campaign for social science sage annual lecture 2015 · idea-generating role of the social...

Social science for public good: who benefits, who pays?

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CAMPAIGN FOR SOCIAL SCIENCE SAGE ANNUAL

LECTURE 2015


Sharon Witherspoon MBE

Delivered at Sixty One Whitehall, London SW1A 2ET

On 7 December 2015

Sharon Witherspoon worked for several years in applied social science research, designing

and carrying out evaluations of government and employment benefit programmes in the

1980s, the first quantitative descriptive study of solicitors in private practice, and serving as

part of the original research team on the British Social Attitudes survey. She worked at the

Nuffield Foundation for 19 years, first leading its programmes of social research and social

policy, and then for three years as Director; she also led the Q-Step programme to improve

quantitative research skills for UK social science undergraduates. She was awarded an MBE

for services to social science in 2008, received the British Academy President’s Medal in

2011, and was awarded an honorary doctorate by University College London in 2015. She

was conferred with the Fellowship of the Academy of Social Sciences in 2010.


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INTRODUCTION

I want to start by thanking the Campaign

for Social Science and the Academy of

Social Science that backs it, and SAGE

publishing, which has done so much to

support the social sciences and whose

founder, Sara Miller McCune has been a

long-term influence for good, for

sponsoring this annual lecture. I note too

that there are number of supporters of

UK social science who support aspects of

the work of the Campaign, including the

ESRC and the British Academy, who are

also concerned to improve UK social

science and ensure its continuing rigour

and impact.

I am conscious that the first two speakers

in this annual lecture series, David

Willetts, now Lord Willetts, and Craig

Calhoun, have set a high standard. Both

of their lectures bear re-reading; both are

on-line. I want to follow in their footsteps

in some ways – standing on the shoulders

of giants, as it were – by taking, as indeed

the Campaign was founded to do, a

positive and un-defensive stance about the

strengths of contemporary of UK social

science. But I don’t want to shy away

from taking a close look at the challenges

facing UK social science and I want, as a

strong supporter, to raise questions that

the social science community itself needs

to address – or needs to address better --

in the coming years in order to achieve all

that it is capable of.

TOPICS THAT WILL BE

ADDRESSED

I should start by giving a quick overview of

the issues I want to address – and the

taken-for granteds that I won’t address.

These latter probably need stating

forcefully early on.

I take it for granted that social science

isn’t important solely because of its

immediate usefulness – to government or

policy-making, the private sector or

business skills, or even for wider public

debate. Social science is part of the

general knowledge that underpins our

culture. I believe that wholeheartedly.

That means I understand and support the

idea-generating role of the social sciences,

and what Paul Nurse’s recent report

called ‘discovery science’. In social

science, ideas are important, not least

because of the general role of pure ideas

in forming policy and public debate. As

John Maynard Keynes noted: "(…) The

ideas of economists, and political

philosophers, both when they are right

and when they are wrong, are more

powerful than is commonly understood.

Indeed the world is ruled by little else.

Practical men, who believe themselves to

be quite exempt from any intellectual

influences, are usually the slaves of some

defunct economist. Madmen in authority,

who hear voices in the air, are distilling

their frenzy from some academic scribbler

of a few years back. (...) Soon or late, it is

ideas, … which are dangerous for good or

evil." So I don’t underestimate the

importance of purely idea-generating

work but that’s not mainly what I’ll speak

about.

In any case, the distinction between

discovery research and applied research is

an analytical distinction. Empirically not

only are there muddy boundaries but

there is iteration between the two. Who

can doubt that a more nuanced notion of

rational economic action and its limits

owes much not only to conceptualisation

but empirical experiments large and small

carried out partly under the banner of

behavioural economics? By social science

I mean a range of ways of combining

substantive knowledge about human

beings with a concern for methodology.


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Of course, the point of this annual lecture

is to speak both to the social science

community and to those outside it who

are interested in it and I will speak about

the issues I know best and have thought

most about. So I’m largely going to talk

about the challenges facing empirical social

science research in the UK over the next

10 years or so. While autobiography

doesn’t determine everything, it’s no

doubt relevant that I worked for many

years in applied social research settings

before joining the Nuffield Foundation,

one of the few social science funders in

the UK. There I worked on programmes

to strengthen the evidence and rigour of

various policy fields, to develop ways of

supporting general UK social science

capacity – and of course to speak in

favour of the importance of social science

in various policy-making settings. That

means I will focus on the important role

of social science in helping us understand

our world, and dare I say, help use that

understanding to make it better. The fact

that I don’t think that’s a naïve statement

is, I hope, a testament to my belief in the

importance of sound social science. It

does mean that I’m aware of the wide-

range of social science – syntheses of

what we know, descriptive research,

research that aims to understand the

strength of causal mechanisms and

evaluations - that illuminate our social

world, and should underpin some of the

decisions we make about how to improve

it.

