A polarization score is supposed to describe a community, not its surroundings. Yet when a minority community is embedded in a larger network, its measured polarization can rise or fall with the size and structure of the majority around it. We ask whether polarization measures are therefore fair to minorities and develop an audit built around two criteria: measurement invariance (MI), which asks whether otherwise equivalent majorities and minorities receive equivalent scores, and structural exogeneity (SE), which asks whether a minority's score changes when its surrounding majority changes. Resolution sensitivity (RS) is treated as a prerequisite for meaningful fairness assessment. We audit seven polarization measure families spanning the three network-operationalizable dimensions of polarization, introducing Network-Weighted Distance (NWD) to fill an unserved extremeness-separation combination. Across controlled synthetic networks, mechanism-isolating diagnostic topologies, and real political and communication networks, no measure passes all applicable checks. Minorities are systematically scored as more polarized than equivalent majorities. We trace this dependence to two separate channels: majority structure can alter the opinions that opinion-reading measures consume, and, on a different path, opinion-orthogonal structural change can affect the arithmetic of structural measures. Reading opinions is thus double-edged, letting contamination in when structure moves opinions but shielding the score when structure changes and opinions do not. We close with practical guidance for reporting polarization scores without inheriting these biases.

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