Exploring the complex relationship between scientific evidence and policy-making
Imagine a team of scientists spending years meticulously researching a critical policy issue—say, the most effective ways to reduce childhood poverty or combat climate change. They publish their findings in a prestigious journal, confident their evidence will guide decision-makers. Yet when policies are announced, they bear little resemblance to the researchers' recommendations. Instead, political considerations, outdated assumptions, and ideological preferences have shaped the outcome, while the scientific evidence sits gathering dust on a shelf.
This frustrating scenario plays out regularly in governments worldwide. The complex relationship between evidence and policy has become increasingly scrutinized, especially during crises like the COVID-19 pandemic when the stakes for getting policy right have never been higher.
Evidence-based policy advice aims to ground government decisions in rigorous research rather than political whims or unsupported assumptions. But multiple landmines litter the path from research to implementation, creating what scholars call the "evidence-policy gap." 1
This article explores why translating evidence into effective policy remains so challenging—from the different worlds researchers and policymakers inhabit to the outright manipulation of science for political or economic gain. Understanding these challenges is the first step toward overcoming them, potentially leading to more effective policies that improve lives, save resources, and address society's most pressing problems.
At first glance, the solution to ineffective policies seems straightforward: simply give policymakers better evidence. But the reality is far more complex. The evidence-policy gap refers to the frustrating disconnect between scientific research and political decision-making. Studies have identified multiple barriers contributing to this divide: 2
Scientists and policymakers often speak different languages. Researchers typically publish their findings in technical academic journals using specialized jargon, while policymakers need concise, accessible summaries that focus on practical implications rather than methodological details.
The fundamental rhythms of research and policy creation are often misaligned. Scientific inquiry values thoroughness, replication, and peer review—processes that can take years. In contrast, the political world operates on electoral cycles and rapid response to emerging events.
| Dimension | Research Community | Policy Community |
|---|---|---|
| Primary motivation | Knowledge generation | Problem-solving and political gain |
| Time orientation | Long-term | Short-term |
| Success metrics | Publications, citations | Votes, public support |
| Communication style | Technical, nuanced | Simple, actionable |
| Evidence standards | Rigorous methodology | Practical feasibility |
This communication gap is compounded by timing issues—policymakers often need information quickly to respond to emerging crises, while rigorous research typically moves at a slower pace. 3 Additionally, their primary concerns differ: researchers generally seek truth and knowledge, while politicians must balance evidence with electability, public opinion, and values-based considerations.
History might seem like a natural guide for policymakers—after all, shouldn't we learn from past successes and failures? But using history as a policy tool is fraught with challenges. As one historian warns, "History has no lessons for you," meaning that simple, direct lessons from history are often misleading or dangerous. 4
Policymakers frequently draw historical analogies to make sense of current situations. After the 9/11 attacks, comparisons to Pearl Harbor were rampant. During the 2008 financial crisis, references to the Great Depression abounded. While these analogies can be rhetorically powerful, they often obscure more than they reveal. 4
The problem lies in context and contingency—the specific circumstances that make each historical moment unique. For example, when U.S. strategists attempted to apply "lessons" from the Iraq surge to Afghanistan, they overlooked critical differences between these contexts.
Policymakers often cherry-pick historical examples that support their predetermined conclusions. During the Cold War, proponents of counterinsurgency strategies highlighted successful campaigns in Malaya and the Philippines while downplaying their imperialistic contexts and the many differences between those conflicts and contemporary challenges. 4
Similarly, history often offers contradictory lessons. From World War II, one might draw the lesson that aggressors must be confronted early (the "Munich analogy"), while from Vietnam, one might conclude that foreign interventions are best avoided.
| Historical Event | Common Policy "Lesson" | Limitations of This Lesson |
|---|---|---|
| Great Depression | Governments must respond forcefully to economic crises | Current crises may have different causes and require different solutions |
| 2008 Financial Crisis | Bailouts and stimulus packages prevent economic collapse | Such measures may create moral hazard or exacerbate inequality |
| 1938 Munich Agreement | Appeasement encourages aggression | Not all compromises constitute appeasement; diplomacy has its place |
| COVID-19 Pandemic | Early lockdowns save lives | Lockdowns have significant economic and social costs that must be balanced |
Even when high-quality evidence is available and communicated effectively, it must navigate the complex world of politics where values, interests, and beliefs often hold more sway than facts. Policy theory suggests that evidence constitutes just one aspect of policy-making alongside interests, ideas, values, and beliefs. 5
According to the advocacy coalition framework, political actors operate within belief systems that encompass deep-core values, policy preferences, and instrumental decisions. Scientific evidence primarily influences the instrumental level but rarely alters deep-core values.
This explains why presenting contradictory evidence often fails to change minds—it may threaten deeply held identities and worldviews.
John Kingdon's multiple streams framework suggests that policy changes occur when three streams converge: a well-defined problem, a feasible policy solution, and favorable political conditions.