I should add that I won’t talk only about

the work carried out in universities. I

include the very strong social science

done in independent research institutes

(such as IFS, NIESR and the National

Foundation for Educational Research), and

charitable think-tanks such as the

Resolution Foundation. I also include the

social science done within government,

including much of the work of ONS and

the Government Social Research

network. All these contribute to the

social science research base, and often

with rigorous research which has high

impact. It’s that wider institutional

framework I mean when I talk about UK

social science.

BACKGROUND CONTEXT

By any measure, UK social science is

strong. The evidence gathered in The

Business of People on international

citations, the various ESRC bench-marking

reviews are among the evidence that

shows the strong international standing of

much UK social science. REF impact case

studies testify to the impact of social

science, both in fundamental research and

in more applied work. The Chief Scientific Adviser Sir Mark Walport has written

often of the contributions of social

science, most recently in THE

acknowledging the role that anthropology

played in strategies to tackle Ebola.

Thanks to actions taken over a number of

years by various governments but

deepened most recently by the decisions

made by Lord Willetts when he was

Minister for Science, we also have a

robust infrastructure for many important

data sources, and to address some of the

data challenges that face us. Over the last

few years, for the first time in decades, all

the main birth cohort and longitudinal

studies have secure homes and

infrastructure funding for development.

There is a regular structure for reviews

for future rounds. The UK Data Service,

which used to concentrate mainly on its

archival function, now takes a more

proactive role to encourage greater use of

data, including making such use easier,

training those who wish to use data and

generally taking an active role in

promoting access to government data

series, including national statistical series,


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so that they are available to the widest

possible range of users. The ESRC has

been funded and worked hard to create

its Administrative Data Network to

promote the use of government data that

needs stronger safeguards, and taken

innovative steps to promote the use of

‘big data’ – data collected from that

gathered by local government and the

private sector for reasons other than

research but that can have a clear

research use. These are early days but

arguably this support and the strategic

approach taken by a number of

institutions have given UK social science a

real international advantage in the kinds of

empirical work that can potentially be

done.

All this is to be welcomed – these are,

after all, the social science equivalents of

the ‘well-found laboratory’. And even in

countries with strong social science

communities, such as the United States,

there is often a far less generous and

supportive atmosphere for national

governmental discussions about

supporting social science. One only has

to think of the recent debates in the US

about whether or not political or other

social science research can be funded by

the National Science Foundation to think

about how different things might be.

But while all this – and the strong

evidence compiled by The Business of

People about the wider usefulness of social

science– is clearly what 1066 and All That

would characterise as A Good Thing,

there is, I think, little room for

complacency if we look at the current

state of UK social sciences. As a

community, I think it behoves us to

examine ourselves some of the areas in

which we might grade ourselves as ‘could

do better’.

INTERNAL CHALLENGES

First, in many important areas, due both

to disciplinary strengths, the difficulty in

getting data and the lack of attention by

funders, we simply have far less empirical

research than I would argue we

objectively need. For instance, drawing

on my many years as a funder, I would

observe that in many areas of child

development – ranging from child

protection to more fundamental studies of

child development and educational

outcomes – we don’t have the robust

cumulative work that would yield enough

evidence for good policy or deepen what

should be a cumulative understanding of ‘what works’. This isn’t to decry the

work of many child psychologists, social

workers, educationists and the still

relatively new ‘what works’ centres, or

the excellent work done by funders such

as the Sutton Trust which in education at

least seeks to redress this balance. But

many of the disciplines that have

substantive understanding of particular

issues have not been buttressed by the

quantitative training to look at outcomes

in a structured way. And in this area,

responsibilities for data collection and

data access are fragmented among local

authorities and schools; and central

government hasn’t taken the strategic

approach to address these issues. I know

there are promising developments afoot.

But I’m trying to make the point that this

isn’t simply a rhetorical cry to jump on

the data bandwagon, but to note that

there are many areas, clearly important to

our well-being, where we face structural

challenges. Some of them are of data and

some of them of skills and training of

researchers, but they require strategic

investments to redress. That we don’t

have that evidence is not just a matter of

resources, and not just something for

which we should blame others. They also reflects characteristics of the way the

social science community itself is

structured.


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For instance, to my mind there is a

worrying divide – in training, and in where

people work – between those with data

collection skills and those who would

regard themselves primarily as analysts.

This is perhaps particularly visible for

structured data collection. I will return to

this below, but I note that many of the

strongest data collection – and dare I say,

fundamental research design – skills reside

in government, market and independent

social research institutes and so on, while

advanced analytic skills are often more

likely to be held by those working in

universities and some independent

research institutes. This affects planning

for many large scale data projects, where

difficulties in data collection are often

addressed only late relatively late in the

planning stage. As to why this matters, I

need only give as an example discussions

over the performance of the 2015 general

election opinion polls, where we learned

clearly that not all data collection

difficulties (in this case in getting a truly

representative sample) can be

compensated for by sophisticated analysis

(at least that’s my own view). Those

planning for the 2021 Census reached a

similar conclusion about the difficulties in

subjecting administrative data to

sophisticated matching and weighting

without some underlying structured data

collection to assess representativeness. In

the future, intelligent use of ‘big data’ will

absolutely make it more, not less,

important to understand the process by

which data are generated and

constructed, in order to avoid drawing

misleading conclusions. But we haven’t

got a strong internal consensus on this,

much less made the case for it in wider

discussions.

