The many paths to PhD study

I presented at the Vitae Researcher Development International Conference today. My slides have been published and this post is a summary of the issues covered in my talk.

Every year more than 20,000 students embark on a journey towards qualifying with a PhD. As part of that journey they make a significant contribution to the research endeavour. And when they graduate they progress into all sorts of careers, inside and outside of research, here and overseas, bringing the benefits of doctoral training in a myriad of ways.

It is hugely important that we set a policy environment that ensures that talented people with the commitment and aptitude for PhD study make the successful transition, with the minimum of barriers, and certainly no barriers that lock people out of this course for reasons outside of their control. To set this policy environment we need to understand how and when the transition happens, who makes the transition and what motivates them.

New data and new analysis is illuminating the transition process, and it turns out to be more complex than many might think. HEFCE analysis published last year demonstrates that there are some students who transfer directly from their undergraduate courses within a year or two, and without acquiring any additional postgraduate qualifications. But for others there is a much longer gap between their first degree and PhD study, often including a period studying a taught postgraduate course.

The students who transfer directly have some particular characteristics. They are mostly male, mostly study STEM subjects, and mostly graduate from more selective institutions in terms of undergraduate entry.

New analysis has shown that the group who begin their PhD studies after a period of taught postgraduate training are more likely to be in the social sciences or humanities, but this is not exclusively the case. For example, around a third of the students starting a PhD in the Life Sciences have a prior postgraduate qualification. Those with prior qualifications also tend to have longer gaps between their last period of study and starting on PhD. In contrast to the direct transferrers, these students are moving from study to the workplace and back again over an extended period before PhD study.

Understanding the many and varied pathways to PhD is important to the policy goal of minimising barriers to the pursuit of doctoral study. The challenges facing students taking the longer, more complex routes involving taught postgraduate study will be different from those moving directly from undergraduate courses. There will be different financial challenges, for example. Even navigating the processes of recruitment and selection for PhD places may be more complex for those students doing so from a position outside of the Higher Education sector. These issues are strongly confirmed by a qualitative study of the recruitment and selection of PhD students carried out for HEFCE by CRAC.

Further insight into the transition into PhD study is also coming from the new Intentions After Graduation Survey (IAGS). This survey, part of the National Student Survey, is providing important information on the proportion of final year undergraduates who are planning postgraduate study, and their motivations for doing so.

According to these data, some 44% of final year students are either 'certain' or 'likely' to progress to postgraduate study, and around a fifth of these express an intention to study for a doctoral degree. A further 14% are planning a postgraduate taught course as a step towards a PhD. This information will be an important baseline for discerning any effects of the undergraduate fee regime on intentions for further study. But the survey is also revealing important information about the transition. Some ethnic groups, for example, have a very much higher expressed intention to progress to PhD study than is achieved in reality, helping to pinpoint potential barriers to progression.

So there are many paths involved in progression to PhD study, each with their own issues and possible barriers. Does the policy environment appropriately cope with this diversity? At one level the answer is yes – the evidence published today suggests that there is no shortage of well-qualified candidates applying for places. But in other respects we are less successful. There are still issues with the diversity of the PhD student population; in terms of gender, ethnicity, disability and socio-economic background the population does not reflect the representation in the undergraduate population from which they are drawn. To address these issues a better, more nuanced understanding of the pathways of transition is essential.

 

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On commonplace books

If you are looking to kill some time try Googling 'commonplace book'. You will find an endless stream of fascinating material, both examples of commonplace books themselves, and writing about commonplace books, including, eventually this post.

The commonplace book is a seventeenth century innovation, and the idea is a simple one: A notebook for capturing interesting quotes from reading, ideas, snippets of text for writings, diagrams, sketches, anything that comes to mind. Over time these notebooks developed into personal anthologies of thought and reflection, and were often accompanied by elaborate schemes of indexing, so that the entries could be located and themes extracted.

