Investigating replicability in the social and behavioral sciences
Publication id: tyner-2026-score-replicability
Status: verified
Citation: Tyner, A., ..., Shakya, S., ... et al. (2026). Investigating the replicability of the social and behavioural sciences. Nature. Download PDF
Facts¶
Policy hook¶
How replicable is social and behavioral science research? Systematic assessment can identify which finding types replicate reliably and which warrant skepticism before policy application.
Main finding¶
Systematic replication study examining replicability of published findings across social and behavioral sciences identifies patterns in which result types successfully replicate.
Data and setting¶
Large-scale replication study of social and behavioral science findings; Systematizing Confidence in Open Research and Evidence (SCORE) project in Nature publication.
Research design (plain language)¶
Coordinated replication of many published studies using standardized protocols to measure what percentage of original findings successfully replicate.
One caveat¶
Replication success depends on exact protocol adherence and resource constraints may prevent perfect reproduction of original conditions.
PDF or DOI¶
Why it matters¶
Science depends on cumulative knowledge, but cumulative knowledge is undermined if published findings don’t replicate. SCORE’s large-scale replication project is landmark work because it measures what percentage of social and behavioral science findings replicate with new data. If replication rates are high, the field is trustworthy; if low, policies built on social science are on shaky ground. For policymakers, the results inform how much confidence to place in social science evidence. For researchers, replication metrics identify which finding types are robust versus fragile, directing future work toward understanding what makes results stable. The identification of patterns (which research areas replicate well, which don’t) is especially valuable—it guides researchers toward more reliable methodologies. For public trust in science, transparency about replication challenges (and successes) builds credibility. The caveat that replication depends on protocol adherence is important: negative results don’t always mean the original was wrong, but they do signal the need for caution before policy adoption. SCORE data provides a new gold standard for evidence quality assessment.