When Professor Calhoun gave this lecture

last year, he spoke of the ‘near secession’

of economics from the social sciences. To

the extent that this is an issue, I think it

raises issues not only of the self-

conception of economists but also for

those who us who are social scientists but

not economists – and before I’m found

out I confess that I was trained as a

sociologist! One issue is that the best

economics has the rigour of quantification

and clear models and an understanding of

research design, while appreciating that

quantification needs to be tethered to

clear questions and that conclusions

should be limited to the questions it is

able to answer. (Note I said the best

economics…) Over a number of years

as a funder, I was struck by how often I

turned to the excellent Institute for Fiscal

Studies to do work that in theory

sociologists or psychologists could (and

perhaps even should) address. To what

extent, for instance, is it marriage per se

or the ‘selection’ of people into marriage

(or more clearly, the different decisions

different types of people make about

whether or not to get married) that

accounts for the significantly better

outcomes on average for children of

married parents, compared to those who

do not get married? How have women

and their male partners responded in the

labour market to the increases in the age

at which women become eligible for state

pensions? The fact that IFS started with a

clear understanding of the need to think

about research design, how to categorise

different types of social causes, how to

incorporate behavioural and attitudinal

aspects and so on meant that they could

marshal evidence and present clear

analysis that revealed some underlying

patterns.

All this by way of saying that the

quantitative skills deployed weren’t simply

about using structured data and applying

fancy statistical analysis abstracted from

underlying social causes. I would argue


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that the quantitative training generally

viewed as central to economics and much

psychology simply helps in clarifying

relevant issues of research design, what

are and are not appropriate measures, and

assumptions, and what can or what (or

under what conditions generalisations can

be made). My personal view is that this

isn’t always as closely related to the

substantive field of economics or

psychology as to the training and

intellectual formation required by these

disciplines.

I want to state clearly that this is not at all

a statement about the usefulness of

‘qualitative’ techniques – small scale

studies, ethnographies and the like. These

are essential as means of understanding

social processes, cultural factors and often

the mechanisms by which relationships

uncovered by statistical analysis work.

But too many social scientists lack some

of the basic tools to think about issues of

representativeness, to assess good vs bad

evidence or to tackle issues that would

benefit from disciplinary paradigms and

assumptions other than economics. This

informed the reasoning behind the Q-Step

programme, which I helped develop while

I was at the Nuffield Foundation, along

with support (both funding and intellectual

support) from the ESRC and HEFCE.

That there is a sort of market failure in

some UK undergraduate social science in

this regard is not, I believe, just a matter

for social science. It also means many of

those trained as social scientists can’t

contribute as strongly as they should to

broader public discussions as citizens.

The Q-Step prospectus we released for

the funding programme tried to lay out

transparently our grounds for concern

and why we thought a strategic

intervention was needed to bring critical

mass to institutional efforts to address the

issue. It is early days but so far I gather

the news from Q-Step is promising. But I

am of the clear view that this is merely a

first step; it’s a big complex issue and will

take time to address. And in the context

of new developments – in the data

available, in increasing power analysis

techniques and computing power and so

on, as David Rhind persuasively argued in

his lecture The Impact of Big Data on Social

Research to the Social Research

Association last December – we are like

Lewis Carroll’s Red Queen, running as

fast as we can simply to stand still. We

will find some areas of social science

overtaken by those who simply use big

data and coded algorithms if we cannot

engage as a community with these issues.

This was one reason that the British

Academy, in its excellent report, Count Us

In, tried to focus on the wider needs for

quantitative skills for the social sciences,

for the economy and citizens whose

interests can’t simply be reduced to those

of consumers. And virtually every report

that has looked at this issue – and there

have been many – links this too to the

premature specialisation at secondary

school level. While I welcome Core

Maths as one means to address this, that

is still a small and relatively modest step

that ‘aspires’ to ensure that by 2020 most

students in post-16 education will

continue to study some form of maths. It

is unclear how many students will be

taking such courses in the next few years.

The problem is, as Count Us In argues,

Core Maths probably needs to be one of a

number of pathways foraddressing this

deficit if UK social science is to make the

step change in its tool kit that is needed.

We need to take a multi-pronged

approach, and stop playing a zero sum

game. Decisions by DfE about the

treatment of AS-levels may give some

concern if the numbers of entrants to AS


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maths falls in the next few years. As

Mathematics in Education and Industry has

most recently shown, the number of

entrants to A-level maths rose from

under 50,000 in 2003 to over 80,000 in

2015 (the solid black line), while the

comparable figures for AS maths were

under 60,000 in 2003 to over 150,000 in

2015 (the dotted black line). My own

view is that this indicator should function

as a canary in the mine – if the number of

students taking AS maths decreases

(especially if it decreases faster than the

roll-out and take up of Core Maths, as it

might well) we might want to think again

about pathways and about signaling. I

KNOW the difficulties in getting sufficient

numbers and quality of maths teachers

but, as Count Us In argued, that should be

an argument tackled separately and in a

variety of ways. After all, this is to some

extent a chicken and egg situation and

breaking into the complex causal chain

somewhere will require some strong

cultural signalling and a sense of urgency.

