Policy Evidence Readiness Levels (PERLs)
Policy Evidence Readiness Levels (PERLs) classify how mature an evidence base is and what action that maturity supports. They give funders, evaluators, and evidence synthesists a common language for matching decisions (and the claims used to justify them) to the strength of the underlying evidence.
The evidence gap PERLs fill
Rigorous impact evaluation has never been stronger. Yet the field still lacks a shared way to express how mature the evidence base behind an intervention actually is, and what that maturity justifies. A single well-identified study and a synthesized body of science are routinely invoked as similarly credible evidence of effectiveness — in funding decisions, scaling choices, and appeals to “follow the science” — even though they support very different actions.
The consequences are substantial. Interventions get scaled, and millions of dollars invested, on promising early results that later fail to replicate. Evidence-backed claims are produced without signaling whether they rest on an evolving or a mature evidence base, leaving their weight for decisions unclear. And caution is too easily framed as anti-evidence or skeptical of science, when such skepticism is often justified given what the evidence actually shows.
Policy Evidence Readiness Levels provide the missing signal. Modeled on NASA’s Technology Readiness Levels, which classify whether a technology is ready for deployment, PERLs classify whether an evidence base is ready to support experimentation, targeted adoption, or broad scaling. They are a technical assessment of evidence maturity, not a normative judgment of whether a policy is desirable, affordable, or politically viable. And they are not a gate to prevent action as evidence is still evolving; acting on early-stage evidence is often necessary. What PERLs require is that the claims and commitments made on that evidence match what it can actually support.
PERLs at a glance
Evidence matures in stages. A decision-maker can act at any stage — but what the evidence can honestly be claimed to show, and how far it justifies committing, changes as it matures.
The PERL staircase: what the evidence supports, and what “following the science” means, at each level of maturity. Adapted from Cotton (2026), Science.
The levels in detail
| Level | What the evidence shows | What following the science means |
|---|---|---|
| PERL 1 — Preliminary insight (“It might work”) | A theoretical or observational basis for expecting an intervention may be effective, but no rigorous evidence of impact. | Support research design and piloting, not implementation. Present findings as hypotheses to be tested — not as evidence that the intervention works. |
| PERL 2 — Emerging evidence (“It can work”) | Rigorous evidence of potential effectiveness — from a controlled trial under specific or favorable conditions, or comprehensive field research documenting impact without establishing causation. Not yet tested causally under representative implementation conditions. | Fund effectiveness trials under representative conditions. Present results as promising but preliminary: evidence that the intervention can work, not that it will work across contexts or at scale. |
| PERL 3 — Evolving evidence (“It works here”) | Robust evidence of real-world impact, including at least one rigorous causal evaluation under representative delivery conditions — but not yet mature enough to support general guidance on cross-context robustness. | Adopt in contexts matching the successful studies; scale into new contexts incrementally and adaptively. Frame recommendations as conditional rather than universal, noting where evidence gaps remain. |
| PERL 4 — Mature evidence (“It works, broadly”) | A systematically synthesized evidence base — rigorous reviews and meta-analyses that address heterogeneity and cross-context effectiveness — supporting generalized guidance, including which variations work best and for whom. | Act on the synthesized guidance and scale broadly. Continue to monitor fidelity and revisit the evidence base, as effectiveness can change as conditions evolve. |
At every level, the danger is the same: acting as if the evidence were more mature than it is. PERLs do not tell decision-makers to wait. They align claims and commitments with what the evidence can actually support — and shift the burden of justification onto those arguing to implement before the evidence has matured.
Putting PERLs in practice
PERLs are designed to fit existing workflows rather than replace them. They function as a meta-standard. Like NASA’s Technology Readiness Levels, they provide a shared scale without prescribing how any single study should be conducted or assessed.
- Funders and program officers can require a PERL classification in proposals and evaluations, reserving broad implementation funding for interventions supported by mature, synthesized evidence while directing innovation funds toward testing and incremental scaling of less-ready candidates.
- Evaluators can report a PERL classification alongside findings, making explicit what the evidence supports (and does not yet support) for scaling.
- Evidence synthesists can state the PERL of the evidence base a review assesses. A systematic review of an evolving evidence base and one of a mature base can support very different actions; a PERL classification makes that distinction legible. This becomes increasingly important as AI makes on-demand evidence synthesis routine.
- Policymakers, journalists, and advocates can evaluate claims about what “the science” supports against a common, contestable standard.
Assessing evidence
The same logic can be applied quickly to any claim that an intervention “works.” Four questions locate roughly where an evidence base sits:
- Is it one study, or a body of research? A single result, however rigorous, is a starting point; confidence comes from findings that repeat.
- Was it tested under representative conditions, or ideal ones? Effects established under favorable conditions or by expert teams often shrink in ordinary delivery.
- Does it hold beyond where it was first shown to work? Success in one setting or population does not guarantee it transfers to others.
- Has the whole evidence base been independently synthesized? A systematic review weighing all the studies together — not a single team’s read of its own work — is the mark of mature evidence.
A reference card for assessing how mature the evidence behind a claim is. Adapted from Cotton (2026), Science.
Reference and reuse
PERLs are introduced in a peer-reviewed article in Science. The framework and the figures above are free to use with attribution, including in evaluations, funding and procurement guidelines, systematic review protocols, teaching, and reporting.
Cite as: C. Cotton (2026). Rigor is not readiness: The PERL framework for evidence-based policy, Science 393 (6810): 463–5. doi:10.1126/science.aef3529
Read the article: doi.org/10.1126/science.aef3529. Please credit figures as “Adapted from Cotton (2026), Science.” If your organization is considering incorporating PERLs into evaluation, funding, or evidence-synthesis guidelines, please get in touch.
Chris Cotton 