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Corpus Linguistics is a relatively new field which was made possible as a result of the wider availability and use of personal computers in the last quarter of the twentieth century. This chapter illustrates the incorporation of both corpus-based and corpus-driven approaches into a small-scale study that examined United States media's framing of a controversial federal budget negotiation involving disagreement between members of the two major political parties in the United States. The chapter argues that Gwyneth FOX's coverage of the fiscal cliff negotiations presented impending or proposed changes to income tax structure in the United States as undesirable to the reader by framing them as increases over a normalised Bush-era system of taxation. It demonstrates how machines can aid human beings to make more credible interpretations based on salient linguistic patterns in large amounts of data that may otherwise have been overlooked.
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Stored only when both papers are in the corpus — 25 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.