We need too to build into A-level social

science curricula more examples of

examining data and evidence and number,

alongside other methods, to raise

substantively interesting questions and

show that this really can be interesting,

and help in understanding. I know that

the British Psychological Association and

the Royal Geographical Society have

recently made various steps in this

direction. Again, this places demands on

our secondary teaching work-force. But

the arguments for doing so are not just

linked to economic case laid out in Count

Us In, but are vital to the intellectual well-

being of our social sciences. I fear if we

don’t’ have the confidence to tackle this,

we’re actually undermining our capacity to

improve.

To be clear, I am not arguing every social

scientist who enters university should

have Maths A or AS level. But I suspect a

world where about one in five of incoming

undergraduates studying geography or

psychology have an A-level in maths, and

fewer than one in ten of those studying

politics or sociology do so, is not helpful

to the breadth and reach of those

disciplines. This isn’t of course particular

only to the social sciences; I have heard

arguments that the biological sciences face

some of these issues, though to a lesser

degree. If time were longer, I might make

a feminist argument here about

advantaging disciplines with large numbers

of women students, but I’ll leave that to

the work of excellent groups like Your Life,

which aims to encourage more girls to

acquire number and data skills.

I understand all these take investment. But

we are not as loud in our demand as

social scientists for these skills in order to

yield better evince. And creating that

demand, not just among social scientists,

but a wide range of the public, also means

saying public policy discussions ought to

be linked with better evidence. These are

hard issues for the social sciences and

requires continued strategic investment,

since social and institutional change is

complicated and takes time. But as a

community, we have not always helped

create the demand for better evidence in

important fields – much less better use of

that evidence.

And creating that demand – not just

among social scientists but among a

wider-range of the public –also means

saying that public policy discussions ought

to be linked with better evidence, and we

need to take more responsibility for that.

We simply haven’t captured the public

imagination, much less public

commitment, that it’s actually important

to collect and look at better evidence

before governments roll out what are


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essentially experiments in people’s lives. I

don’t believe politics can or should be

reduced to technocracy; disagreements

over values are fundamental (and also

underpin legitimate debates within social

science). But when claims are made that a

policy change will result in particular

outcomes, we really ought to be able to

expect to see better evidence that this is

so.

To my mind, this argument about

quantification is very closely linked to the

need for more experimental approaches,

in all sorts of policy developments – I

commend the excellent NESTA report

Better Public Services Through Experimental

Government for arguments about how in

the social research on public policy we

need a far greater range and number of

explicit experiments. Clearly there are

external challenges -- few governments

are keen to commit themselves to

transparent evaluation and the longer

time-frames that such as approach

requires, as we learned when Sure Start

was implemented. But we in the social

science community must also take some

responsibility for not engaging in wider

public discussions and trying to stimulate

more demand for these experiments.

EXTERNAL CHALLENGES

Well, I know many will disagree with the

arguments I’ve just made, and I’ll be happy

to talk about that in questions. And they

are after all internal challenges in the

context of general health within UK social

sciences. But I hope to be at least as

provocative in looking at external

challenges, while starting from an

essentially optimistic view that, just as our

underlying health is good, so too the

external environment has many positive

aspects.

First, I think it is probably true to say –

and many have done so, including

Professor Calhoun in his lecture last year,

and the Nurse Review – that many of the

most important problems – and many

intellectually interesting ones –

increasingly require multi-disciplinary and

interdisciplinary research. That’s not to

say that training doesn’t benefit from a

strong disciplinary base especially in early

stages. But there are good reasons to

attend to multi-disciplinary perspectives

both for fruitful intellectual development

and for social research that addresses

these questions.

This isn’t a question of priorities being

dictated by other disciplines or narrowly

by policy-makers. Increasingly we expect

sophisticated psychology about child

development to attend to genetic

influences, family structure and formation

and relationships and the role of schools;

we expect economic studies to attend to

behavioural factors and social context; we

expect studies of health to consider the

context within which health care is

provided and the social structure that

presents challenges and solutions to

individual behaviour. The world – and

policy certainly – would be poorer if

social science didn’t confidently play its full

role in examining these and other

challenges. And I would argue social

science will be poorer too. And how

many of us social scientists have seen

natural or physical scientists seek to

collect evidence on science in society

without understanding that some of their

data needs to pay attention to hard-won

lessons from social science and social

statistics?

Yes this sort of multi-disciplinary and

inter-disciplinary work doesn’t just

happen, it’s not just bringing together

short term, ad hoc teams It requires

social structures – be they teams,

institutes or funding streams – that

require infrastructure investment.


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We also need a greater range of models

for carrying out multi- and inter-

disciplinary work. I note with interest

Cardiff University’s recently created its

Social Science Park SPARK and that

University College London now organises

some of research in Grand Challenge

teams. These structures require

institutional investment above and beyond

traditional research funding. Some will

work and some will be less successful.

