Conventional approaches define income poverty as a binary status, implying that being poor or nonpoor is equivalent across groups. The authors propose a novel visualization that moves beyond head count rates to display group-specific income distributions relative to the poverty threshold, simultaneously illustrating poverty prevalence, poverty gaps, and what the authors term poverty buffers: the distance above the threshold capturing income security. The authors apply this approach to all children aged 0 to 18?years in Sweden in 2022, by mother’s country of birth. The visualization reveals three patterns obscured by standard indicators. First, head count poverty rates vary dramatically, from 8?percent to 77?percent across groups. Second, average poverty gaps are surprisingly similar despite vast differences in prevalence, reflecting stark stratification by parental migration background. Third, poverty buffers reveal cumulative advantage: lower poverty rates coincide with substantially greater income security. By rendering gaps, buffers, and full distributions in a single figure, this visualization exposes dimensions of inequality that no single poverty measure captures alone.