’ll use to decide who is eligible. Audit-able evidence will be required and Institutions can choose different options for different UoAs.

Proposed core eligibility requirements – staff must meet all of the following:

  • “have an academic employment function of ‘research only’ or ‘teaching and research’
  • are independent researchers [i.e. not research assistants unless ‘demonstrably’ independent]
  • hold minimum employment of 0.2 full time equivalent
  • have a substantive connection to the submitting institution.”

I like this as an approach – it throws the question back to universities, and leaves it up to them whether they think it’s worth the time and trouble running an exercise in one or more UoAs. And I think the proposed core requirements look sensible, and faithful to the core aim which is to maximise the number of researchers returned and prevent the hyper selectivity game being played.

(2) Transition arrangements for non-portability of publications.

HEFCE are consulting on either:

(a) “The simplified model, whereby outputs would be eligible for return by the originating institution (i.e. the institution where the research output was demonstrably generated and at which the member of staff was employed) as well as by the newly employing institution”.
or
(b) “The hybrid approach, with a deadline (to be determined), after which a limited number of outputs would transfer with staff, with eligibility otherwise linked to the originating institution. (This would mean operating two rules for portability in this exercise: the outputs of staff employed before the specified date falling under the 2014 rules of full portability; outputs from staff employed after this date would fall under the new rules.)”

I wrote a previous post on portability and non-portability when the Stern Review was first published, which I still think is broadly correct.

I wonder how simple the simplified model will be… if we end having to return n=2 publications, and choosing those publications from a list of everything published by everyone while they worked here. But it’s probably less work than having a cut off date.

More to follow….

‘Unimaginative’ research funding models and picking winners

XKCD 1827 – Survivorship Bias  (used under Creative Commons Attribution-NonCommercial 2.5 License)

Times Higher Education recently published an interesting article by Donald Braben and endorsed by 36 eminent scholars including a number of nobel laureates. They criticise “today’s academic research management” and claim that as an unforeseen consequence, “exciting, imaginative, unpredictable research without thought of practical ends is stymied”. The article fires off somewhat scattergun criticism of the usual betes noire – the inherent conservatism of peer review; the impact agenda, and lack of funding for blue skies research; and grant application success rates.

I don’t deny that there’s a lot of truth in their criticisms… I think in terms of research policy and deciding how best to use limited resources… it’s all a bit more complicated than that.

Picking Winners and Funding Outsiders

Look, I love an underdog story as much as the next person. There’s an inherent appeal in the tale of the renegade scholar, the outsider, the researcher who rejects the smug, cosy consensus (held mainly by old white guys) and whose heterodox ideas – considered heretical nonsense by the establishment – are  ultimately triumphantly vindicated. Who wouldn’t want to fund someone like that? Who wouldn’t want research funding to support the most radical, most heterodox, most risky, most amazing-if-true research? I think I previously characterised such researchers as a combination of Albert Einstein and Jimmy McNulty from ‘The Wire’, and it’s a really seductive picture. Perhaps this is part of the reason for the MMR fiasco.

The problem is that the most radical outsiders are functionally indistinguishable from cranks and charlatans. Are there many researchers with a more radical vision that the homeopathist, whose beliefs imply not only that much of modern medicine is misguided, but that so is our fundamental understanding of the physical laws of the universe? Or the anti-vaxxers? Or the holocaust deniers?

Of course, no-one is suggesting that these groups be funded, and, yes I’ll admit it’s a bit of a cheap shot aimed at a straw target. But even if we can reliably eliminate the cranks and the charlatans, we’ll still be left with a lot of fringe science. An accompanying THE article quotes Dudley Herschbach, joint winner of the 1986 Nobel Prize for Chemistry, as saying that his research was described as being at the “lunatic fringe” of chemistry. How can research funders tell the difference between lunatic ideas with promise (both interesting-if-true and interesting-even-if-not-true) and lunatic ideas that are just… lunatic. If it’s possible to pick winners, then great. But if not, it sounds a lot like buying lottery tickets and crossing your fingers. And once we’re into the business of having a greater deal of scrutiny in picking winners, we’re back into having peer review again.

One of the things that struck me about much of the history of science is that there are many stories of people who believe they are right – in spite of the scientific consensus and in spite of the state of the evidence available at the time – but who proceed anyway, heroically ignoring objections and evidence, until ultimately vindicated. We remember these people because they were ultimately proved right, or rather, their theories were ultimately proved to have more predictive power than those they replaced.

But I’ve often wondered about such people. They turned out to be right, but were they right because of some particular insight, or were they right because they were lucky in that their particular prejudice happened to line up with the actuality? Was it just that the stopped clock is right twice per day? Might their pig-headedness equally well have carried them along another (wrong) path entirely, leaving them to be forgotten as just another crank? And just because someone is right once, is there any particular reason to think that they’ll be right again? (Insert obligatory reference to Newton’s dabblings with alchemy here). Are there good reasons for thinking that the people who predicted the last economic crisis will also predict the next one?

A clear way in which luck – interestingly rebadged as ‘serendipity’ – is involved is through accidental discoveries. Researchers are looking at X when… oh look at Y, I wonder if Z… and before you know it, you have a great discovery which isn’t what you were after at all. Free packets of post-it notes all round. Or when ‘blue skies’ research which had no obvious practical application at the time becomes a key enabling technology or insight later on.

The problem is that all these stories of serendipity and of surprise impact and of radical outsider researchers are all examples of lotteries in which history only remembers the winning tickets. Through an act of serendipity, the XKCD published a cartoon illustrating this point nicely (see above) just as I was thinking about these issues.

But what history doesn’t tell us is how many lottery tickets research funding agencies have to buy in order to have those spectacular successes. And just as importantly, whether or not a ‘lottery ticket’ approach to research funding will ultimately yield a greater return on investment than a more ‘unimaginative’ approach to funding using the tired old processes of peer review undertaken by experts in the relevant field followed by prioritisation decisions taken by a panel of eminent scientists drawn from across the funder’s remit. And of course, great successes achieved through this method of having a great idea, having the greatness of the idea acknowledged by experts, and then carrying out the research is a much less compelling narrative or origin story, probably to the point of invisibility.

