I wrote a book and now I have to wrap it up. In that effort, I have many! facts to check. I think I can plow through the bulk of it at ~60 facts per/day for ~30 days (spread across ~10 sources). My new hobby, I guess?
This type of tedious, detailed work is not my favorite thing. I have the source material, but I need to go back and scrutinize what I wrote in detail to make sure it's correct.
On one hand, it may have been easier if past Nicole did a better job at documenting details along the way. On the other hand, it was really unclear what would make it through the final filter and documenting every little thing would have been even more tedious (and would have disrupted the process of connecting it all together).
Any tips for how to make this new hobby of mine easier or more pleasant?
Extremely typical of @analog_ashley that she is capable of giving a talk in a bar that's both a full stand-up comedy routine that has people shouting with laughter yet also teaching how to engage with open datasets in neuroscience
Lord do I wish tech conferences had more talks like this
I have a weirdly good memory for number strings, getting 100% of them right on the WAIS forward digit span test, which the examiner said they never seen before. This is helpful mostly because I can memorize license plates of cars that seem like they're about to hit me while riding my bike, and it's dangerous because I remember all my credit card info and can buy stuff online really fast lol
@elduvelle_neuro
In the US, some institutions will extend a complementary faculty title to any postdoc ambitious enough to submit a grant. And sometimes they are awarded! In that case, many grants are open to you.
That said, grants to do data analysis are a bit few and far between.
(Academic press) book pre-publication reviews are back. Really positive. YES!!!!!!!!!!!! 🎉🎉🎉.
So now I'm moving onto final revisions. It feels good to slip back into that headspace again.
My big question for anyone who has sent a book off to the world: What was your strategy for those last steps? There's addressing the feedback, of course. But after that? It will never been perfect. But it has to be great. How do you know when to let it go?
There are so many different types of researchers. Weather researchers, climate researchers, brain researchers. And within those categories, the nuances (like memory researchers).
When someone says they are an X researcher, what does that imply to you? In other words, what qualifies? Does it just imply that they are curious about X? Or perhaps that they know a bit more about it - perhaps they've mastered some scholarly literature or they've done at least one experiment? Or maybe even published a paper in a peer reviewed journal? Or maybe even more - perhaps they have a body of work on the topic; maybe they even run a lab (and have grants to support X research).
On one hand, no one should gate keep curiosity! On the other, certain terms imply knowledge and qualifications. I'm a "researcher". But just because I know a lot about memory doesn't automatically mean that people should listen to me about climate or economics. And I once read a very good book about ecosystems, but I don't think that means I should quality as an ecosystem researcher. So what, then, might instead?
@analog_ashley
Great point! The field has built things up to require some bravado to declare "Yes, I'm computational". What qualifies? Is y=mx+b enough? Does x need to be a vector? Or do you need to be able to define what a "Jacobian" is?
Some of my best computational insights have been of the form: if you and and subtract and apply a threshold, then ....
@APBBlue
Solidarity. My sense there is that some of us are open to reading glasses when 14 pt font menus are a normal distance from our face whereas others of us won’t give in if there’s any arm length distance we can still read a menu. If you look around at a restaurant, the more sensible among us have glasses on. The less sensible … (just look; it’s amusing!)