I'm wondering: if I use someone else's data in my paper, should they be co-author? And if someone uses my model in their paper, should I be co-author? What about if all my analyses use brms? Should @paulbuerkner and @mcmc_stan always be co-authors?
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Why do non-modelling people feel the need for example to tell me that modelling is easy? When they are probably from the same group who say modelling is hard? Why? I don't say anything is easy about data collection.
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Again, it’s not the difficulty level. BOTH ARE HARD. It’s the level of control. If your code is hard to debug, that’s on you—you wrote it! If you have a hard time publishing something, you picked the topic. Exp have these problems too, obviously.
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I still don't get it. Why are non-modellers always behaving like it's zero sum? Also... all debugging is hard and not all code is single-developer code.
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We are talking about *authorship*, it should be obvious that whoever builds a model authors it, that authorship does not rely on the difficulty or riks entailed in a task. However, and talking as both empirical (animal) scientist and modeller, I don't think that
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using others' models, data or methods directly qualifies someone as co-author. IMO, it would depend on their implication on that specific study. Your research is not an investment in others'
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Yeah, totally agreed. I do think
@shravanvasishth is picking up a on real thing though were data collectors are more protective than modellers. And modellers do get very little recognition in general. Many relegated to middle author almost always. -
This is why I do very little when I am asked to model something for people now, because I know I will be middle author even if I do a tonne of modelling.
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The only way as a modeller I can be first author is if I don't allow any data-collectors to be involved.

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