But the funding challenges for setting up

these sorts of entities is something that I

know the ESRC and other funders, as well

as institutional leaders, will be addressing

over the next few years.

More worrying, is the challenge posed by

various developments – and lack of

developments – in data protection which

restricts our ability to carry out serious

social science research. It should go

without saying that I not only understand

concerns over data protection and

confidentiality but am deeply committed

to privacy and confidentiality and worried

about the misuse of personal data. But if I

may say so, I believe the social science

community has long had a more robust

regime for considering these issues than

has generally been appreciated – and yet

we’ve been fairly quiet in our advocacy on

these issues.

This has recently been crystallised by the

UK Data Service, following ONS, in their

‘5 Safes’ principles. These require that we

move from a narrow-minded and, to my

mind, wrong-headed focus solely on

individual specific consent. That specific

consent would require for instance that

each secondary re-use of data, or data

linkage for which general permission

would in many cases have been given, be

referred back to research participants for

an opt-in—in most cases making the

research impossible. Not all research that

could be done should be done, and

consent is certainly an important issue.

But – I can’t help being a sociologist in

wondering about the way that this debate

which privileges individual consent actually

means that powerful, private stakeholders

like private firms (who use long consent

forms before a transaction is completed,

and who can argue that data sharing

within a multinational is not in fact shared)

can have access to data, but researchers

carrying out research for public benefit

and which is published for transparent

public scrutiny find it ever harder to do

so. By focussing only on individual

consent, we risk replicating a privatisation

of resources – in this case evidence – that

doesn’t serve the wider public good but

those of powerful interests.

We need to be much stronger in facing

this external challenge with clearer

advocacy that, in order to safeguard the

public interest both in data protection and

in the wider and more democratic use of

data collected often at great public

expense, but that consent is not the only

principle we have to think about these five

principles.

o Safe projects: projects genuinely

for public good (and publication of

results is an important indicator

here) with a proportionate and

independent consideration of the

public good. This requires

considering the role of specific

consent or general consent where

specific consent about each

independent data use would

preclude the work, or lay

involvement in decisions about the

proportionate public benefit if that

is not possible. I think this means

being explicit that the definition of

‘public benefit’ is not a matter of

precise a priori theological


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definition – it would be hard, I

suspect have such a purely logical

or philosophical definition. But it

would require consideration of

public benefit by an independent

scrutiny mechanism that brings the

judgements of others beside the

researchers or funders into play. If

we have learned anything about

the failures of research into

scientific experiment on humans, it

is that having lay involvement in

such oversight is crucial. The

ESRC’s Administrative Data

Network is a model of this sort of

scrutiny, with each proposal being

reviewed by an outside committee.

But all social science funders have

long had in place independent

mechanisms for considering the

ethical and data protection aspects

of proposals. Such scrutiny is far

from being a fig leaf – it is

challenging, and it takes time and

resources. But it gives public

benefit research some way of

ensuring the interests of the

collectivity, and not just whoever

happens to be the data owner, are

taken into account.

o Safe people: much of the data

which our social science needs to

use for public benefit cannot by its

nature be ‘open data’. Virtually no

individual level data can be. So in

addition to consent we have

safeguards about the identify and

practices of researchers who can

adhere to agreed data protocols,

including protection of anonymity

and safe data handling and use.

o Safe settings: for the physical

and virtual handling of data of

varying degrees of confidentiality,

ranging from third-party linkages

to virtual safe labs to literal safe

rooms.

o Safe outputs: which govern the

ways in which data analyses should

be reported, to ensure data

protection in publication, while

allowing independent scrutiny of

the analysis techniques and

methods. This is not only to

produce better social science but

more open-ness to contestation

and debate. This is one reason I

argue that public benefit research

almost always has some

publication, something that is not

true for instance of all government

use of data.

o Finally, safe data – though I would

argue that this in a sense follows

on from the other ‘safes’. As a

community we are, I think, aware

that much data could, especially in

combination, present challenges to

data confidentiality. But this is not

simply an inherent quality of the

data themselves, but is also a

product of the other safety

mechanisms put into place.

And we actually have empirical evidence

that when the public engages with this

issue, they understand it. The excellent

work that the ESRC has supported – in

conjunction with, for example the Office

for National Statistics and MORI on public

attitudes towards the use of

administrative data – shows that the

public can, given sufficient time and

information, understand this. The Digital

Catapult has also recently produced

evidence about this, and why altruistic

motives matter to the public. It gives the

lie to the assertion that younger


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generations have a different view of data

protection and data privacy, but also to

the assertion that a unidimensional focus

on consent is the sole means of protecting

legitimate concern about privacy. This

may be a severe external challenge to the

role of social science over the next few

years.

