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mekline /
Last active Jul 19, 2018
How I screwed up participant privacy and what I did about it

The problem

A while ago, I cottoned on to the (pretty obvious, in retrospect) fact that even if you are not sharing a piece of information in plain text, if it can be derived from your dataset, it counts (ethically, and probably according to your IRB/equivalent body of choice) as sharing that info. I thought I had successfully handled this wrinkle in my data sharing, but I found out I hadn't.

I collect three types of personally identifiable information (PII) in my research:

  • Video of the children who participate in my studies, primarily so I can check that paradigms are being implemented correctly/consistently, and to hand-check eyetracking data. I'm not the head of a lab so I don't share video (following my labs' practices), but if I was, I'd use Databrary to provide access to researchers who've been vetted by their institutions.

  • First names, because calling your participants "Hey You" is rude so it winds up on the video, and recording the name they're referred to in t

View gist:2d6fcdbbeebc92ab005531d9bd8d0157

This isn’t really a post about statistics so much as about my personal experience. I’m feeling down about the upcoming job market and decided to test my impression that ‘all the guys are getting jobs’. Here are the stats for the early career researchers coming out of my labs, which I feel the need to stress are run by VERY supportive, mostly female PIs.

Filter: from on of the 4 labs I've worked closely with, currently holds a pHD, and I overlapped with them for at least a year in grad school.

Faculty or accepted offer - 8F, 13M

Still postdoc-ing - 9F, 0M

Outside academia - 1F, 3M (There's a chance I'm underestimating this category depending on how people are listed on the alumni website.)

mekline /
Last active Feb 11, 2019
Giving academic presentations

Giving academic presentations

I'm noticing some pattens in the feedback I give to people when we're doing lab practice talks, so I decided to write it down. None of it is that revolutionary, and I'm confident that at least some of it is directly from Ted Gibson (@LanguageMIT) & Rebecca Saxe (@rebecca_saxe) in particular. It's all stuff I wish I had known when I started giving conference talks.

I find this model of The Audience to be helpful to think about when designing talks. It's not meant as a criticism of scientists, audiences in general or anything like that. When I am in an audience, I consider all of the below to be true of me. It IS meant to provide a way of thinking of audiences as a decidedly non-scary or judgemental body. If there are people in the audience, it's because they want to hear YOU talk (see point 1). Someone is probably going to have a negative opinion about you no matter what, and that's okay. Also, this advice is written for the personality type of many scientists - careful, prec

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