The age of the internet has the potential to be the golden age of the commonplace book. First we have an unprecedented opportunity to read and access texts of all sorts, and secondly it is simple – no more complicated than 'copy and paste' – to bring elements of text together into places where search tools allow the rapid compilation of themes.

I have been using Evernote as a commonplace book for a number of years. All sorts of things get saved into my Evernote notebooks, some of them automatically, and then the search function allows later retrieval. For example, a quick search for 'commonplace book' reveals that, rather spookily I was contemplating drafting a blog post on the topic exactly a year ago today. I was also able to identify previous reading I had done about commonplace books, and a quote from 'Where Good Ideas Come From: The Natural History of Innovation' by Steven Johnson:

The great minds of the period—Milton, Bacon, Locke—were zealous believers in the memory-enhancing powers of the commonplace book. In its most customary form, “commonplacing,” as it was called, involved transcribing interesting or inspirational passages from one’s reading, assembling a personalized encyclopedia of quotations.

The search also provided me with a link to a related piece I had read by James Gleick on digitising books.

The commonplace book was a powerful idea in the seventeenth century but digitised text takes it to a new level. This idea is explored and developed further by Johnson in a blog post. In this post Johnson points out that searching for text can, in an instant, assemble a type of commonplace book using an algorithm. The google search I linked to at the beginning of this post is an example. The search results are presented in a particular order, and to an extent that order is customised to the individual. A new association of words and ideas is being created, specific for the reader, and in no way predictable by the authors of the original texts:

What you see on [a Google search results] page is, in a very real sense, textual play: the recombining of words into new forms and associations that their original creators never dreamed of.

Johnson goes on to consider the value that is created through these new combinations of text:

When text is free to combine in new, surprising ways, new forms of value are created. Value for consumers searching for information, value for advertisers trying to share their messages with consumers searching for related topics, value for content creators who want an audience. And of course, value to the entity that serves as the middleman between all those different groups.

And there is a following discussion on paywalls and technologies that prevent text to be mined and combined in new ways. The whole, long post is well worth a read. His conclusion is that access to text and reasonable re-use rights are central to ensuring that the potential benefits of the internet-enabled commonplace book. In Johnson's words we need text to be in a commonplace book, not a glass box.

This is one of the reason that open access to the scholarly literature is so important. At the moment much of the scholarly literature is, at best, in a glassbox and at worst in a locked chest for which only a select few hold the key. Not only does the scholarly literature need to be made more available, but also licensed in such a way that re-use and re-purposing is possible. As Cameron Neylon has recently argued permissive licensing is essential. Access through glass boxes, like the Access to Research initiative is also deeply limited in its value.

I wonder what those seventeenth century 'commonplacers' would make of all this. I think they would be amazed by the potential of the digital commonplace book, but shocked to see how we have locked away some of the most valuable text, preventing real value to be obtained.

 

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Openness and research integrity

Last week I spoke at the annual conference of the UK Research Integrity Office. The slides I used have been published, and this post sets out the argument that I made.

Research misconduct happens. There is less certainty about how much research misconduct, but there is no doubt that we need a policy response to address the issue. In formulating this response it is important to acknowledge that the term ‘misconduct’ covers a range of activities, with different motivations, and levels of seriousness. And that this variation will influence the policy response.

At one end of the spectrum are deliberate acts by researchers to falsify or misrepresent research. I believe this is rare, although it often the type of misconduct that gets the most publicity. Further down the range are small acts of misconduct that, while deliberate, aren’t motivated by a desire to falsify the conclusions of the research. In this category I would include leaving out inconvenient data points, or perhaps even inconvenient experiments, that challenge conclusions that the researcher strongly believes, often on the basis of other evidence, to be true. At the other end of the spectrum is less deliberate misconduct, that stems from lack of knowledge or expertise on the part of the researcher, or possibly the cutting of corners to speed up the research process. This is accidental misconduct where the researcher doesn’t realise that anything is wrong.

