The three-bucket problem

Ten tests for the UK’s new R&D funding framework

The government has started to talk seriously about putting public R&D funding into three “buckets”:

1. “basic curiosity-driven, investigator-led research”;

2. “applied research which should be aligned to Government ambitions”; and

3. “helping the transition from start-up to scale-up” and “support[ing] our big R&D-intensive companies”.

Starting life as comments made by science minister Lord Vallance, this framing recently made its way into the Post-16 Education and Skills White Paper. While this framing may initially sound like a useful shorthand for capturing the breadth of our R&D system, the formalisation in the White Paper shows it is much more than that; it’s part of a wider effort to connect research, skills, industrial strategy and economic renewal.

That gives the buckets extra weight: positioning them as an organising device for how ministers intend to steer the entire research-innovation-skills chain. The three buckets could even frame how UKRI allocates its budget, how departments think about their R&D portfolios, how universities and other research organisations position themselves, and how companies interact with the state.

The three buckets are also an explicit intervention in the long-running Haldane Principle conversation: the boundary between ministerial direction and academic autonomy.

There are reasons to welcome clarity. An explicit ‘discovery’ bucket could stop the recurrent tendency of governments to meddle in areas where light touch is both appropriate and politically defensible. A government-aligned bucket creates space for more coherent strategic action. A business-led bucket could signal that innovation policy matters at least as much as research policy.

But there is an obvious risk. This could become nothing more than Frascati-with-branding: a relabelled version of the basic/applied/experimental development split that the OECD has used for half a century. Critically for our discussions, Frascati is descriptive, not normative: it tells you what you have, not how it should be governed. If the UK simply maps existing programmes into three headings, the result will not resolve any of the real tensions: who sets priorities, how you govern complex institutes like LMB or Turing, how you protect discovery-led research at Spending Reviews, or what “business-led” even means when most relevant levers sit outside DSIT.

There is also the danger of creating a framework that simply gives future Chancellors a more legible way to shift money out of discovery and into short-term priorities. The question is how to secure the benefits of this approach safely.

To do this, ‘bucket theory’ needs to work as a governance framework: distinct modes of agenda-setting, accountability and instrument design. That is, admittedly, a high bar; most government restructurings fail this test. So to help us, we need to ask a sharper question: what conditions must be met for ‘bucket theory’ to be meaningful? What would have to be true for buckets to improve the functioning of the UK’s R&D system, rather than add another layer of classifications and acronyms? And what capabilities and constraints distinguish one bucket from another in practice?

If buckets are to become a meaningful settlement, they must pass some hard tests about governance, institutions, incentives and political economy.

In the remainder of this piece, I set out the tests I think matter most. They are not exhaustive, but in my view they are necessary. If the three-bucket framework cannot meet them, it risks becoming an elegantly structured way to misdiagnose, and potentially worsen, the UK’s long-standing challenges in research and innovation.

Test 1: Does bucket theory solve anything ministers actually care about?

Before you can judge the usefulness of the three buckets, you need to know what problem they are meant to solve. In my interactions, I perceive at least four different motivations:

1. Government cannot direct research towards national priorities with enough grip.

2. Business investment in R&D is low and must driven up significantly.

3. The system is too messy: nobody can describe what sits where or why.

4. Government knows it is funding lots of blue-skies research, but given the state of the economy, it has no idea whether it’s funding the right amount.

Each of these is a legitimate problem. But each implies a different remedy. If the concern is that missions need more coherence, the question might be not be about buckets at all – it is about how to get as quickly as possible from hypothecating the funding to running effective departmental R&D governance. If the concern is weak business R&D, the answer probably lies in improving tax policy, procurement, standards and regulation, none of which fall neatly into Bucket 3 unless you radically enlarge the definition of “public R&D”. If the real concern is that our university research system is too large or insufficiently steered, then bucket theory is all about giving ministers a neat mechanism for shifting money from Bucket 1 into Buckets 2 and 3 (and no need to pretend otherwise).

A bucket framework that does not clearly state the problem it is designed to address will quickly become everyone’s favourite justification tool: every spending review, every ministerial push, every institutional turf battle will try to claim the buckets support their preferred narrative.

A serious bucket settlement must therefore begin by answering one simple question: what specific system failures or political dilemmas is this intended to fix? Unless that is stated upfront, no other part of the framework can carry weight.

