Want a Nobel Prize? Better be called John! A Bayesian Survival Analysis of Nobel Prize Timing
The Nobel Prize in Physics, Chemistry, and Physiology or Medicine is awarded annually to scientists whose contributions to human knowledge are judged, by a committee in Stockholm, to be sufficiently important. We ask: by what other factors might prize timing be predicted? To answer this, we assemble a pool of 1,012 plausible candidates drawn from Wolf, Lasker, Gairdner, and Clarivate Citation Laureate lists, fit a Bayesian Weibull Accelerated Failure Time model to their survival times, and extract posterior estimates of what structural features shorten or lengthen the wait. The strongest predictor is not citations, not institutional prestige, and not field. It is the scientist's first name. We find a 7.8× difference in expected Nobel waiting time between the most and least structurally advantaged career pipelines. None of our findings will surprise working scientists. We publish them anyway.