Which Comparisons Does a University Ranking Support? Typed Indeterminacy in the QS World University Rankings: Latin America & The Caribbean 2027 Under Imprecise Weights and Data

University rankings publish positions and bands that readers may interpret as precise comparisons. We examine which comparisons the QS World University Rankings: Latin America & The Caribbean 2027 supports under imprecise weights and indicator data, and assess change using both the 2026 and 2027 editions. Nominal weights centre an epsilon-contamination credal set with an imprecise Dirichlet interpretation. Missing indicators enter as observed-range intervals, and one-decimal scores reflect rounding uncertainty. Closed-form necessary orders and sequential typing distinguish conflict, ignorance and resolution among 517 institutions. At ε=0.10, only 4.0% of 5115 near pairs (reference ranks at most 10 positions apart) have a necessary order, against 61.2% of all pairs. Conflict represents 99.3% of undecided neighbouring pairs; ignorance represents 55.6% overall. An eight-coalition factorial analysis and symmetric Shapley attribution allocate 70.1% of additional neighbouring indeterminacy to weights and 57.3% of additional overall indeterminacy to missing indicators. For 494 matched institutions, mixed-integer optimisation closes 1976 marginal rank-endpoint problems under edition-specific admissible weights. Median change-hull width falls from 365.5 positions under outer bounds to 294 under attainable endpoints; exact rational witnesses support both a rise and a fall for 493 institutions. These are model-based possibilities, rather than evidence of stability or institutional quality. The analysis combines necessary comparisons, attainable rank and change bounds, and complementary sequential and symmetric descriptions of indeterminacy. Its findings support reporting comparison precision and underlying indicator coverage alongside ranking positions.