Test 2: Do the buckets correspond to genuinely different modes of governance?

The second test follows immediately from the first. If bucket theory is meant to change how decisions are made, each bucket must embody a distinct mode of governance. That means each must have:

• a different logic for agenda-setting (who decides the “what” and “why”);

• a different accountability structure (to whom, through which forums, and with what consequences);

• a different tolerance for risk and failure;

• a different suite of instruments and operating rhythms or tempi.

Without these differences, the buckets are nothing but “purposes”: Bucket 1 “exists to expand the frontiers of knowledge”, Bucket 2 “exists to advance national missions”, or Bucket 3 “exists to support business innovation”, or whatever the wording is. But those are statements of intent, not operating models. The real distinction lies in how power flows:

• In Bucket 1, is government genuinely hands-off on content, intervening only in the architecture of the system (portfolio balance, infrastructure decisions, public appointments)?

• In Bucket 2, can ministers articulate outcome-based missions and hold programme directors to account without drifting into micromanagement or political signalling?

• In Bucket 3, is the state clear about which market failures justify its participation – and which instruments align with those failures?

A useful thought experiment here is the Alan Turing Institute, which has recently been the subject of very Bucket 2-style intervention. But the Turing is an independent institute, funded by UKRI – whose website asserts their decision-making independence from government (putting Turing in Bucket 1). So into which bucket does Turing fall? Its activities arguably straddle all three buckets. If the only reliable way to classify it is “where ministers want more control vs. where they fear political blowback”, then bucket theory has failed the mode test. Our buckets become a map of revealed political preference, not a structure that disciplines it.

Or perhaps we should look at the REF. The White Paper implies that institutions will be rewarded for bucket-aligned behaviour – demonstrating clarity of purpose, alignment with government priorities, or measurable impact (one might read this as a sector-friendly version of the three buckets). This is indeed a mode shift of sorts! But it is one that leaves open major questions on how this will work to differentiate university activity (and consequent funding) across the buckets. No small challenge.

The severity of this second test is intentional. If buckets do not lead to visibly different behaviours – in programme design, accountability, tempo, risk appetite, and system oversight – then the reform is cosmetic. If they do, then bucket theory becomes a way of hard-wiring the differences that most people in the system already recognise, and we might be able to right-size our efforts accordingly.

Test 3: Can the framework cope with research moving between buckets over time?

A further conceptual challenge arises when we try to apply the three buckets to real research trajectories, when today’s discovery becomes tomorrow’s mission priority and next year’s commercial opportunity. Genomics, quantum technologies, AI, new materials, and mRNA platforms have all travelled this path. A static allocation framework built around project types may therefore be inherently unstable.

This matters because it forces a deeper question: what exactly is being ‘bucketed’? Are we classifying projects? Institutions? Funding streams? Capabilities? Patrick Vallance drifts between talking about buckets as priorities and broad categories of research activity; officials mainly think in budgets; and universities might wisely assume it must be about institutional or other politics. These are not compatible views.

If the buckets apply to projects, then most significant research programmes will, by construction, cross multiple buckets during their lifetime. If the buckets apply to institutions, then the framework implies a much more radical restructuring of the landscape than is currently being acknowledged: the Research Councils, PSREs, Catapults, ARIA, national research infrastructure, and major university institutes would need to be designated into specific modes and held to them. And if the buckets apply to budgets, then regular reclassification becomes unavoidable as fields mature, making long-term planning harder.

None of these problems is fatal, but they require explicit design choices. At a minimum, bucket theory needs a doctrine (and protocols) for how research should transition across modes, who adjudicates those transitions, and what happens to the funding and governance arrangements when it does. Without that, the buckets will either become rigid categories that distort the evolution of research, or porous categories into which anything can be moved for convenience – in which case they cease to have meaning at all.

The test here is simple: does bucket theory contain a credible account of how research moves between modes, and what institutional machinery supports that movement? If not, it risks operational incoherence from the start.

Test 4: Can the buckets be mapped onto existing institutions without breaking them?

Even if the conceptual model works, it must still survive contact with the machinery of UK research and innovation – and this is where difficulties could multiply. The country’s institutional landscape is not designed around cleanly separated purposes or modes. Almost every significant organisation straddles two or three of the proposed buckets.