Regulation – rules, processes to enforce them, and sanctions applied when they are broken – clearly has an important part to play across this spectrum, and is probably the only policy option for tackling deliberate and large-scale fraud. However, in tackling most misconduct there is an essential and important role in ensuring that we have the right culture within our universities and research organizations. We need to focus on stopping misconduct from happening; catching misconduct after the event is both a very costly approach, but it is also less effective to allow poorly conducted or fabricated research to be disseminated.

If we accept that tackling misconduct is about changes to the whole culture within which research is conducted, then rather than being a specific ‘policy issue’ it becomes a cross-cutting theme that underpins the whole research policy agenda. We need to consider the implications for the research culture of all the policy interventions we make: from the design of funding processes, to the mechanisms of research assessment. The current investigation by the Nuffield Council on Bioethics will, no doubt, provide some useful insights into the relationship between policy interventions and the research culture that emerges.

There is one aspect of the research culture that stands out for me – the extent to which research is conducted openly, and especially the extent to which research data is made available for scrutiny and further analysis. As has been eloquently argued by Andrew Rawnsley there is, or ought to be, an intimate link between research integrity and research openness.

This is not just because the sharing of data allows other researcher to check the findings of research. There is also reason to believe that a presumption of openness will influence research cultures in a positive way. For example, a study carried out in 2011 by Wicherts, Bakker and Molenaar concluded that:

the reluctance to share data [was] associated with weaker evidence (against the null hypothesis of no effect) and a higher prevalence of apparent errors in the reporting of statistical results. The unwillingness to share data was particularly clear when reporting errors had a bearing on statistical significance.

As these authors rightly point out the study describes a correlation, and it is not possible to draw a causal inference. They propose a number of possible explanations, but one is particularly compelling:

statistically rigorous researchers may archive their data better [...and,so...] will more promptly share their data

There could be a deep cultural linkage between the rigour with which data is analysed, the care with which data is curated and the willingness to share. Or maybe the act of sharing itself encourages a further review of the data and its analysis, a point recently well made by Dorothy Bishop. Either way, data openness should be part of the research culture that supports and fosters research integrity.

As I have written previously, opening up research data is not without its challenges. But I would argue that the benefits that more openness will bring for research integrity are significant, and provide part of the case for universities, funders and journals intervening to foster the culture of open research.

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How many research mavericks do we need?

The topic of ‘scientific mavericks’ is receiving some attention at the moment. There was a letter, signed by a number of Nobel laureates and FRSs among others, published this week in the Guardian suggesting that the current structures inhibit mavericks, and that this is a problem. And this follows on the heels of comments by Peter Higgs last year. The arguments in the Guardian letter are flawed in my view (there is an excellent post by Jenny Rohn that sets out why), and based on a very particular reading of history.

But the question of providing space within the research policy landscape for the exploration of radical ideas and approaches is an important one.

Of course, in the policy world we more often talk about ‘high risk/high reward’ research rather than mavericks, but the basic concept is the same. The question that is regularly debated by research policy people is how to ensure that the structures and environment we create around research don’t produce barriers that prevent researchers from trying out ‘crazy ideas’. In thinking about how to tackle this question there are a number of challenges. A big one is that we don’t actually know how much ‘high risk/high reward’ research is going on. As Jenny indicates in her post, researchers find ways to do this type of work, and, by definition, most of it will fail, so we will never hear about it. The successful projects – the extraordinary findings supported by extraordinary evidence – can potentially look very mainstream quite quickly, so the visibility of successful ‘high risk/high reward’ research can be low too. In the absence of good evidence on the volume of activity it’s hard to know whether the current policy environment is really encouraging or inhibiting.

