[-] [email protected] 6 points 1 year ago
[-] [email protected] 6 points 1 year ago* (last edited 1 year ago)

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.

[-] [email protected] 6 points 1 year ago

Imagine waiting in a drive through.

(I'm an Europoor)

[-] [email protected] 6 points 1 year ago

Wtf on their homepage:

How about my privacy?

We respect users' privacy and do not collect any personal data besides the essential minimum to create and sync your account.

https://reports.exodus-privacy.eu.org/en/reports/399618/

Facebook analytics, Facebook login, facebook share, google firebase analytics and microsoft visual studio app center are present in the android app.

[-] [email protected] 7 points 1 year ago* (last edited 1 year ago)

Oh no the Uhuber

[-] [email protected] 6 points 1 year ago

Look at these tiny wings and long horns

[-] [email protected] 6 points 1 year ago

Probably not a valid excuse with M series macbooks :(

[-] [email protected] 6 points 2 years ago* (last edited 2 years ago)

Not personalized. But what I personally use from time to time is the invidious popular feed, some invidious instances have the popular feed turned on, which shows popular videos streamed on that instance.

Instance list: https://docs.invidious.io/instances/

Example instance: https://vid.puffyan.us/feed/popular

[-] [email protected] 7 points 2 years ago* (last edited 2 years ago)

This is the code (Github link):

class Quitter(object):
    def __init__(self, name, eof):
        self.name = name
        self.eof = eof
    def __repr__(self):
        return 'Use %s() or %s to exit' % (self.name, self.eof)
    def __call__(self, code=None):
        # Shells like IDLE catch the SystemExit, but listen when their
        # stdin wrapper is closed.
        try:
            sys.stdin.close()
        except:
            pass
        raise SystemExit(code)

What happens is that the python repl calls __repr__ automatically on each variable/statement that you type into the repl (except assignments e.g. x = 1). But this basically only happens in the repl. So "executing" only exit wouldn't work in a python script as it is not calling __repr__ automatically, so better you learn how to do it right than using just exit in your python scripts and scratching your head why it works in the repl but not in your code.

[-] [email protected] 7 points 2 years ago

Don't know how techy you are, but I've had some luck with using pandas for stuff like this, though I don't know how good it works on wikipedia.

https://pandas.pydata.org/docs/reference/api/pandas.read_html.html

You can either do the filtering directly on the resulting pandas datframes or export it to whatever format you like including excel or csv

https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_excel.html

https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_csv.html

[-] [email protected] 6 points 2 years ago

Probably because they sell you the FLAC files directly, too. But you are right, it's a high payout, that can't be really sustainable.

e.g.

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Bronco1676

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