Crucially, all these approaches make the same core assumption: that there is one feature of a representation that would make it the "best" (the highest correlation with human judgements, the most regular vector offsets, the closest approximation of a linguistic resource, etc.)
language is a multifaceted phenomenon, and different NLP tasks may rely on its different aspects -which would doom any one-metric-to-rule-them-all approach.