Perhaps most pressing today are

continuing worries over the EU Data

Protection Regulations currently being

debated, in a complex triangulation of

competing drafts. As it stands, it is

possible that this regulation may, as one of

the drafts states, require ‘individual

specific consent’ for reanalysis – that is

consent to each new analysis, which

would vitiate much of the public benefit

analysis in health and social research. The

Wellcome Trust is doing excellent work

in promoting both public engagement and

policy discussion about this, and I would

advise any who have not done so to see

their webpage

http://www.wellcome.ac.uk/About-

us/Policy/Spotlight-issues/Personal-

information/Data-protection-legislation/

and sign up as a supporter of a public

benefit research pathway. But they tend

to stress health research and there are

wider social science questions – about

welfare and benefit reforms and who they

affect for instance – that would also be

affected if this regulation went the wrong

way.

In the UK, while we have general

government support – not least in funding

but also in depositing much government

survey data with the UK Data Service –

we still lack a concrete and coherent

framework that views public benefit

research as a positive public good. In the

absence of such a framework, government

departments all too often delay depositing

data, or deposit it with such restrictions

that it cannot be used by others, even

when they could safely do so. Uncertainty

creates risk aversion.

The issue of having a clear positive

pathway for public benefit research is one

challenge that requires a positive and

concrete lead from government, distinct

from the focus on data sharing to combat

fraud. I understand that this responsibility

remains, after its useful discussion over

possible legislation in 2013 and 2014, with

the Cabinet Office and it would be good

to see further action here, with a positive

framework for public benefit research,

separate from the links made within

government for fraud and so on. My own

modest contribution is to suggest that it is

not beyond the wit of parliamentary

drafters to define public benefit research if

they consider a structural and procedural

definition that requires external and

independent scrutiny, and well-defined

and appropriate protocols using the five

‘safes’. That allows a social and

transparent consideration of the degree of

public benefit and the degree of risk, and

could lead to a new examination of opt-

outs, rather than opt-ins.

I apologise for the rather geeky focus on

data protection – but I think that the

social science community should start

from the principle that we can both

protect individuals while promoting wider

social democratic principles to ensure

scrutiny of policy, and to understand who

benefits, and who loses, by particular

social changes.

So far I’ve mainly spoken about the need

to make a strong case for the public

benefit of social science research. REF

impact studies are one thing, but

impressive as they are, we need to ensure

that we meet external challenges that will


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change what we can do over the next

twenty years.

But this leads us to the question – who

pays? I think the ‘eco-system’ of funding

social science research also presents

challenges for the next few years.

Some of this is of course due to austerity

and its effects on government spending.

But before I turn to the spending review, I

want to start with a graph from HEFCE’s

Report from Main Panel C (which includes

most though not all social science

disciplines carrying out research in higher

education institutions). This appeared on

page 24 and captured remarkably little

attention on publication last January.

Now I note the limitations of this data. It

captures only the research spend of Main

Panel C subjects for research carried out

in universities, but to my mind one of the

striking things about it is the direct spend

by UK government (the green line). That

shows that a clear reduction in spend

from 2004/5 and then more markedly

after 2010. I know the figures don’t

account for government spend on non-

university social science, including

management consultancy. But those of

us funding social science research in other

settings have been aware of the marked

decline in government funded social

research, much of it programme

evaluation. It is not my purpose to defend

all the previous spend, nor indeed to say

that all evaluations should be done by

universities. But evidence suggests that, as

austerity bit, external research budgets

were cut disproportionately partly

because savings were achievable relatively

quickly. I bring this up for three reasons.

First, the loss of too many high-quality

evaluations has wider effects on skills. I

don’t just mean the effect on independent

research institutes who often carry out

such research, and some of whom have

found the last few years very difficult. But

the loss of skills generally, both in

university-based social science and

elsewhere, makes worse our problems

about data collection expertise and

research design.

Second, I would argue it causes a lack of

democratic scrutiny over the effects of

government policies and programmes, and

results in even less piloting or

experimentation with any independent

objective review. Particularly in the

context of our heavily-centralised

government this is a real worry. I know

there is a view that greater devolution

should lead to more natural experiments.

In principle that may be so but if a

devolved power has only one-tenth or

twentieth or fiftieth the budget but covers

the same wide range of policy areas as the

bigger unit that is cutting its budgets,

we’re actually going to see less

experimenting if you mean any collection

of systematic data about it. I know that it

is even more of a problem for policies or

issues devolved to local authority areas,

which include important things like social

care for older people and child

protection. It has been good to see, in

London, the London Datastore tackle

some of these issues, because 33 London

authorities can’t individually address it.

But the scale of challenge shouldn’t be


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underestimated. In some areas, we have

been very dependent on independent

funding simply to document who

benefitted and who was disadvantaged by

particular government interventions.

Surely we should expect more objective

scrutiny of these issues – not only as

social scientists but as citizens.

Third, given the relative sizes of budgets,

it also affects the total spend on social

science (with the repeated caveat that this

is for university-conducted social science

research). By my rough calculations, the

total income of about £290m provided by

research councils and UK government

(who provide the lion’s share of funding)

reached its high point in 2008/09, when

the reductions in central government

spending was more than matched by

increased research council spending. By

2012/13 (the latest year described), the

total was £214m (all in adjusted 2012/13

pounds). This is about 85% of the average

total over the period, and 75% of the

income from the high point of 2008/09 –

so we’ve seen cuts in university social

science of between 15-25% in real terms

over the period, with that falling

disproportionately on the sorts of

descriptive work government

departments tend to fund. Given that the

research councils had a nominal cash

freeze from 2010, and from what I know

of direct government spending on social

science research, I would guess that the

total spend may be even lower today.