A mixed ecosystem of conventional and high risk-high reward funding streams

I think there would be broad agreement that the research funding landscape needs a mixture of funding methods and approaches. I don’t take Braben and his co-signatories to be calling for wholesale abandonment of peer review, of themed calls around particular issues, or even of the impact agenda. And while I’d defend all those things, I similarly recognise merit in high risk-high reward research funding, and in attempts by major funders to try to address the problem of peer review conservatism. But how do we achieve the right balance?

Braben acknowledges that “some agencies have created schemes to search for potentially seminal ideas that might break away from a rigorously imposed predictability” and we might include the European Research Council and the UK Economic and Social Research Council as examples of funders who’ve tried to do this, at least in some of their schemes. The ESRC in particular on one scheme abandoned traditional peer review for a Dragon’s Den style pitch-to-peers format, and the EPSRC is making increasing use of sandpits.

It’s interesting that Braben mentions British Petroleum’s Venture Research Initiative as a model for a UCL pilot aimed at supporting transformative discoveries. I’ll return to that pilot later, but he also mentions that the one project that scheme funded was later funded by an unnamed “international benefactor”, which I take to be a charity or private foundation or other philanthropic endeavor rather than a publically-funded research council or comparable organisation. I don’t think this is accidental – private companies have much more freedom to create blue skies research and innovation funding as long as the rest of the operation generates enough funding to pay the bills and enough of their lottery tickets end up winning to keep management happy. Similarly with private foundations with near total freedom to operate apart perhaps from charity rules.

But I would imagine that it’s much harder for publically-funded research councils to take these kinds of risks, especially during austerity.  (“Sorry Minister, none of our numbers came up this year, but I’m sure we’ll do better next time.”) In a UK context, the Leverhulme Trust – a happy historical accident funded largely through dividend payments from its bequeathed shareholding in Unilever – seeks to differentiate itself from the research councils by styling itself as more open to risky and/or interdisciplinary research, and could perhaps develop further in this direction.

The scheme that Braben outlines is genuinely interesting. Internal only within UCL, very light touch application process mainly involving interviews/discussion, decisions taken by “one or two senior scientists appointed by the university” – not subject experts, I infer, as they’re the same people for each application. Over 50 applications since 2008 have so far led to one success. There’s no obligation to make an award to anyone, and they can fund more than one. It’s not entirely clear from this article where the applicant was – as Braben proposes for the kinds of schemes he calls for – “exempt from normal review procedures for at least 10 years. They should not be set targets either, and should be free to tackle any problem for as long as it takes”.

From the article I would infer that his project received external funding after 3 years, but I don’t want to pick holes in a scheme which is only partially outlined and which I don’t know any more about, so instead I’ll talk about Braben’s more general proposal, not the UCL scheme in particular.

It’s a lot of power in a very few hands to give out these awards, and represents a very large and very blank cheque. While the use of interviews and discussion cuts down on grant writing time, my worry is that a small panel and interview based decision making may open the door to unconscious bias, and greater successes for more accomplished social operators. Anyone who’s been on many interview panels will probably have experienced fellow panel members making heroic leaps of inference about candidates based on some deep intuition, and in the tendency of some people to want to appoint the more confident and self-assured interviewee ahead of a visibly more nervous but far better qualified and more experienced rival. I have similar worries about “sand pits” as a way of distributing research funding – do better social operators win out?

The proposal is for no normal review procedures, and for ten years in which to work, possibly longer. At Nottingham – as I’m sure at many other places – our nearest equivalent scheme is something like a strategic investment fund which can cover research as well as teaching and other innovations. (Here we stray into things I’m probably not supposed to talk about, so I’ll stop). But these are major investments, and there’s surely got to be some kind of accountability during decision-making processes and some sort of stop-go criteria or review mechanism during the project’s life cycle. I’d say that courage to start up some high risk, high reward research project has to be accompanied by the courage to shut it down too. And that’s hard, especially if livelihoods and professional reputations depend upon it – it’s a tough decision for those leading the work and for the funder too. But being open to the possibility of shutting down work implies a review process of some kind.

To be clear, I’m not saying let’s not have more high-risk high-reward curiosity driven research. By all means let’s consider alternative approaches to peer review and to decision making and to project reporting. But I think high risk/high reward schemes raise a lot of difficult questions, not least what the balance should be between lottery ticket projects and ‘building society savings account’ projects. We need to be aware of the ‘survivor bias’ illustrated by the XKCD cartoon above and be aware that serendipity and vindicated radical researchers are both lotteries in which we only see the winning tickets. We also need to think very carefully about fair selection and decision making processes, and the danger of too much power and too little accountability in too few hands.

It’s all about the money, money, money…

But ultimately the problem is that there are a lot more researchers and academics than there used to be, and their numbers – in many disciplines – is determined not by the amount of research funding available nor the size of the research challenges, but by the demand for their discipline from taught-course students. And as higher education has expanded hugely since the days in which most of Braben’s “500 major discoveries” there are just far more academics and researchers than there is funding to go around. And that’s especially true given recent “flat cash” settlements. I also suspect that the costs of research are now much higher than they used to be, given both the technology available and the technology required to push further at the boundaries of human understanding.

I think what’s probably needed is a mixed ecology of research funders and schemes. Probably publically funded research bodies are not best placed to fund risky research because of accountability issues, and perhaps this is a space in which private foundations, research funding charities, and universities themselves are better able to operate.

The rise of the machines – automation and the future of research development

"I've seen research ideas you people wouldn't believe. Impact plans on fire off the shoulder of Orion. I watched JeS-beams glitter in the dark near the Tannhäuser ResearchGate. All those proposals will be lost in time, like tears...in...rain. Time to revise and resubmit."
“I’ve seen first drafts you people wouldn’t believe. Impact plans on fire off the shoulder of Orion. I watched JeS beams glitter in the dark near the Tannhäuser ResearchGate. All those research proposals will be lost in time, like tears…in…rain. Time to resubmit.”

In the wake of this week’s Association of Research Managers and Administrator‘s conference in Birmingham, Research Professional has published an interesting article by Richard Bond, head of research administration at the University of the West of England. The article – From ARMA to avatars: expansion today, automation tomorrow? – speculates about the future of the research management/development profession given the likely advances of automation and artificial intelligence. Each successive ARMA conference is hailed as the largest ever, and ARMA’s membership has grown rapidly over recent years, probably reflecting increasing numbers of research support roles, increased professionalism, an increased awareness of ARMA and the attractiveness of what it offers in terms of professional development. But might better, smarter computer systems reduce, and perhaps even eliminate the need for some research development roles?