By far the biggest challenge in formulating policy for ‘high risk/high reward’ research, however, is deciding how much research of this type is needed. I think there definitely should be space for some, but it is also self-evident that we don’t want all research to be like this. That would result in too much public money being spent on research that leads nowhere, not even advancing its discipline, let alone bringing wider benefits to society. As in many areas of research policy, we need to find the appropriate balance point.

Part of the responsibility for addressing this issue lies with researchers and universities themselves. Through the UK’s dual funding system, universities have access to funding, provided by HEFCE and the other UK funding bodies, that could be used to support ‘high risk/high reward’ research. Whether the block grant funding is used in this way, and, if it isn’t, why not, are interesting questions worth exploring. It is the case that researchers and universities are themselves well placed to decide how much ‘high risk/high reward’ research should take place. Perhaps increasing the proportion of research funding that is distributed through this route might shift the balance, and a allow a few more mavericks to be nurtured?

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Open access and academic freedom

There is always a point in any policy-making process where a clash of objectives or values takes place. Sometimes different aspects of what you are trying to achieve turn out, on analysis, to be in conflict with one another. In other cases, it emerges that objectives are in opposition to principles which were held to be important at the start of the process. These dilemmas are one aspect that makes policy-making a challenge and enjoyable, but also they often result in some stakeholders, sometimes all stakeholders, ending up unhappy with the outcome.

There is one of these dilemmas at the heart of making policy about open access to research publications. The whole point of an open access policy is to maximise openness. But this is in conflict with a core value that underpins research and higher education policy-making – the principle of academic freedom. If we take this to include the freedom to publish research in whatever journal researchers wish too, then it follows that an open access policy must allow publication in journals that restrict access in order to respect academic freedom. But will a policy with such a loop-hole ever achieve its objective of more openness?

It would be easy to think that confronting dilemmas like this is nothing but a problem, but in fact it is incredibly helpful. It forces you to think deeply, and challenge the assumptions that underpin principles and objectives. In this example, is it really the case the academic freedom demands absolute control over the vehicle of publication? On reflection, I think the core of academic freedom is the ability to publish ideas at all, and that, especially now, doesn’t rest on using a particular academic journal, or even an academic journal at all. It could even be argued that the peer review process is itself a barrier to academic freedom, imposing censorship, restricting the dissemination of ideas to those approved of by peers. I am not sure I would go that far, but the more I consider this issue, the more I am convinced that the prize of maximum dissemination is more important that maintaining an excessive interpretation of the notion of academic freedom.

 

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Open data reflections

I am spending a lot of time thinking and reading about open research data at the moment, in preparation for some policy development work in the New Year. I am personally positive about the open research data agenda, seeing lots of benefits to more sharing of data, both for research itself and wider. There are some strong public-good arguments for making data available, including, but not limited to, potential economic benefit.

It is common to find these positive arguments articulated. As I have argued recently in a post on the Sciencewise blog, any policy intervention around open research data needs to balance the benefits against the costs, which are not so well understood. There are also complex issues around the politics of open data that have been discussed in an excellent blog post by Rob Kitchen. The post expands on four critiques of open data arguing that it:

  • lacks a sustainable financial model;
  • promotes a politics of the benign and empowers the empowered;
  • lacks utility and usability; and
  • facilitates the neoliberalisation and marketisation of public services.

The post concludes that

we lack detailed case studies of open data projects in action, the assemblages surrounding and shaping them, and the messy, contingent and relational ways in which they unfold. It is only through such studies that a more complete picture of open data will emerge, one that reveals both the positive and negatives of such projects, and which will provide answers to more normative questions concerning how they should be implemented and to what ends.

Real food for thought there, and a welcome stimulus to reflect on the assumption that open data is inevitably positive.

 

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On impact

Innovation is a complex business, but Seth Godin has some thought-provoking words in his post today:

Inventing isn’t the hard part. The ideas that change the world are changing the world because someone cared enough to stick it out, to cajole and lead and evolve.

It seems to me he has captured something important there about impact, and what needs to be done to achieve it.

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