Statistical significance is often treated as a stamp of truth, but I've seen too many studies with p-values under 0.05 fail to replicate. For example, in psychology, the replication crisis showed that many landmark findings didn't hold up. Should we rely more on effect sizes and confidence intervals instead? What's your take on balancing statistical rigor with practical significance in research?