Comment on Forced to lie on a questionnaire

zqwzzle@lemmy.ca ⁨4⁩ ⁨days⁩ ago

• pipes@sh.itjust.works ⁨4⁩ ⁨days⁩ ago

  I’m exclusively on Pinterest 100hours/week. (I forgot to close the tab with the image search for cool origami)

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  • dependencyinjection@discuss.tchncs.de ⁨4⁩ ⁨days⁩ ago

    What’s the coolest origami you’ve ever made? Never tried it but it seems fun.

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    • pipes@sh.itjust.works ⁨4⁩ ⁨days⁩ ago

      I was kidding mostly but while travelling I did recently make, out of basically waste paper, an origami gift card holder I was proud of :) it opens up in the back and you can slide out the card. I can look for the website with instructions if you’re interested

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      • dependencyinjection@discuss.tchncs.de ⁨4⁩ ⁨days⁩ ago

        Thanks for sharing. Thats very cool.

        If you have the link on hand I’d take a look but don’t go out of your way as it may just end on my endless list of things I might do one day.

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• scarabic@lemmy.world ⁨4⁩ ⁨days⁩ ago

  No one will like hearing this answer but they may already underrated the issue of it being bad data and have a good reason not to care.

  Here’s the thing. When “none” or “skip” is there, people gravitate toward it. You end up getting 75% of people saying “none” for every question, and then your entire survey is meaningless. I hate surveys too. Everyone hates them. All the more reason to just mash “skip” or “none.” Because fuck you and fuck your survey.

  Meanwhile, what % of people don’t touch any of these social networks? Maybe we can’t say for sure, but it’s way less than 75%.

  So you’re choosing between two possible sources of bad data, and choosing the one you know to be of lower magnitude.

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  • superkret@feddit.org ⁨3⁩ ⁨days⁩ ago

    Then provide an “other” option with a text box instead.
    Make entering some text mandatory if you click it.
    No one gravitates toward that.
    Besides, a “none” option can just be discarded when you analyze the data.
    If all your boxes are social media sites, you have no idea which ones are poisoned by bad data, and by how much.

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