In many ways, the future is already here. In my darker moments I’ve wondered whether some colleagues might be replicants or cylons. But many universities already have (or are in the progress of getting) some form of cradle-to-grave research management information system which has the potential to automate many research support tasks, both pre and post award. Although I wasn’t in the session where the future of JeS, the online submission grant system used by RCUK UKRI, tweets from the session indicate that JeS 2.0 is being seen as a “grant getting service” and a platform to do more than just process applications, which could well include distribution of funding opportunities. Who knows what else it might be able to do? Presumably it can link much better to costing tools and systems, allowing direct transfer of costing and other informations to and from university systems.

A really good costing tool might be able to do a lot of things automatically. Staff costs are already relatively straightforward to calculate with the right tools  – the complication largely comes from whether funders expect figures to include inflation and cost of living/salary increment pay rises to be included or not. But greater uniformity across funders could help, and setting up templates for individual funders could be done, and in many places is already done. Non-pay costs are harder, but one could imagine a system that linked to travel and bookings websites and calculated the average cost of travel from A to B. Standard costs could be available for computers and for consumables, again, linking to suppliers’ catalogues. This could in principle allow the applicant (rather than a research administrator) to do the budget for the grant application, but I wonder if there’s much appetite for doing that from applicants who don’t do this. I also think there’s a role for the research costing administrator in terms of helping applicants flush out all of the likely costs – not all of which will occur to the PI – as well as dealing with the exceptions that the system doesn’t cover. But even if specialist human involvement is still required, giving people better tools to work smarter and more efficiently – especially if the system is able to populate the costings section application form directly without duplication – would reduce the amount of humans required.

While I don’t think we’re there yet, it’s not hard to imagine systems which could put the right funding opportunities in front of the right academics at the right time and in the right format. Research Professional has offered a customisable research funding alerts service for many years now, and there’s potential for research management systems to integrate this data, combine it with what’s known about individual researchers and research team’s interests, and put that information in front of them automatically.

I say we’re not there yet, because I don’t think the information is arriving in the right format – in a quick and simple summary that allows researchers to make very quick decisions about whether to read on, or move on to the next of the twelvety-hundred-and-six unread emails. I also wonder whether the means of targeting the right academics are sufficiently nuanced. A ‘keywords’ approach might help if we could combine research interest keyword sets used by funders, research intelligence systems, and academics. But we’d need a really sophisticated set of keywords, coving not just discipline and sub-discipline, but career stage, countries of interest, interdisciplinary grand challenges and problems etc. Another problem is that I don’t think call summaries are – in general – particularly well-written (though they are getting better) by funders, though we could perhaps imagine them being tailored for use in these kinds of systems in the future. A really good research intelligence system could also draw in data about previous bids to the scheme from the institution, data about success rates for previous calls, access to previously successful applications (though their use is not without its drawbacks).

But even with all this in place, I still think there’s a role for human research development staff in getting opportunities out there. If all we’re doing is forwarding Research Professional emails, then we could and should be replaced. But if we’re adding value through our own analysis of the opportunity, and customising the email for the intended audience, we might be allowed to live. A research intelligence system inevitably just churns out emails that might be well targeted or poorly targeted. A human with detailed knowledge of the research interests, plans, and ambitions of individual researchers or groups can not only target much better, but can make a much more detailed, personalised, and context sensitive analysis of the advantages and disadvantages of a possible application. I can get excited about a call and tell someone it’s ideal for them, and because of my existing relationship with them, that’ll carry weight … a computer can tell them that it’s got a 94.8% match.

It’s rather harder to see automation replacing training researchers in grant writing skills or undertaking lay review of draft grant applications, not least because often the trick with lay review is spotting what’s not there rather than what is. But I’d be intrigued to learn what linguistic analysis tools might be able to do in terms of assessing the required reading level, perhaps making stylistic observations or recommendations, and perhaps flagging up things like the regularity with which certain terms appear in the application relative to the call etc. All this would need interpreting, of course, and even then may not be any use. But it would be interesting to see how things develop.

Impact is perhaps another area where it’s hard to see humans being replaced. Probably sophisticated models of impact development could and should be turned in tools to help academics identify the key stakeholders, come up with appropriate strategies, and identify potential intermediaries with their own institution. But I think human insight and creativity could still add substantial value here.

Post-award isn’t really my area these days, but I’d imagine that project setup could become much easier and involve fewer pieces of paper and documents flying around. Even better and more intuitive financial tools would help PIs manage their project, but there are still accounting rules and procedures to be interpreted, and again, I think many PIs would prefer someone else to deal with the details.

Overall it’s hard to disagree with Bond’s view that a reduction in overall headcount across research administration and management (along with many other areas of work) is likely, and it’s not hard to imagine that some less research intensive institutions might be happy that the service that automated systems could deliver is good enough for them. At more research intensive institutions, better tools and systems will increase efficiency and will enable human staff to work more effectively. I’d imagine that some of this extra capacity will be filled by people doing more, and some of it may lead to a reduction in headcount.

But overall, I’d say – and you can remind me of this when I’m out of a job and emailing you all begging for scraps of consultancy work, or mindlessly entering call details into a database – that I’m probably excited by the possibilities of automation and better and more powerful tools than I am worried about being replaced by them.

I for one welcome our new research development AI overlords.

Getting research funding: the significance of significance

"So tell me, Highlander, what is peer review?"
“I’m Professor Connor Macleod of the Clan Macleod, and this is my research proposal!”

In a excellent recent blog post, Lachlan Smith wrote about the “who cares?” question that potential grant applicants ought to consider, and that research development staff ought to pose to applicants on a regular basis.

Why is this research important, and why should it be funded? And crucially, why should we fund this, rather than that? In a comment on a previous post on this blog Jo VanEvery quoted some wise words from a Canadian research funding panel member: “it’s not a test, it’s a contest”. In other words, research funding is not an unlimited good like a driving test or a PhD viva where there’s no limit to how many people can (in principle) succeed. Rather, it’s more like a job interview, qualification for the Olympic Games, or the film Highlander – not everyone can succeed. And sometimes, there can be only one.

