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We quantitatively show that our model is able to retain information about an expected answer category, resulting in more diverse, goal-driven questions.
Answer category leaderboards will now be updated on a daily basis instead of weekly.
As there was no way to fit this middle category into the four-point scale of the MIFARE data we did not include this answer category.2 A final point to notice on this variable is that while MIFARE asked about reducing income differences between rich and poor, the ESS did not include this phrasing.
The chart below also includes NBC/WSJ data, which measures favorability in a positive/negative scale, with a "neutral" answer category).
If the result for any given answer category among men (such as the percentage favorable) was an even number, the result among women was also an even number.
In Table 1, a business was put into the "No answer" category if there were no answer after five or more attempts at contact, which is interpreted as businesses that had not yet reopened.
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Answer categories differ per questionnaire item (see notes below the Table).
Each of the four variables had five answer categories ranging from 'never' to 'often'.
Notes: Bars indicate the percentage distributions of the combined answer categories 'regularly' and 'often'.
with answer categories ranging from 'completely dissatisfied' (0) to 'completely satisfied' (10).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com