ARIA is discovery-oriented but was explicitly created outside Haldane with unprecedented political risk-taking and, through its Activation Partners, is now engaging in firm formation and scale-up. Catapults are business-facing yet majority publicly funded, often operating pre-competitively, and pursuing goals that are part-technological, part-government mission. Research England’s functions sprawl across all three buckets: QR might be ‘core research’ in the Treasury R&D stack, but in reality props up significant amounts of government and industry funded research. REF’s increased use over the last few cycles as a powerful lever for policy change makes it look ever more mission-oriented. And in a post-HEFCE world, HEIF has inched ever closer to being exclusively a mechanism for business engagement and economic growth. Even the research councils have mixed portfolios that run across discovery grants, strategic programmes, translational pathways, industry partnerships, and major facilities.

To cut through this tangle, bucket theory must specify whether institutions are expected to align to buckets or span them. Both choices carry significant consequences. Alignment implies major structural redesign, where existing organisations are carved into bucket-specific units, or where new machinery is built on top of what we already have. Span implies matrix governance, with explicit rules for which decisions belong to which mode. Neither approach is straightforward, and both risk unintended incentives: institutions forced into a single bucket may lose capabilities; institutions allowed to span buckets may default back to the familiar governance patterns that bucket theory was meant to clarify.

A workable settlement therefore needs to answer at least three questions. First, how will bucket assignments interact with the governance of our existing funders and institutions? Second, where do cross-bucket entities such as large facilities, shared talent funding, PSREs and departmental R&D programmes sit? And third, what prevents institutions in politically attractive buckets from absorbing functions by default?

Unless bucket theory can be mapped onto the real institutions of the UK system without producing internal contradictions or perverse incentives, it will have no operational purchase. That is why institutional mapping is a crucial early test.

Test 5: Can discovery be protected without becoming either illegitimate or an easier target?

Bucket 1 is vulnerable. Missions have ministers. Business-led research has firms, investors and industry groups. Discovery has a diffuse constituency whose political salience is low and whose work is often presented as remote from everyday concerns. Without explicit guardrails, Bucket 1 becomes the easiest source of funds for anything urgent or electorally resonant. The fact we have a minister who ‘gets it’ on discovery research is a telling exception that proves the rule – and even Patrick can’t stop the research community from descending into blind panic at every fiscal event.

One answer might be to introduce a floor or band for discovery spending. But why should frontier research enjoy protected resources when other important public services do not? Can we show the compelling public-interest rationale without indulging in self-declared privilege? I wonder.

And here is the paradox. Creating a formal Bucket 1 does not necessarily protect discovery; but it may make raiding it politically easier. Once clarified and ring-fenced on paper, discovery spend becomes a discrete line item that can be targeted in future fiscal consolidations, particularly if a government faces incentives to shift resources into applied missions or industrial support. A well-defined bucket might prove easier to cut than a diffuse and conceptually interwoven system – and while ministers are clear that discovery research will be protected and, when the economy allows, grown, this is protection-by-assertion.

The science minister himself has illustrated the tension. In recent testimony, Vallance framed Bucket 1 as “knowledge creation and the cost of doing business,” urging that we “not have false promises around economic growth from that in the short term.” That’s fair enough, and loosely echoes a familiar sector talking point about not throwing the golden goose out with the bathwater. But it is also an attempt at protection through lowered expectations: if discovery isn’t held to growth metrics, it can’t be judged to have failed them. This framing cuts both ways, of course, as when budgets tighten, costs must be cut.

There is a related danger in treating Bucket 1 as “set and forget”: a space where government steps back, leaving the research community to steer priorities through a mix of peer review, QR allocation and institutional strategy. This ignores where important governance questions sit. The state already shapes the architecture of discovery: the mix of instruments, the balance between disciplines, the approval and siting of major infrastructure, the incentives for interdisciplinarity, and the metascientific rules that govern quality and reproducibility. These are not questions that can be delegated wholesale to an undifferentiated “academic community” – researchers hold divergent interests, and many of these decisions involve public interest considerations that aren’t synonymous with institutional preference.