I’ve recently been fortunate enough to serve on a funding panel myself, as a patient/public involvement representative for a health services research scheme. Assessing significance in the form of potential benefit for patients and carers is a vitally important part of the scheme, and while I’m limited in what I’m allowed to say about my experience, I don’t think I’m speaking out of turn when I say that significance – and demonstrating that significance – is key.

I think there’s a real danger when writing – and indeed supporting the writing – of research grant applications that the focus gets very narrow, and the process becomes almost inward looking. It becomes about improving it internally, writing deeply for subject experts, rather than writing broadly for a panel of people with a range of expertise and experiences. It almost goes without saying that the proposed project must convince the kinds of subject expert who will typically be asked to review a project, but even then there’s no guarantee that reviewers will know as much as the applicant. In fact, it would be odd indeed if there were to be an application where the reviewers and panel members knew more about the topic than the applicant. I’d probably go as far as to say that if you think the referees and the reviewers know more than you, you probably shouldn’t be applying – though I’m open to persuasion about some early career schemes and some very specific calls on very narrow topics.

So I think it’s important to write broadly, to give background and context, to seek to convince others of the importance and significance of the research question. To educate and inform and persuade – almost like a briefing. I’m always badgering colleagues for what I call “killer stats” – how big is the problem, how many people does it affect, by how much is it getting worse, how much is it costing the economy, how much is it costing individuals, what difference might a solution to this problem make? If there’s a gap in the literature or in human knowledge, make a case for the importance or potential importance in filling that gap.

For blue skies research it’s obviously harder, but even here there is scope for discussing the potential academic significance of the possible findings – academic impact – and what new avenues of research may be opened out, or closed off by a decisive negative finding which would allow effort to be refocused elsewhere. If all research is standing on the shoulders of giants, what could be seen by future researchers standing on the shoulders of your research?

It’s hugely frustrating for reviewers when applicants don’t do this – when they don’t give decision makers the background and information they need to be able to draw informed conclusions about the proposed project. Maybe a motivated reviewer with a lighter workload and a role in introducing your proposal may have time to do her own research, but you shouldn’t expect this, and she shouldn’t have to. That’s your job.

It’s worth noting, by the way, that the existence of a gap in the literature is not itself an argument for it being filled, or at least not through large amounts of scarce research funding. There must be a near infinite number of gaps, such as the one that used to exist about the effect of peanut butter on the rotation of the earth – but we need more than the bare fact of the existence of a gap – or the fact that other researchers can be quoted as saying there’s a gap – to persuade.

Oh, and if you do want to claim there’s a gap, please check google scholar or similar first – reviewers, panel members (especially introducers) may very well do that. And from my limited experience of sitting on a funding panel, there’s nothing like one introducer or panel member reeling of a list of studies on a topic where there’s supposedly a gap (and which aren’t referenced in the proposal) to finish off the chance of an application. I’ve not seen enthusiasm or support for a project sucked out of the room so completely and so quickly by any other means.

And sometimes, if there aren’t killer stats or facts and figures, or if a case for significance can’t be made, it may be best to either move on to another idea, or a different and cheaper way of addressing the challenge. While it may be a good research idea, a key question before deciding to apply is whether or not the application is competitive for significance given the likely competition, the scale of the award, the ambition sought by the funder, and the number of successful projects to be awarded. Given the limits to research funding available, and their increasing concentration into larger grants, there really isn’t much funding for dull-but-worthy work which taken together leads to the aggregation of marginal gains to the sum of human knowledge.I think this is a real problem for research, but we are where we are.

Significance may well be the final decider in research funding schemes that are open to a range of research questions. There are many hurdles which must be cleared before this final decider, and while they’re not insignificant, they mainly come down to technical competence and feasibility. Is the methodology not only appropriate, but clearly explained and robustly justified? Does the team have the right mix of expertise? Is the project timescale and deliverables realistic? Are the research questions clearly outlined and consistent throughout? All of these things – and more – are important, but what they do is get you safely though into the final reckoning for funding.

Once all of the flawed or technically unfeasible or muddled or unpersuasive or unclear or non-novel proposals have been knocked out, perhaps at earlier stages, perhaps at the final funding panel stage, what’s left is a battle of significance. To stand the best chance of success, your application needs to convince and even inspire non-expert reviewers to support your project ahead of the competition.

But while this may be the last question, or the final decider between quality projects, it’s one that I’d argue potential grant applicants should consider first of all.

The significance of significance is that if you can’t persuasively demonstrate the significance of your proposed project, your grant application may turn out to be a significant waste of your time.

ESRC success rates 2014/2015 – a quick and dirty commentary

"meep meep"
Success rates. Again.

The ESRC has issued its annual report and accounts for the financial year 2014/15, and they don’t make good reading. As predicted by Brian Lingley and Phil Ward back in January on the basis of the figures from the July open call, the success rate is well down – to 13% –  from the 25% I commented on last year , 27% on 2012-13 and 14% of 2011-2012.

Believe it or not there is a staw-grasping positive way of looking at these figures… of which more later.

This research professional article has a nice overview which I can’t add much to, so read it first. Three caveats about these figures, though…

  • They’re for the standard open call research grant scheme, not for all calls/schemes
  • They relate to the financial year, not the academic year
  • It’s very difficult to compare year-on-year due to changes to the scheme rules, including minimum and maximum thresholds which have changed substantially.

In previous years I’ve focused on how different academic disciplines have got on, but there’s probably very little to add. You can read them for yourself (p. 38), but the report only bothers to calculate success rates for the disciplines with the highest numbers of applications – presumably beyond that there’s little statistical significance. I could be claiming that it’s been a bumper year for Education research, which for years bumped along at the bottom of the league table with Business and Management Studies in terms of success rates, but which this year received 3 awards from 22 applications, tracking the average success rate. Political Science and Socio-Legal Studies did well, as they always tend to do. But it’s generalising from small numbers.

As last year, there is also a table of success rates by institution. In an earlier section on demand management, the report states that the ESRC “are discussing ways of enhancing performance with those HEIs where application volume is high and quality is relatively weak”. But as with last year, it’s hard to see from the raw success rate figures which these institutions might be – though of course detailed institutional profiles showing the final scores for applications might tell a very different story. Last year I picked out Leeds (10/0), Edinburgh (8/1), and Southampton (14/2) as doing poorly, and Kings College (7/3), King Leicester III (9/4), Oxford (14/6) as doing well – though again, one more or less success changes the picture.

