early career academics and the fuss about glam

Trying to publish glamorously in a high impact factor journal is not a bad thing if you do it purely by having a great, high quality study to publish that changes the world – or at least influences your field. But reading such ‘glam pubs’ I sometimes feel they were pushed into that journal by just boldly overselling the work’s importance. Scientists are usually very carefull with their statements. So what makes them completely oversell what they did? I think it is the high competition among early career scientists and career path insecurity.
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Barplot Madness

Maybe it is because of the change in fields and scientific environment, but I increasingly doubt data presented in talks, posters and articles. Mostly because I find myself wondering whether the choice of statistical description of the data makes any sense. I am not speaking of advanced statistics at all, just the simplest descriptive techniques and the choice of the right plot for it.

figure 1. X represents spike rates, categories cell types A and B respectively. Whisker indicates standard deviation.
figure 1. X represents spike rates, categories cell types A and B respectively. Whisker indicates standard deviation.

My doubts are usually raised when I see a bar plot as sketched in figure 1. What looks like a rather okay representation of data actually does not really give you an intuitive idea of how the data are distributed.
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Survey: The Ultimate Goal of Neuroscience

I am planning a blog post on what the Ultimate Goal of Neuroscience is. I would like to make a survey first, to hear from all you neuroscientists out there, what you think, is the big goal of neuroscience. I will present the results in this blog and write a commentary on it.

The question is: “Given unlimited ressources (infinite time – yes immortatlity, people, money, technology, everything), what would be the ultimate goal or ultimate application that would crown your neuroscientific work?”

Please write your brief(!) answer in the comments below, or twitter (don’t forget to adress me: @DennisEckmeier)! Please be creative! ‘Duh, everything.’ does not count! And spread the word!

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Cite the shite out of this site. Or better don’t.

I caused a little outrage among the passionate social designers of the future science community, lately. They usually envision a brighter future for science communication, discussing evaluation metrics, funding practices and strongly facilitate open access publishing, open data, science writing, and whatnot. I greatly appreciate this – I convinced my skeptical PhD adviser to publish open access in 2008 and I made suggestions about which online medium would serve best as a publishing platform that has great post-publication review features built in (via Twitter). Still I got called a ‘complete fool’ with an ‘unfortunate, outdated attitude’ by one of them (HHMI Investigator Michael Eisen, via Twitter). Why? Because I don’t see why an article has to mention everybody the author was ever inspired by and I do not think that every source should be ‘cite-able’ – like Twitter (in parts storified by @Hysell).

I made a ‘trollish’ (@sarcastic_f, via Twitter) comment as I entered the general discussion by indirectly responding to ‘We need better culture of citing blog posts, not just papers.’ (Michael Eisen, via Twitter), saying ‘I disagree. I would never quote a blog because most of them are terrible and almost all others are still not worth it.’ (DE, via Twitter). Of course this made a bad first impression. Ironically, what I then received became a collection of tweets directed at me that serves as a great example for why sources like twitter should not be considered cite-able – and I include my own. Because they are not meant to be official statements and people – even scientists – don’t act like professionals when using social media. And such free space is good for us!
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