The most obvious of these is disciplinary balance. How much of the national research effort should sit in STEM versus AHSS? How much should flow into fields with large spillovers versus fields with high public-value content but fewer market-facing impacts? For ministers responsible for stewarding national research capability, these choices cannot be elided. But our system rarely confronts these questions explicitly, because our sector operates on a shared belief that all disciplines are created equal. Bucket theory does not resolve this problem; if anything, it might obscure it further.

A performatively insulated Bucket 1 may also invite attack rather than deflect it. If discovery is placed behind an institutional curtain and presented as exempt from scrutiny, it becomes an obvious target for future populist governments intent on demonstrating value for money or punishing perceived ideological bias. Trump’s “Restoring Gold Standard Science“ Executive Order is instructive: reproducibility, replication and bias are no longer internal metascience debates but matters of national political attention. A discovery bucket with opaque governance and weak public explanation of quality assurance will be left very vulnerable here.

Thus the real test is dual: can Bucket 1 be protected in ways that are politically sustainable and publicly defensible, while also being governed explicitly enough to address both disciplinary balance and quality – all without collapsing into either politicisation or abdication? Protection cannot be achieved by structural boundaries alone. It requires a publicly defensible account of why discovery matters, how it is governed, and how its quality is assured. Without a visible metascience agenda – covering reproducibility, transparency, risk appetite and evaluation – the bucket will lack the legitimacy needed to withstand fiscal pressure or ideological policing. Any protection that rests on insulation rather than legitimacy will fail at the first encounter with a hostile Chancellor or a populist critique.

Test 6: Can the boundary between Buckets 1 and 2 be drawn in a way that resists political opportunism?

The hardest line to draw in the entire framework is the one between discovery-led research (Bucket 1) and mission/priorities-led research (Bucket 2). The two are not cleanly separated in the real world. Much discovery occurs in institutions that have implicit strategic intent; much mission work depends on fundamental capabilities; and many organisations span the boundary as a matter of good design.

This makes the boundary acutely vulnerable to political opportunism. If the criteria for classifying research as “mission-led” are vague, then almost any activity can be placed into Bucket 2 when ministers want more grip, and almost any activity can be placed into Bucket 1 when ministers want to avoid ownership or accountability. Without hard-edged criteria, bucket assignment becomes a proxy for revealed preference: which programmes ministers want to direct, which they want to shield, and which they want to disown.

That is precisely the pathology a governing framework is meant to prevent.

A workable settlement therefore needs objective tests for Bucket 2 status – tests that apply equally whether the activity is fashionable or embarrassing, electorally attractive or politically toxic. At minimum:

• a clearly articulated, outcome-based mission;

• a time-bounded charter;

• a named political owner; and

• a theory of change linking research to mission outcomes.

If a programme cannot meet these tests, it should not be designated as mission-led. If it can, it should not be allowed to retreat into Bucket 1 when results are disappointing. The same logic applies to institutions: if an organisation claims it is “mission-oriented”, it should be accountable for mission progress; if it claims it is discovery-oriented, it should be insulated from mission-driven interference.

The test here is whether bucket theory can stabilise the 1/2 boundary, preventing both disguised control and disguised abdication. Without that, the framework will merely provide a more elegant vocabulary for the politics it claims to rationalise.

Test 7: Is this a whole-of-government R&D strategy or merely a UKRI reorganisation?

An ambiguity runs through bucket theory: its scope. Is this a framework for allocating the DSIT R&D budget that sits under Lord Vallance, or is it a design for the UK’s entire public R&D system? The distinction matters enormously, because the two approaches imply radically different institutional machinery and very different claims about what the framework can achieve.

The immediate context is the government’s Industrial Strategy, which, due to its centrality in Whitehall discussion, must be both the conceptual jumping-off point and the organising principle for R&D investment. Growth is explicitly Labour’s primary mission – Bucket 2 by definition. Yet the Industrial Strategy is led by DBT, structured around eight sectors, and fundamentally business-facing – which sounds like Bucket 3. The government’s own Digital and Technologies Sector Plan discusses AI, engineering biology, and quantum: technologies that span discovery research, government missions, and commercial application simultaneously. The government might reasonably argue that Industrial Strategy is big enough platform to give the overall directional logic for all three buckets. But that only sharpens the question: if bucket theory is meant to operationalise Industrial Strategy priorities, can it do so from within DSIT and UKRI alone?