This year, Leeds (8/1) and Edinburgh (6/1) have stats that look much better. Southampton doesn’t look to have improved (12/0) at all, and is one of the worst performers. Of those who did well last year, none did so well this year – Kings were down to 11/1, Leicester 2/0, and Oxford 11/2. Along with Southampton, this year’s poor performers were Durham (10/0), UCL (15/1)  and Sheffield (11/0) – though all three had respectable enough scores last time. This year’s standouts were Cambridge at 10/4. Perhaps someone with more time than me can combine success rates from the last two years, and I’m sure someone at the ESRC already has….

So… on the basis of success rates alone, probably only Southampton jumps out as doing consistently poorly. But again, much depends on the quality profile of the applications being submitted – it’s entirely possible that they were very unlucky, and that small numbers mask much more slapdash grant submission behaviour from other institutions. And of course, these figures only relate to the lead institution as far as I know.

It’s worth noting that demand management has worked… after a fashion.

We remain committed to managing application volume, with
the aim of focusing sector-wide efforts on the submission
of a fewer number of higher quality proposals with a
genuine chance of funding. General progress is positive.
Application volume is down by 48 per cent on pre-demand
management levels – close to our target of 50 per cent.
Quality is improving with the proportion of applications now
in the ‘fundable range’ up by 13 per cent on pre-demand
management levels, to 42 per cent. (p. 21).

I remember the target of reducing the numbers of applications received by 50% as being regarded as very ambitious at the time, and even if some of it was achieved by changing scheme rules to increase the minimum value of a grant application and banning resubmissions, it’s still some achievement. Back in October 2011 I argued that the ESRC had started to talk optimistically about meeting that target after researcher sanctions (in some form) had started to look inevitable. And in November 2012 things looked nicely on track.

But reducing brute numbers of applications is all very well. But if only 42% of applications are within the “fundable range”, then that’s a problem because it means that a lot of applications being submitted still aren’t good enough.This is where there’s cause for optimism – if less than half of the applications are fundable, your own chances should be more than double the average success rate – assuming that your application is of “fundable” quality. So there’s your good news. Problem is, no-one applies who doesn’t think their application is fundable.

Internal peer review/demand management processes are often framed in terms of improving the quality of what gets submitted, but perhaps not enough of a filtering process. So we refine and we polish and we make 101 incremental improvements… but ultimately you can’t polish a sow’s ear. Or something.

Proper internal filtering is really, really hard to do – sometimes it’s just easier to let stuff from people who won’t be told through and see if what happens is exactly what you think will happen, which it always is. There’s also a fine line (though one I think that can be held and defended) between preventing perceived uncompetitive applications from doing so and impinging on academic freedom. I don’t think telling someone they can’t submit a crap application is infringing their academic freedom, but any such decisions need to be taken with a great deal of care. There’s always the possibility of suspicion of ulterior motives – be it personal, be it subject or methods-based prejudice, or senior people just overstepping the mark and inappropriately imposing their convictions (ideological, methodological etc) on others. Like the external examiner who insists on “more of me” on the reading list….

The elephant in the room, of course, is the flat cash settlement and the fact that that’s now really biting, and that there’s nowhere near enough funding to go around for all of the quality social science research that’s badly needed. But we can’t do much about that – and we can do something about the quality of the applications we’re submitting and allowing to be submitted.

I wrote something for research professional a few years back on how not to do demand management/filtering processes, and I think it still stands up reasonably well and is even quite funny in places (though I say so myself). So I’m going to link to it, as I seem to be linking to a disproportionate amount of my back catalogue in this post.

A combination of a new minimum of £350k for the ESRC standard research grants scheme and the latest drop in success rates makes me think it’s worth writing a companion piece to this blog post about potential ESRC applicants need to consider before applying, and what I think is expected of a “fundable” application.

Hopefully something for the autumn…. a few other things to write about first.

ESRC – sweeping changes to the standard grants scheme

The ESRC have just announced a huge change to their standard grants scheme, and I think it’s fair to say that it’s going to prove somewhat controversial.

At the moment, it’s possible to apply to the ESRC Standard Grant Scheme at any time for grants of between £200k and £2million. From the end of June this year, the minimum threshold will raise from £200k to £350k, and the maximum threshold will drop from £2m to £1m.

Probably those numbers don’t mean very much to you if you’re not familiar with research grant costing, but as a rough rule of thumb, a full time researcher for a year (including employment costs and overheads) comes to somewhere around £70k-80k. So a rough rule of thumb I used to use was that if your project needed two years of researcher time, it was big enough. So… for £350k you’d probably need three researcher years, a decent amount of PI and Co-I time, and a fair chunk of non-pay costs. That’s a big project. I don’t have my filed in front of me as I’m writing this, so maybe I’ll add a better illustration later on.

This isn’t the first time the lower limit has been raised. Up until February 2011, there used to be a “Small Grants Scheme” for projects up to £200k before that was shut, with £200k becoming the new minimum. The argument at the time was that larger grants delivered more, and had fewer overheads in terms of the costs of reviewing, processing and administering. And although the idea was that they’d help early career researchers, the figures didn’t really show that.

The reasons given for this change are a little disingenuous puzzling. Firstly, this:

The changes are a response to the pattern of demand that is being placed on the standard grants scheme by the social science community. The average value of a standard grant application has steadily increased and is now close to £500,000, so we have adjusted the centre of gravity of the scheme to reflect applicant behaviour.

Now that’s an interesting tidbit of information – I wouldn’t have guessed that the “average value” would be that high, but you don’t have to be an expert in statistics (and believe me, in spite of giving 110% in maths class at school I’m not one) to wonder what “average” means, and further, why it even matters. This might be an attempt at justification, but I don’t see why this provides a rationale for change.

Then we have this….

The changes are also a response to feedback from our Grant Assessment Panels who have found it increasingly difficult to assess and compare the value of applications ranging from £200,000 to £2 million, where there is variable level of detail on project design, costs and deliverables. This issue has become more acute as the number of grant applications over £1 million has steadily increased over the last two years. Narrowing the funding range of the scheme will help to maintain the robustness of the assessment process, ensuring all applications get a fair hearing.

