Researchers of the past – whether historians, literary scholars or archaeologists – depend on the sources that have stood the test of time. That sample of history is usually far from complete, however. There are numerous reasons for this, such as natural causes (e.g., fires or floods), decisions at the level of archival policy (what do we preserve and what do we not?), and biases in the formation of the archives themselves. Data representing lower classes were long considered less relevant, for example, and thus socioeconomic factors likewise play a role in the survival of sources. In a series of recent experiments, we have explored how statistical methods from ecology can help us identify such gaps and biases in our knowledge. Those methods all find their basis in “Unseen Species Models,” which were originally developed to estimate the number of unique species in an environment. Just as ecologists try to estimate biodiversity from an incomplete sample, we apply the models to incomplete historical archives to measure the actual cultural diversity.
„Folgert Karsdorp & Mike Kestemont: The application of unseen species models in history: correcting registration bias in nineteenth-century police reports from Brussels“ weiterlesenFolgert Karsdorp & Mike Kestemont: The application of unseen species models in history: correcting registration bias in nineteenth-century police reports from Brussels
