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Historical sociolinguistics is a rich and promising field, which provides scope to deepen our understanding of linguistic variation and change through the analysis of long-term real-time data. However, whilst there has been considerable progress in the field over the last thirty years, the analysis and interpretation of past written texts still requires considerable refinement. A key issue concerns the choice of appropriate textual sources or the so-called “bad data” problem. After reviewing different approaches to the question, we consider the extent to which it is possible to use large-scale multi-genre databases and corpora to track the spread of change through different text types or genres. Some of the issues are illustrated through case studies from the history of French: clitic climbing; agreement with la plupart; and the competition between après, par après and en après. More studies of this kind and more data are required before we can draw firm conclusions either about the way changes spread through different text types, or as to which genres in the past are closer to speech than others.
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