I have every sympathy for the Grant Assessment Panel members here – how do you choose between funding one £2m project and funding 10 x £200k projects, or any combination you can think of? It’s not so much comparing apples to oranges as comparing grapes to water melons. And they’re right to point out the “variable” level of detail provided – but that’s only because their own rules give a maximum of 6 A4 page for the Case for Support for projects under £1m and 12 for those over. If you think that sounds superficially reasonable, then notice that it’s potentially double the space to argue for ten times the money. I’ve supported applications of £1m+ and 12 sides of A4 is nowhere near enough, compared to the relative luxury of 6 sides for £200k. This is a problem.

In my view it makes sense to “introduce an annual open competition for grants between £1 million and £2.5 million”, which is what the ESRC propose to do. So I think there’s a good argument for lowering the upper threshold from £2m to £1m and setting it up as a separate competition. I know the ESRC want to reduce the number of calls/schemes, but this makes sense. As things stand I’ve regularly steered people away from the Centres/Large Grants competition towards Standard Grants instead, where I think success rates will be higher and they’ll get a fairer hearing. So I’d be all in favour of having some kind of single Centres/Large/Huge/Grants of Unusual Size competition.

But nothing here seems to me to be an argument for raising the lower limit.

But finally, I think we come to what I suspect is the real reason, and judging by Twitter comments so far, I’m not alone in thinking this.

We anticipate that these changes will reduce the volume of applications we receive through the Standard Grants scheme. That will increase overall success rates for those who do apply as well as reducing the peer review requirements we need to place on the social science community.

There’s a real problem with ESRC success rates, which dropped to 10% in the July open call, with over half the “excellent” proposals unfunded. This is down from around 25% success rates, much improved in the last few years. I don’t know whether this is a blip – perhaps a few very expensive projects were funded and a lot of cheaper ones missed out – but it’s not good news. So it’s hard not to see this change as driven entirely by a desire to get success rates up, and perhaps an indication that this wasn’t a blip.

In a recent interview with Adam Smith of Research Professional, Chief Exec Jane Eliot recently appeared to rule out the option of individual sanctions which had been threatened if institutional restraint failed to bring down the number of poor quality applications and it appears that the problem is not so much poor quality applications as lots of high quality applications, not enough money, plummeting success rates, and something needing to be done.

All this raises some difficult questions.

  • Where are social science researchers now supposed to go for funding for projects whose “natural size” is between £10k (British Academy Small Grants) and £350k, the proposed new minimum threshold? There’s only really the Leverhulme Trust, whose schemes will suit some project types and but not others, and they’re not exclusively a social science funder.
  • Where will the next generation of PIs to be entrusted with £350k of taxpayer’s money have an opportunity to cut their teeth, both in terms of proving themselves academically and managerially?
  • What about career young researchers? At least here we can expect a further announcement – there has been talk of merging the ‘future leaders scheme’ into Standard Grants, so perhaps there will be a lower minimum for them. But we’ll see.
  • Given that the minimum threshold has been almost doubled, what consultation has been carried out? I’m just a humble Business School Research Manager (I mean I’m humble, my Business School is outstanding, obviously) so perhaps it’s not surprising that this the first I’ve heard. But was there any meaningful consultation over this? Is there any evidence underpinning claims for the efficiency of fewer, longer and larger grants?
  • How do institutions respond? I guess one way will be to work harder to create bigger gestalt projects with multiple themes and streams and work packages. But surely expectations of grant getting for promotion and other purposes need to be dialled right back, if they haven’t been already. Do we encourage or resist a rush to get applications in before the change, at a time when success rates will inevitably be dire?

Of course, the underlying problem is that there’s not enough money in the ESRC’s budget to support excellent social science after years and years of “flat cash” settlements. And it’s hard to see what can be done about that in the current political climate.

ESRC success rates 2013/2014

The ESRC Annual Report for 2013-14 has been out for quite a while now, and a quick summary and analysis from me is long overdue.

Although I was tempted to skip straight through all of the good news stories about ESRC successes and investments and dive straight in looking for success rates, I’m glad I took the time to at least skim read some of the earlier stuff.  When you’re involved in the minutiae of supporting research, it’s sometimes easy to miss the big picture of all the great stuff that’s being produced by social science researchers and supported by the ESRC.  Chapeau, everyone.

In terms of interesting policy stuff, it’s great to read that the “Urgency Grants” mechanism for rapid responses to “rare or unforeseen events” which I’ve blogged about before is being used, and has funded work “on the Philippines typhoon, UK floods, and the Syrian crisis”.  While I’ve not been involved in supporting an Urgency Grant application, it’s great to know that the mechanism is there, that it works, and that at least some projects have been funded.

The “demand management” agenda

This is what the report has to say on “demand management” – the concerted effort to reduce the number of applications submitted, so as to increase the success rates and (more importantly) reduce the wasted effort of writing and reviewing applications with little realistic chance of success.

Progress remains positive with an overall reduction in application numbers of 41 per cent, close to our target of 50 per cent. Success rates have also increased to 31 per cent, comparable with our RCUK partners. The overall quality of applications is up, whilst peer review requirements are down.

There are, however, signs that this positive momentum may
be under threat as in certain schemes application volume is
beginning to rise once again. For example, in the Research
Grants scheme the proposal count has recently exceeded
pre-demand management levels. It is critical that all HEIs
continue to build upon early successes, maintaining the
downward pressure on the submission of applications across
all schemes.

It was always likely that “demand management” might be the victim of its own success – as success rates creep up again, getting a grant appears more likely and so researchers and research managers encourage and submit more applications.  Other factors might also be involved – the stage of the REF cycle, for example.  Or perhaps now talk of researcher or institutional sanctions has faded away, there’s less incentive for restraint.

Another possibility is that some universities haven’t yet got the message or don’t think it applies to them.  It’s also not hard to imagine that the kinds of internal review mechanisms that some of us have had for years and that we’re all now supposed to have are focusing on improving the quality of applications, rather than filtering out uncompetitive ideas.  But is anyone disgracing themselves?

