Lmao I asked chatgpt what some common falsely flagged words are and it literally used Scunthorpe as an example:

Certainly, here are some examples to illustrate how non-offensive words might be falsely flagged as slurs, highlighting the importance of context and nuanced understanding in slur detection systems:

1. Ethnic Names/Terms:

   • “Niger” (the name of a country) might be flagged due to its similarity to a racial slur.
   • “Shiite” (a sect of Islam) could be mistaken for a derogatory term due to phonetic similarity.

2. Geographical Locations:

   • “Essex” (a county in England) might be flagged due to its ending, which could be misinterpreted as a sexist term.
   • “Scunthorpe” (a town in England) contains a substring that is a common vulgar term, leading to potential misflagging.

3. Historical Terms:

   • “Spartan” (relating to Sparta in ancient Greece) could be misinterpreted if the system is not aware of historical contexts.
   • “Crusader” (referring to participants in the Crusades) might be flagged due to its aggressive historical connotations, despite being a legitimate term in many contexts.

4. Animal Names:

   • “Tit” (a type of bird) might be flagged due to its double meaning, one of which is vulgar.
   • “Cock” (a male chicken) could be flagged for similar reasons.

5. Technical Terms:

   • “Homo” (as in Homo sapiens, the scientific name for humans) could be flagged due to its use as a derogatory term for homosexual individuals.
   • “Uranus” (the seventh planet from the Sun) might be flagged due to its phonetic similarity to an anatomical term.

These examples underscore the complexity of language and the need for sophisticated, context-aware algorithms in slur detection systems to minimize false positives.