Other disciplines face different funding

profiles as other sources of funding – by

the private sector and large research

charities in, for instance, biomedicine –

are larger. As HEFCE notes in the report

the effect of the reduction of direct

government spend is much more marked

for the social sciences than for any other

group of disciplines.

Now my purpose is not to complain

about the economic situation that led to

reductions in government spending. But it

does mean we’re going to have to think

very carefully about the Haldane

principles. I have used the plural

deliberately; as the government’s Science

and Innovation Strategy, published late last

year but partly now over-taken by the

Nurse review, there were originally six.

Nowadays we are more likely to

remember only one and refer to it in the

singular. This is the one that states clearly

that how research should be done and

who should carry it out should be left to

the decisions of experts; this underpins

our use of peer review of various sorts by

research councils.

But while it is clearly appropriate for

government to set topics and challenges

for research (as Haldane recognised it

would it be democratically wrong if they

did not have a say) it is also one of the

Haldane principles that ‘each government

department should provide funds to

answer specific policy questions’ and that

this should be distinguished from general

research spending. So the reduction in

government departmental spend raises

questions about whether this

departmental policy work will simply not

get funded or whether others – charities

with an interest in the issues, or research

councils facing demands from researchers

who want to evaluate policy areas, say –

will step into the breach. When I was at

the Nuffield Foundation we had

occasionally to grapple with these issues

and while sometimes it could be a benefit

to the quality or open-ness of the

research if we funded it, sometimes it did

rather feel as if we were stepping into the

breach faute de mieux. This is an external

challenge that needs watching.


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And in the context of the Nurse review,

this will be doubly so. It will be important

for Research UK to take views about

national interest and be responsive to

government views – after all governments

have been elected and public funding

requires legitimacy. On the other hand, it

cannot simply to step in and fill gaps in

what government itself ought properly to

do. This will require open discussion

about what is a national statistic, what is a

departmental matter and how

government itself (and Parliamentary

Select Committees) ensures objective

evidence about and scrutiny of its own

policies. These issues simply cut differently

for the social sciences than they do for

the natural and physical sciences, because

one of our objects of domain are things

that are relevant to public policy and we

need to be open in discussing this

If this has sounded at all carping, I don’t

mean it too. I know how much the social

science spend was protected in 2010,

even though the flat cash settlement

meant a real cut; it could have been so, so

much worse. And the announcements in

the recent Comprehensive Spending

Review that the science spend in total will

be protected in real terms is greatly to be

welcomed. As is the under-appreciated

fact that we have relatively stable long-

term time horizons for planning our

science spend, which is not the case in

many other countries.) The spending

review does not recover the research

council real-term cuts since 2010 but it

does mean the total spend won’t decline

further.

But as James Wilsdon of the Campaign for

Social Science, Stephen Curry of Imperial

and David Price, Graeme Reid and

Andrew Clark have recently written,

many of the implications are still unclear

due to the Nurse review. I won’t dwell on

this, not least because there is still much

uncertainty. In principle the social sciences

should be confident about their ability to

contribute to and benefit from cross-

disciplinary research and work on global

challenge issues, but we all need to play an

active and constructive role in the public

policy discussions about these. That will

mean working with the Campaign, the

Academy of Social Sciences, the British

Academy and the ESRC to really put

forward the best possible cases for social

science research.

I will, however, end by highlighting a few

aspects of the spending announcements,

the Nurse review and other proposed

‘architectural’ changes to the teaching and

research infrastructure that have not, I

think, been much discussed, where the

internal challenges meet the external

challenges facing UK social science.

First, the preservation of the capital

infrastructure fund is something that the

social sciences, inside and outside

universities, should actively welcome.

Many of the new data challenges facing us

require this sort of infrastructure funding.

I am, I’m sure, among many who were

pleased that a new birth cohort study was

funded in 2010, and who noted with

sadness its cancellation earlier this year. I

don’t pretend to know all the reasons.

But I do know that the challenges I’ve

already discussed – about the divide

between those with real data collection

expertise and those with data analysis

skills, in the context of the existing data

protection environment – can’t have been

helpful. I know that both scientifically and

in terms of wider public policy, we badly

need a new birth cohort. No amount of

creative use of ‘big data’ or administrative

data – which is ‘thin’ data compared to

the richness of the birth cohorts – can

compensate for the absence of a birth


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cohort. It is now 15 years since the last

new birth cohort, and I’m old enough to

know all too well the losses to social

science – substantively and

methodologically – and to public policy

arising from the previous 30 year gap

between the 1970 cohort and the

Millennium cohort. Family structures and

the wider social structure had changed

out of all recognition between those two

studies. I hope that UK social science will

consider new ways of bridging the divide

between the challenges for data collection

and support those who may want to take

this forward, because I do think it’s an

essential tool kit for understanding our

society.