The answer is obviously no. The research councils and Research England account for well under half of the government’s total civil R&D spend (excluding fiscal measures like R&D tax credits). The rest flows through departmental budgets, public sector research establishments, and various arms-length bodies. Defence and health research mainly flow through separate bodies. If Bucket 2 is the home for mission-led research but excludes most departmental R&D, it cannot fulfill its stated purpose.

The same applies to Bucket 3. Innovation policy is not primarily about Innovate UK grants or Catapult infrastructure. The largest levers shaping business R&D are tax credits, procurement rules, standards, IP regimes, competition policy, and access to finance. Most sit with HMT, DBT, or regulators. If Bucket 3 is defined narrowly as “DSIT’s business R&D programmes”, it is a minor component presented as the main story.

So, if bucket theory is intended as a whole-of-government framework, then it must be designed accordingly. That means specifying how departmental R&D budgets, PSREs, tax instruments, procurement, and regulatory policy map onto the buckets. And it means creating effective cross-departmental governance and coordination mechanisms for Bucket 2 missions, including explicit machinery for aligning DSIT, DBT and HMT around industrial strategy priorities. At the risk of stating the obvious, this is very difficult to do.

The test is therefore simple but consequential: if bucket theory drives the whole-of-government R&D settlement, does the institutional design measure up? If the framework is meant to operationalise industrial strategy but is built only on DSIT and UKRI machinery, it will fail. The buckets cannot carry more weight than the institutions that underpin them.

Test 8: Can a three-bucket framework handle cross-bucket dependencies without collapsing under its own contradictions?

Even if the buckets are conceptually clear and institutionally mapped, the real system is knitted together in ways that resist neat separation. Much of the UK’s research capability is sustained by shared platforms: large facilities, expensive instrumentation, data infrastructures, compute resources, doctoral training pipelines, technical professions, place-based clusters. These are neither purely discovery nor purely mission nor purely commercial: they are enablers that sit underneath all three.

Trying to allocate these platforms to specific buckets creates immediate distortions. Does Diamond Light Source become a “mission-led” asset because so much of its science supports national priorities? Does exascale compute belong in Bucket 1 because frontier researchers need it? Are Catapult facilities “business-led” even when they serve as translational infrastructure for publicly funded missions? And how do we classify doctoral training programmes whose graduates feed universities, PSREs, government labs and industry simultaneously?

If bucket theory forces all shared infrastructure into one category, it will misrepresent the system. If it spreads infrastructural responsibility across buckets, it risks fragmentation, inconsistent investment cycles and duplicated oversight. And if it attempts a proportional allocation (X% discovery, Y% mission, Z% business), we are back to accounting cosmeticism rather than governance design.

The stable solution must be to acknowledge explicitly that cross-bucket platforms require their own logic, governance and investment model, sitting alongside the buckets rather than inside them. Without such a platform layer, the buckets cannot function operationally. With it, they begin to look less like a whole-system architecture and more like discrete modes nested within a broader infrastructure regime.

Thus the test is: can bucket theory accommodate the horizontal dependencies – infrastructure, talent, data, compute, or regulation – that make the vertical buckets possible? If not, the framework breaks the system into conceptual parts it cannot operate.

Test 9: Can Bucket 3 be made coherent without redefining “business-led innovation” beyond recognition?

Bucket 3 is, on paper, the simplest of the three: research led by firms, focused on commercialisation, scaling, productivity and growth. In practice, it might be the most internally conflicted. Truly business-led research is already occurring in the private sector – and not only does this spending not appear in public R&D budgets, it actually dwarfs it. What instead appears in public accounts is the relatively small amount of research that government co-funds because of specific market or system failures: spillovers, coordination failures, finance gaps, or public-good characteristics.

In this context, a credible Bucket 3 therefore requires the government to articulate:

1. which failures justify public involvement;

2. which instruments address each failure (grants, loans, equity, guarantees, procurement, standards, data regimes); and

3. how those instruments interact with the tax system, which remains the largest single lever shaping business R&D.

Without such clarity, “innovation” risks becoming a rhetorical wrapper for an eclectic mix of policy interventions – some pre-competitive, some mission-driven, some industrial-policy-driven, and some regionally motivated – whose only common feature might be that they are not “discovery”. That is neither analytically coherent nor operationally stable.

