during my #PhD, i conducted a side project investigating what the barriers are towards making changes to the #academicpublishing system to reduce publication #bias
i got about 50:50 praise and hate for this. weirdly enough, the praise and hate were often about the same thing: the (early) stage of my career.
praise: "it's great you're so keen and have grasped key issues and taken action so early..." 2/8
hate: "you're too early in your career and naïve to understand these issues. you shouldn't be researching this"
more worryingly, whilst i did get a lot of this feedback in person/by email, some of it was BEHIND MY BACK to my colleagues 3/8
ofc, my naivety WAS true & was in some ways a valid critique. but they never actually critiqued the research, so it wasnt helpful feedback
speculatively: id guess i had actually read more research about publication bias than most of these academics 4/8
naivety can also be a good thing: at that stage of my career i hadn't hypernormalised the perverse structures that uphold academic publishing. so i was seeing the problem with fresh eyes 5/8
this is a microcosm of a wider #academic problem: (senior) academics often don't like #ECRs with big ideas. ESPECIALLY if they are #women (and i imagine also other marginalised identities) 6/8
i really appreciated the actual critical feedback though, some people highlighted some really useful pitfalls of the work, but they did it with respect and could still see the merit of the work, and understood that some limitations were unavoidable. 7/8
we should to better at encouraging critical and blue sky thinking in a non-discriminatory way.
if we don't, we are actively blocking innovation, creativity, and ultimately knowledge production.
post-script: the idea of "you're too naïve" doesn't really hold up scientifically either. we all have to start somewhere; how are we meant to become not-naïve if we aren't allowed to #research anything we are naïve to?
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ok i've used R now for about 10 hours so im definitely suitably enough experienced to say i hate it, its a big pile of shit, i dont know why this is what is popular, and i wish i had access to stata again. WAHHHHH
im sure people can tell me a million reasons why R is great. sorry to say: YOU'RE WRONG.
i will delete these tweets in a few weeks when it finally clicks and i think R is brilliant like everyone else does
when it comes to engaging #STEM#academics (an essential task in order to gain max momentum to tackle problems like #casualisation), i think 1 difficulty is that #activism uses a lot of logical fallacies. this makes taking action appear irrational 1/15
identifying an issue (e.g. casualisation) and claiming it impacts other issues (e.g. mental health problems) = potential false cause, and/or hasty generalisation fallacy
making broad statements (e.g. gender pay gap is a real problem) = ambiguity fallacy
3/15
i promised in this thread i'd offer an idea of an alternative #academic#publishing model, so here it is. be prepared, changing to this would require some seriously radical change... 1/17
il do this comparison with the last paper i got formally accepted to a journal as these 2 co-occured so there's no "time effect" or anything as a confounder. (JP = journal publishing; PP = preprint publishing) 2/9
JP: rejected 6 times (i think); 3 were editorial rejections *explicitly* mentioning the null findings as a reason for rejection
PP: paper is out there open for anyone to openly critique and i welcome this 3/9
(i still have a few collaborative papers to write and these will be published properly for the benefit of my co-authors)
i will soon publish a paper on a pre-print server, with no intention of submitting to an academic journal. my reasons for this are manifold 2/38
1. #academia is inherently corrupt & the publication model facilitates this:
- unpaid labour (editors, peer-reviewers,& authors [ok, they do get paid by the uni which oft = public funds yet journals privately profit & we see none of this unlike other forms of publishing]) 3/38