Second, I continue to worry about the

need for concerted strategic steps to

improve quantitative skills. HEFCE as was

took a strong interest in this strategic

area and somebody will continue to need

to do so. I note that the proposed

introduction of a Teaching Excellence

Framework (with a further consultation

next year) and a revised role to safeguard

student interests may have particular

implications for the social sciences in this

regard. Of course, I welcome a stronger

incentive for excellence in teaching – not

only did I benefit from an undergraduate

education in a ‘liberal arts’ setting that

prioritised undergraduate teaching, I also

agree with Craig Calhoun that we

underestimate the importance of teaching

as our biggest – widest and longest-term-

path to impact. Divorcing research

excellence from teaching excellence

doesn’t make for the long-term health of a

discipline. But I remember well a report

the ESRC board responsible for post-

graduate education received when I was

member some years ago, in which

research carried out while they were still

postgraduates showed that students were

least happy (or satisfied) with the amount

of time they were called on to spend in

quantitative methods training (which was

tiny). When the students were re-

interviewed a couple of years later, their

views had virtually reversed and a large

number regretted that they had not done

more work in this area. While I know

teaching of quantitative skills can be

inspiring, and many of the new Q-Step

posts will ensure that this is so, I also

know it can seem hard especially if

students enter without much background.

So I suspect the TEF and the metrics

about student satisfaction are going to

need to be looked at very carefully if

we’re not going to be go backwards in

quantitative training expectations among

undergraduate social scientists.

I also note the uncertainty over the form

of any future Research Excellence

assessment. I have often expressed

worries over the transaction and

opportunity costs of the REF as was, and

would hope that there might be some

streamlining. (As a former empirical

researcher, dare I suggest that sampling

might be helpful?). But I worry about the

effects of moving to what seems to be a

simpler, lighter touch metrics-based only

system if it’s looking at publications only.

That isn’t only because I think metrics

work differentially in different disciplines.

From the point of view of one who cares

deeply about the health of UK social

science and its role in policy formation, I

worry that a move to a metric system

based on journal articles will return to the

system in which only journal articles were

incentivised. The hard graft of doing work

that has impact on policy, on

implementation, on data collection and on

evaluation seem to me likely to be dis-

incentivised by any system based on

publication metrics alone. That is not to

say that all research should aim for

impact, but the 2014 REF seemed to me


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to take a sensitive approach to this issue,

with robust case study evidence for a

modest proportion of the work. That

seems to me a public good and I would

argue is good for social science as well.

Without some incentive for impact as part

of research assessment – so that it could

address Witherspoon’s dictum, that the

worst outcome would be for low quality

social science research to have a big

impact -- I worry that the shortfalls in

quantitative social science and empirical

research might get worse. That would I

think lead to a long-term weakening in the

role and status of social science, and

fewer fruitful encounters of theory and

methods with the grit of empirical

evidence. That’s an empirical proposition

of course and testable in principle. I do

think we should be watching the social

science effects of the REF.

For the last minutes, I have dwelt on

government spending and policies and

their possible implications for social

science. I don’t apologise for doing so,

even though in many areas the uncertainty

is so great that I can’t say much more than

‘watch this space’ and please take part in

the public discussions of these issues. I

hope I’ve also reminded us that we’ve got

a responsibility as a community. But I

want to end with a wider comment about

the total amount of funding available for

UK social science of all kinds, whether

basic research, applied research or

translational work. Having spent the best

part of twenty years in a funder of social

and educational research, I am left with

the reflection that there are too few

funders of this kind of research. That isn’t

only a comment about the value of and

need for more spending on social science,

in universities, government, research

institutes and think-tanks.

But I’m more and more mindful of the

value of pluralism in funding. There are

few private sector sources of funding that

get translated into public benefit social

science research. Direct government

funding and research council funding need

to be preserved and over time, I hope,

will grow. But there are few alternative

sources. I’ve already alluded to the

problems of scale posed by devolution

and the extreme financial pressures faced

by local authorities who could in theory

be responsible for funding not only

descriptive studies but a greater

willingness to experiment in social policy

and to examine those experiments

rigorously.

But there is also a shortfall in the number

of charities who support social science

research. The Leverhulme Trust does so

(but not on grounds of social utility), the

Joseph Rowntree and Nuffield

Foundations do so (within their particular

areas of interest), and so too do the Big

Lottery Fund, Esmée Fairbairn, Paul

Hamlyn and other trusts and foundations

from time to time. But far too often,

particularly for those doing social science

outside universities, there are too few

sources of funding. (And that’s before we

consider what BREXIT might mean….)

That is not just a statement about the

total amount of funding available, but also

about the benefit of having pluralism in

funding sources, and competition between

funders to drive up the quality of

research. It means there are fewer

sources of funding for infrastructure or

strategic initiatives.

So while I welcome the many wonderful

initiatives being taken, I think the sign of a

social science community that was

delivering on all its potential would be

that new funders would be called into

being at the sight of all the ways that


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robust social science can give rise to

public benefit. We should have the

audacity but also give it the elbow power

to make that our aim.

SFW

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