Evidence can help define problems and shape solutions, but without political will—what Kingdom calls the "politics stream"—policy change is unlikely. 5
This explains why even rock-solid evidence sometimes fails to influence policy. During the COVID-19 pandemic, initial consensus on the primary goal of saving lives gave way to value conflicts as considerations like economic impacts, educational needs, and personal freedoms entered the debate. Scientific evidence could inform each of these considerations but couldn't resolve the fundamental value trade-offs between them. 5
Perhaps the most disturbing challenge to evidence-based policy comes from deliberate efforts to undermine science that threatens powerful interests. These attacks have become increasingly sophisticated, putting "evidence-based policymaking at risk." 6
Vested interests—often corporations with financial stakes in policy outcomes—have developed numerous tactics to manipulate the scientific record. These include: 6
Industry-sponsored studies are significantly more likely to reach conclusions favorable to their sponsors. For example, a review found that 60% of studies by non-industry researchers found certain chemicals hazardous, compared to only 14% of industry-sponsored studies.
Researchers may be pressured to delay publishing unfavorable results, with one survey finding 20% of scientists reporting delays of more than six months to allow for patent applications or to slow dissemination of undesired results.
Researchers whose findings threaten powerful interests may face lawsuits, freedom of information requests, and personal attacks. One researcher was sued by a pharmaceutical company for publishing negative conclusions about its product.
Vested interests often hide their involvement by creating front groups that masquerade as grassroots organizations. Examples include: 6
Opposed ergonomics regulations while representing industry interests
Opposed gun control while presenting itself as a physician group
Actually a marketing campaign for a pharmaceutical product
These tactics make it difficult for policymakers and the public to distinguish genuine scientific consensus from industry-backed propaganda, undermining the entire evidence-based policy enterprise.
Amid these challenges, there are success stories where evidence effectively guided policy. One notable example comes from the response to the 2008 financial crisis. In 2009, the U.S. Federal Reserve led the Supervisory Capital Assessment Program (SCAP), better known as the bank stress tests. This initiative offers valuable insights into how evidence can inform policy even during high-pressure crises. 7
The SCAP was designed to determine whether major financial institutions had sufficient capital to withstand a worse-than-expected economic scenario. The methodology involved: 7
The results, released in May 2009, showed that 9 of the 19 banks needed to raise approximately $75 billion in additional capital. Crucially, the process successfully restored confidence in the banking system because of its transparency and credibility. Rather than triggering panic as some feared, the clear assessment allowed stronger banks to demonstrate their resilience and gave weaker banks a path to address their shortfalls. 7
"Examiners were dispatched to evaluate them, and banks that were declared sound reopened to renewed depositor confidence."
The stress tests illustrate several conditions that facilitate evidence-based policy: a clear crisis demanding action, strong leadership commitment to transparency, a methodology that balanced rigor with practicality, and a communication strategy that emphasized clarity and credibility.
| Research Tool | Primary Function | Policy Application Examples |
|---|---|---|
| Historical analysis | Understanding context and precedent | Identifying past policy successes/failures |
| Economic modeling | Projecting outcomes of policy options | Forecasting economic impact of tax changes |
| Randomized controlled trials | Isolating causal effects | Evaluating social program effectiveness |
| Cost-benefit analysis | Comparing policy alternatives | Assessing environmental regulations |
| Stakeholder consultation | Incorporating diverse perspectives | Designing healthcare reforms |
Despite these challenges, researchers and policymakers have developed strategies to increase the use of evidence in policy. These approaches recognize that evidence alone is insufficient—it must be translated, timed, and tailored to the policy context.
Effective knowledge exchange requires ongoing relationships between researchers and policymakers rather than one-way communication. The National History Center's Congressional Briefings Program illustrates this approach, bringing historical perspectives to policy issues through regular briefings on Capitol Hill.
The most promising approaches involve co-producing knowledge through early and ongoing collaboration between researchers and policymakers. This might include embedding researchers within government agencies or involving policymakers in defining research questions.
Given that policies often need adaptation to local contexts, some scholars recommend a more flexible approach to evidence-based policy. Adaptive implementation acknowledges that policies may need modification to accommodate different settings, populations, and resources.
An integrated model combining the Collaborative Knowledge Model and policy entrepreneurship mindset emphasizes co-creating knowledge and evidence-based policy solutions that combine scientific evidence with practical knowledge about implementation challenges.
The challenges to evidence-based policy advice are substantial—from the different cultures and timelines of researchers and policymakers to the deliberate manipulation of science by vested interests. Yet abandoning the ideal of evidence-informed policy would be disastrous, leading to more ineffective, wasteful, and even harmful policies.
The solution lies in recognizing that policy is never determined solely by evidence—nor should it be in a democratic system where values, preferences, and trade-offs must be reflected in collective decisions. Rather than aiming for a technocratic ideal where evidence dictates decisions, we should strive for a system where evidence informs, illuminates, and improves policy decisions alongside other legitimate considerations.
This requires humility from researchers—acknowledging that evidence alone cannot resolve value conflicts—and greater sophistication in how they engage with the policy process. It also demands greater sophistication from policymakers in evaluating and using evidence, including recognizing when vested interests are manipulating the scientific record.
As we face increasingly complex challenges from climate change to public health crises to economic disruption, we need both robust evidence and democratic deliberation. The future of effective governance depends on integrating these sometimes competing imperatives rather than choosing between them.