How does peer review affect research reproducibility?

Peer review's intended role is to assess research quality, check methodology, and validate conclusions before publication. In practice reviewers evaluate design, statistical analysis, and novelty, but they rarely rerun experiments or reproduce analyses. The Open Science Collaboration led by Brian A. Nosek at the University of Virginia and the Center for Open Science reported that fewer than four in ten replication attempts in psychology produced statistically significant results consistent with original findings. That empirical evidence highlights a gap between peer review's evaluative function and the technical verification required for reproducibility.

Peer review's strengths and limits

Peer review can catch obvious methodological flaws, ethical problems, and poorly supported claims. Reviewers with domain expertise identify inappropriate controls, misapplied statistical tests, and overstated conclusions. John P. A. Ioannidis at Stanford University has argued that systemic biases including selective reporting and small sample sizes increase the likelihood that published findings are false. Peer reviewers can mitigate some of those biases by demanding transparency, but traditional review timelines and volunteer reviewer labor constrain thorough checks. Reviewers seldom have access to raw data, original code, or the time to reanalyze datasets, which reduces their ability to confirm that results reproduce.

Structural barriers to reproducibility

Cultural incentives in research reward novelty and positive results, creating pressure to publish rather than to replicate. Monya Baker at Nature documented in a major survey that a large majority of researchers had failed to reproduce another scientist's experiments and many had failed to reproduce their own. Resource disparities also matter. Laboratories in low-income regions or underfunded institutions may lack capacity to run replication studies, creating territorial inequities in who verifies which findings. In fields with strong environmental or public health consequences, such as conservation biology or epidemiology, irreproducible findings can misdirect policy, waste limited conservation funds, and erode public trust in science.

Consequences and reforms

The consequence of weak reproducibility verification during peer review is a literature that may accumulate unreliable results, slowing scientific progress and contributing to inefficient use of public and private funds. Policy decisions based on unreproducible studies risk harm to communities and ecosystems. To address these problems, journals and funding agencies are experimenting with reforms that strengthen the link between peer review and reproducibility. Registered reports, which evaluate hypotheses and methods before results are known, reduce publication bias. Data and code sharing mandates enable reviewers and later readers to inspect and rerun analyses. Open peer review and collaborative platforms promoted by the Center for Open Science provide transparency in reviewer comments and editorial decisions.

Human and cultural dimensions

Improving reproducibility requires changes in evaluation and reward systems across disciplines and territories. Encouraging replication work, valuing transparent practices in hiring and promotion, and supporting infrastructure for data sharing can shift norms. For communities relying on applied research, including Indigenous and rural territories, reproducible science ensures that interventions are based on reliable evidence. Peer review remains a vital quality filter, but without coupled structural reforms it cannot by itself guarantee reproducibility.