A key pre-training strategy for models designed to understand long documents involves corrupting the input text. Consider two distinct corruption methods: (1) randomly shuffling the order of complete sentences within a document, and (2) replacing a span of text, which could include parts of sentences or multiple full sentences, with a single special token. Analyze how these two methods would likely differ in the types of linguistic understanding they encourage the model to develop.