  We show that modularity maximization with the resolution parameter offers a
unifying framework of graph partitioning. In this framework, we demonstrate
that the spectral method exhibits universal detectability, irrespective of the
value of the resolution parameter, as long as the graph is partitioned.
Furthermore, we show that when the resolution parameter is sufficiently small,
a first-order phase transition occurs, resulting in the graph being
unpartitioned.