There is a further accountability issue. If Bucket 3 is truly market-driven, who is accountable for outcomes? Ministers cannot credibly claim credit for things built by the private sector (though they will give it a go!). But nor can they disclaim responsibility when public money is involved. Innovate UK sits uneasily in this space: they must answer to ministers for strategy while claiming to serve business demand.

The test here is whether the government can produce a credible theory of business R&D, grounded in identified failures and matched instruments, that explains why these activities belong in the public R&D line at all. If it cannot, Bucket 3 will remain an unstable hybrid: part industrial strategy, part economic development, part fiscal instrument, part corporate subsidy. And, over the years, this unstable settlement has repeatedly shown itself to be vulnerable to attacks from within and without.

Test 10: Does bucket theory change how decisions are actually taken?

The final test is the most important. After all the conceptual work, institutional mapping and political economy analysis, bucket theory must alter behaviour – otherwise it is just a set of headings. The UK R&D system has seen multiple reforms over the past two decades, many of which have not had the expected results because they merely rearranged reporting lines while leaving decision-making cultures untouched.

The risk is clear: the buckets will become a new way for finance teams to classify spend, a new annex in the DSIT annual report, or a new slide in UKRI staff presentations – while councils, departments, institutes and firms continue to operate exactly as before. Missions are still run through ad hoc committees; discovery is still shaped by opaque system-level decisions; business support is still fragmented across Innovate UK, DBT, HMT, and procurement rules with little integration.

For bucket theory to matter, it must create operational consequences. Programme design templates would need to differ between modes. Accountability mechanisms would need to change. Risk appetite statements would need to be explicit and enforced. Departments would need to adapt their R&D governance. UKRI structures would need to reflect the distinction between modes rather than the accident of disciplinary history. Evaluation would need to be bucket-specific rather than one-size-fits-all.

This is not a minor undertaking– a system redesign on a scale greater than anything attempted in recent memory. Which is precisely why this test is necessary: bucket theory must demonstrate that it is capable of changing decisions, not just relabelling budgets. If nothing about programme governance, institutional behaviour or accountability practices changes, then bucket theory fails – even if the taxonomy looks coherent on paper.

Conclusion: what would it take for bucket theory to succeed?

The three-bucket proposal is not trivial. If handled intelligently, it could clarify the roles of discovery, mission-led research and business-led innovation in a way the UK system has struggled to articulate for decades. It could give ministers a clearer mandate in areas where political direction is appropriate, protect discovery from episodic interference, and bring some discipline to the sprawling domain of business support. It could even become the spine of a more coherent national research and innovation strategy.

My tests set a high bar – deliberately so. Government is dealing with a messy inherited system, imperfect information, and real political constraints. No framework will resolve every tension or eliminate every trade-off. But bucket theory is not being proposed as an incremental adjustment or a tactical relabeling. It appears in the White Paper as a potential organising principle for a £20 billion system. If it is to function as so claimed, then it must meet standards appropriate to that ambition.

The purpose of my tests is not to try to argue the framework out of existence, but rather to insist that it be taken extremely seriously. For government, that means:

• identifying clearly the problems that the framework intends to solve;

• treating the buckets as distinct modes of governance, not categories of research;

• managing the inevitable transitions and boundary cases;

• mapping the framework coherently onto real institutions;

• giving discovery research legitimate and stable governance while protecting it from attack;

• stabilising the boundary between discovery and missions to prevent political opportunism;

• embracing this as a whole-of-government affair, not merely DSIT arcana;

• acknowledging the cross-cutting infrastructure on which all three modes depend;

• producing a credible theory of business R&D grounded in identified market failures;

• changing real decision-making, not just spending classifications.

If the government can meet these conditions, then bucket theory could form the basis of a more stable and intelligible R&D system – one in which autonomy, missions and commercial innovation have clearer mandates and less destructive ambiguity. If it cannot, the risks are obvious: another round of structural reform that promises clarity but delivers only reclassification, leaves the core institutional dilemmas untouched, and exposes the system to future interference.

In that sense, the three-bucket proposal is a revealing moment. It forces us to confront, openly, questions that have long been managed implicitly: who sets priorities, who governs discovery, who owns missions, who speaks for business-led R&D, and what the state is ultimately trying to achieve with its R&D investment. The framework will stand or fall on whether it answers those questions directly.