Looking down the list of successes by institution (p. 41) it’s hard to pick out any obvious bad behaviour.  Most of those who’ve submitted more than 10 applications have an above-average success rate.  You’d only really pick out Leeds (10 applications, none funded), Edinburgh (8/1) and Southampton (14/2), and a clutch of institutions on 5/0, (including top-funded Essex, surprisingly) but in all those cases one or two more successes would change the picture.  Similarly for the top performers – Kings College (7/3), King Leicester III (9/4), Oxford (14/6) – hard to make much of a case for the excellence or inadequacy of internal peer review systems from these figures alone.  What might be more interesting is a list of applications by institution which failed to reach the required minimum standard, but that’s not been made public to the best of my knowledge.  And of course, all these figures only refer to the response mode Standard Grant applications in the financial year (not academic year) 2013-14.

Concentration of Funding

Another interesting stat (well, true for some values of “interesting”) concerns the level of concentration of funding.  The report records the expenditure levels for the top eleven (why 11, no idea…) institutions by research expenditure and by training expenditure.  Interesting question for you… what percentage of the total expenditure do the top 11 institutions get?  I could tell you, but if I tell you without making you guess first, it’ll just confirm what you already think about concentration of funding.  So I’m only going to tell you that (unsurprisingly) training expenditure is more concentrated than research funding.  The figures you can look up for yourself.  Go on, have a guess, go and check (p. 44) and see how close you are.

Research Funding by Discipline

On page 40, and usually the most interesting/contentious.  Overall success rate was 25% – a little down from last year, but a huge improvement on 14% two years ago.

Big winners?  History (4 from 6); Linguistics (5 from 9), social anthropology (4 from 9), Political and International Studies (9 from 22), and Psychology (26 from 88, – just under 30% of all grants funded were in psychology).  Big losers?  Education (1 from 27), Human Geography (1 from 19), Management and Business Studies (2 from 22).

Has this changed much from previous years?  Well, you can read what I said last year and the year before on this, but overall it’s hard to say because we’re talking about relatively small numbers for most subjects, and because some discipline classifications have changed over the last few years.  But, once again, for the third year in a row, Business and Management and Education do very, very poorly.

Human Geography has also had a below average success rate for the last few years, but going from 1 in 19 from 3 from 14 probably isn’t that dramatic a collapse – though it’s certainly a bad year.  I always make a point of trying to be nice about Human Geography, because I suspect they know where I live.  Where all of us live.  Oh, and Psychology gets a huge slice of the overall funding, albeit not a disproportionate one given the number of applications.

Which kinds of brings us back to the same questions I asked in my most-read-ever piece – what on earth is going on with Education and Business and management research, and why do they do so badly with the ESRC?  I still don’t have an entirely satisfactory answer.

I’ve put together a table showing changes to disciplinary success rates over the last few years which I’m happy to share, but you’ll have to email me for a copy.  I’ve not uploaded it here because I need to check it again with fresh eyes before it’s used – fiddly, all those tables and numbers.

Pre-mortems: Tell me why your current grant application or research project will fail

I came across a really interesting idea the other day week via the Freakonomics podcast – the idea of a project “pre-mortem” or “prospective hindsight”  They interviewed Gary Klein who described it as follows:

KLEIN:  I need you to be in a relaxed state of mind.  So lean back in your chair. Get yourself calm and just a little bit dreamy. I don’t want any daydreaming but I just want you to be ready to be thinking about things. And I’m looking in a crystal ball. And uh, oh, gosh…the image in the crystal ball is a really ugly image. And this is a six-month effort. We are now three months into the effort and it’s clear that this project has failed. There’s no doubt about it. There’s no way that it’s going to succeed. Oh, and I’m looking at another scene a few months later, the project is over and we don’t even want to talk about it. And when we pass each other in the hall, we don’t even make eye contact. It’s that painful. OK. So this project has failed, no doubt about it [….] I want each of you to write down all the reasons why this project has failed. We know it failed. No doubts. Write down why it failed.

The thinking here is that such an approach to projects reduces overconfidence, and elsewhere the podcast discusses the problems of overconfidence, “go fever”, the Challenger shuttle disaster, and how cultural/organisational issues can make it difficult to bring up potential problems and obstacles.  The pre-mortem exercise might free people from that, and encourages people (as a team) to find reasons for failure and then respond to them.  I don’t do full justice to the arguments here, but you can listen to it for yourself (or read the transcript) at the link above.  It reminds me of some of the material covered in a MOOC I took which showed how very small changes in the way that questions are posed and framed can make surprisingly large differences to the decisions that people make, so perhaps this very subtle shift in mindset might be useful.

How might we use the idea of a pre-mortem in research development?  My first thought was about grant applications.  Would it help to get the applicants to undertake the pre-mortem exercise?  I’m not sure that overconfidence is often a huge problem among research teams (a kind of grumpy, passive-aggressive form of entitled pessimism is probably more common), so perhaps the kind of groupthink overconfidence/excessive positivity is less of an issue than in larger project teams where nobody wants to be the one to be negative.  But perhaps there’s value in asking the question anyway, and re-focusing applicants on the fact that they’re writing an application for reviewers and for a funding body, not for themselves.  A reminder that the views, priorities, and (mis)interpretations of others are crucial to their chances of success or failure.

Would it help to say to internal reviewers “assume this project wasn’t funded – tell me why”?  Possibly.  It might flush out issues that reviewers may be too polite or insufficiently assertive to raise otherwise, and again, focuses minds on the nature of the process as a competition.  It could also help reviewers identify where the biggest danger for the application lies.

Another way it could usefully be used is in helping applicants risk assess their own project.  Saying to them “you got funded, but didn’t achieve the objectives you set for yourself.  Why not?” might be a good way of identifying project risks to minimise in the management plan, or risks to alleviate through better advanced planning.  It might prompt researchers to think more cautiously about the project timescale, especially around issues that are largely out of their control.

So… has anyone used anything like this before in research development?  Might it be a useful way of thinking?  Why will your current application fail?

Adam Golberg announces new post about Ministers inserting themselves into research grant announcements

“You might very well think that as your hypothesis, but I couldn’t possibly comment”

Here’s something I’ve been wondering recently.  Is it just me, or have major research council funding announcements started to be made by government ministers, rather than by the, er, research councils?

Here’s a couple of examples that caught my eye from the last week or so. First, David Willetts MP “announces £29 million of funding for ESRC Centres and Large Grants“.  Thanks Dave!  To be fair, he is Minster of State for Universities and Science.  Rather more puzzling is George Osborne announcing “22 new Centres for Doctoral Training“, though apparently he found the money as Chancellor of the Exchequer.  Seems a bit tenuous to me.

