Neutron-skin thicknesses provide a sensitive probe of the isovector sector of the nuclear equation of state and its density dependence, commonly characterized by the symmetry-energy slope parameter $L$. A wide variety of experimental and observational methods have been used to extract neutron skins, ranging from hadronic and electromagnetic probes of finite nuclei to inferences from neutron-star observations. Each approach carries distinct theoretical and systematic uncertainties, complicating global interpretations and obscuring genuine physical trends. In this work we present a hierarchical Bayesian framework for the statistically consistent synthesis of heterogeneous neutron-skin constraints. The neutron-skin thickness is modeled as a smooth latent function of isospin asymmetry and nuclear size, while method-dependent bias parameters and intrinsic nuisance widths are introduced to account for unmodeled experimental and theoretical systematics. Focusing on the tin isotopes, we infer probabilistic neutron-skin trends from ${}^{100}\mathrm{Sn}$ to ${}^{140}\mathrm{Sn}$, finding minimal uncertainties near stability and increasing uncertainties toward the proton-rich and neutron-rich extremes. We assess the consistency of nuclear energy-density functionals and obtain conditional constraints on the symmetry-energy parameters. The resulting posterior exhibits a pronounced compression of the symmetry-energy slope parameter $L$, reflecting the dominant sensitivity of neutron skins to subsaturation symmetry pressure. We demonstrate that our hierarchical Bayesian framework provides robust and transparent constraints on the subsaturation isovector sector of the nuclear equation of state.

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• Equations of state of nuclear matter
• Neutron skin thickness
• Nuclear matter in neutron stars
• Nuclear reactions
• Nuclear structure & decays
• Bayesian methods