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Boud

@darius

Assuming that "medium" is logarithmic, i.e. about 1000 or so users, there are a few hundreds of these - so you presumably intend to subsample these medium-sized instances, e.g. aim at 10-20 interviews.

Splitting up into e.g. 5-10 medium and 5-10 small instances would increase the sample error and bias, as @jcolomb said, but also increase the chance of better studying all scales: big + medium + small.

The risk of the big crushing the small seems like a significant governance question.

6 comments
Joni Fieggen

@boud @darius @jcolomb I would also argue that a ‘medium and large’ runs a significant risk of skewing heavily white, and mostly male.

Plus the fact that it’s folks from the US, with US money, on a network that for once isn’t as dominated by American interests and governance as almost everything that came before.

Darius Kazemi

@mejofi @boud @jcolomb It just occurred to me that we might not be talking on similar terms here: for me the break point for "medium" is about 150 people, where it is unlikely for everyone to know everyone else. Because to me that is a place where governance mechanisms become necessary rather than just a good idea. I talk about this in runyourown.social

Re: the American thing, it's a valid criticism and I am trying to be mindful of my biases. We want an international sample for sure.

Joni Fieggen

@darius @boud @jcolomb I would still be wary of excluding BIPOC folks that way, though, so I’d argue that you should probably be correcting for that in a parallel track that doesn’t select based on instance size. As in, also talk to folks on Black-run instances, for example, even if they are small.

Joni Fieggen

@darius @boud @jcolomb Might not be a bad idea to be explicit about this in both of your posts on this topic 🙂

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