So I had a quick look back through the ESRC and EPSRC press release archives to see if the prominence of government ministers in research council funding announcements was a new thing or not.  Because I hadn’t noticed it before.  With the ESRC, it is new.  Here’s the equivalent announcement from last year in which no government minister is mentioned.  With the EPSRC, it’s being going on for longer.  This year’s archive and the 2013 archive show government ministers (mainly Willetts, sometimes Cable or Osborne) front and centre in major announcements.  In 2012 they get a name check, but normally in the second or third paragraph, not in the headline, and don’t get a picture of themselves attached to the story.

Does any of this matter? Perhaps not, but here’s why I think it’s worth mentioning.  The Haldane Principle is generally defined as “decisions about what to spend research funds on should be made by researchers rather than politicians”.  And one of my worries is that in closely associating political figures with funding decisions, the wrong impression is given.  Read the recent ESRC announcement again, and it’s only when you get down to the ‘Notes for Editors’ section that there’s any indication that there was a competition, and you have to infer quite heavily from those notes that decisions were taken independently of government.

Why is this happening? It might be for quite benign reasons – perhaps research council PR people think (probably not unreasonably) that name-checking a government minister gives them a greater chance of media coverage. But I worry that it might be for less benign reasons related to political spin – seeking credit and basking in the reflected glory of all these new investments, which to the non-expert eye look to be something novel, rather than research council business as usual.  To be fair, there are good arguments for thinking that the current government does deserve some credit for protecting research budgets – a flat cash settlement (i.e. cut only be the rate of inflation each year) is less good than many want, but better than many feared. But it would be deeply misleading if the general public were to think that these announcements represented anything above and beyond the normal day-to-day work of the research councils.

Jo VanEvery tells me via Twitter that ministerial announcements are normal practice in Canada, but something doesn’t quite sit right with me about this, and it’s not a party political worry.  I feel there’s a real risk of appearing to politicise research.  If government claims credit, it’s reasonable for the opposition to criticise… now that might be the level of investment, but might it extend to the investments chosen?  Or do politicians know better than to go there for cheap political points?

Or should we stop worrying and just embrace it? It’s not clear that many people outside of the research ‘industry’ notice anyway (though the graphene announcement was very high profile), and so perhaps the chances of the electorate being misled (about this, at least) are fairly small.

But we could go further.  MEPs to announce Horizon 2020 funding? Perhaps Nick Clegg should announce the results of the British Academy/Leverhulme Small Grants Scheme, although given the Victorian origins of investments and wealth supporting work of the Leverhulme Trust, perhaps the honour should go to the ghosts of Gladstone or Disraeli.

ESRC success rates by discipline for 2012-13

Update: 2013/14 figures here.

WA pot of gold at the end of a rainbowith all of the fanfare of a cat-burglar slipping in through a first floor window in back office of a diamond museum, the ESRC has published its Vital Statistics for 2012-13, including the success rates by academic discipline.  I’ve been looking forward to seeing these figures to see if there’s been any change since last year’s figures, which showed huge variations in success rates between different disciplines, with success rates varying from 1 in 68 for Business and Management and 2 in 62 for Education compared to 7 of 18 for socio-legal studies.

The headline news, as trumpeted in the Times Higher, is that success rates are indeed up, and that “demand management” appears to be working.  Their table shows how applications, amount of money distributed, and success rates have varied over the last few years, and has figures for all of the research councils.  For the ESRC, the numbers in their Vital Statistics document are slightly different (315 applications, 27% success rate) to those in the Times Higher table (310, 26%) , possibly because some non-university recipients have been excluded.  The overall picture is hugely encouraging and is a great improvement on 14% success rates last year.  And it’s also worth repeating that these figures don’t seem to include the Knowledge Exchange scheme, which now has a 52% success rate.  This success rate is apparently too high, as the scheme is going to end in March next year to be replaced with a scheme of passing funding directly to institutions based on their ESRC funding record – similar to the EPSRC scheme which also delegates responsibility for running impact/knowledge exchange schemes to universities.

For the ESRC, “demand management” measures so far have largely consisted of:
(i) Telling universities to stop submitting crap applications (I paraphrase, obviously…..)
(ii) Telling universities that they have to have some kind of internal peer review process
(iii) Threatening some kind of researcher sanctions if (i) and (ii) don’t do the trick.

And the message appears to have been getting through.  Though I do wonder how much of this gain is through eliminating “small” research grants – up to £100k – which I think in recent times had a worse success rate than Standard Grants, though that wasn’t always the case historically.  Although it’s more work to process and review applications for four pots of 100k than for one of 400k, the loss of Standard Grants is to be regretted, as it’s now very difficult indeed to get funding for social science projects with a natural size of £20k-£199k.

But what you’re probably wondering is how your academic discipline got on this time round.  Well, you can find this year’s and last year’s Vital Statistics documents hidden away in a part of the ESRC’s website that even I struggle to find, and I’ve collated them for easy comparison purposes here.  But the figures aren’t comparing like with like – the 2011/12 figures included the last six months of the old Small Grants Scheme, which distorts things.  It’s also difficult (obviously) to make judgements based on small numbers which probably aren’t statistically significant. Also, in the 2011-12 figures there were 43 applications (about 6% of the total) which were flagged as “no lead discipline”, which isn’t a category this year.  But some overall trends have emerged:

  • Socio-legal Studies (7 from 18, 3 from 8), Linguistics (6 from 27, 5 from 15) and Social Anthropology (5 from 18, 4 from 5) have done significantly better than the average for the last two years
  • Business and Management (1 from 68, 2 from 17) and Education (2 from 62, 2 from 19) continue to do very poorly.
  • Economics and Economics and Social History did very well the year before last, but much less well this year.
  • Psychology got one-third of all the successes last year, and over a quarter the year before, though the success rate is only very slightly above average in both years.
  • No projects in the last two years funded from Environmental Planning or Science and Technology Studies
  • Demography (2 from 2) and Social Work (3 from 6) have their first projects funded since 2009/10.

Last year I speculated briefly about what the causes of these differences might be and looked at success rates in previous years, and much of that is still relevant.  Although we should welcome the overall rise in success rates, it’s still the case that some academic subjects do consistently better than others with the ESRC.  While we shouldn’t expect to see exactly even success rates, when some consistently outperform the average, and some under-perform, we ought to wonder why that is.