This doesn’t need any clarification: cancer really sucks. It’s mentally and physically exhausting, even for people who catch it as a young grad student. My experience until now (described here) was very positive given the circumstances, but support for serious illnesses can be lacking at other funding institutions and universities. Students should be better protected, both during and after their treatment.
Open Science (#openscience) is great! It entails sharing data and code between scientists, so that we can all benefit from each other’s efforts. However, there is a downside to sharing your stuff: You become a helpdesk for people who would like to use it, and sharing distracts from a core part of the job: publishing papers! Because research positions are offered to those who publish a lot, distracting yourself from doing so might put you out of a job in the long run. To solve this problem, publishing open data and software should be valued as much as publishing papers.
Although it sounds like a lot of effort, creating a Twitter bot is actually really easy! This tutorial, along with some simple tools, can help you create Twitter bots that respond when they see certain phrases, or that periodically post a tweet. These bots work with Markov chains, which can generate text that looks superficially good, but is actually quite nonsensical. You can make the bots read your favourite texts, and they will produce new random text in the same style!
Sigmund Freud is back! He returned in the form of a Twitter bot that replies when someone uses the hashtag #askFreud in their tweets. Not unlike the real Freud, Sigbot produces nonsensical, but real-looking text that is produced using a Markov chain. The bot can recognise and respond to specific keywords, and it can speak both German and English.
The PyGaze website was down for a few days, because it exceeded its monthly bandwidth allowance. This has been a problem for a few months now, so we’ve decided to upgrade. Our apologies for any inconvenience, and thanks for using PyGaze!
The Dutch Psychonomic Society’s biennial Winter Conference is upon us! Here, Dutch and international members of the Society meet to discuss cutting edge research. I’ll be there to listen to all of the amazing speakers, and to present a poster on our work in speed skating. Read this post for some additional info, and for a digital copy of the poster.
Two weeks ago, we published a Perspective article on how the starting procedure in racing sports could bias competitions. Some speed skating enthusiasts suggested we analyse the 100-meter times from the races we reported on. So we did! The results are very similar to our earlier results: Longer ready-start intervals lead to slower 100-meter times in Olympic speed skating.
Threatening elements (think spiders) in your surroundings tend to grasp your attention more strongly than non-threatening things (think puppies). Some scientists believe that your brain is wired to notice threatening stimuli quicker, via a special sub-cortical route. In a new experiment, we show that task-irrelevant threatening stimuli are prioritised over non-threatening stimuli, but that they are not processed any quicker.
Yesterday, we reported that random variability in the starting procedure of racing sports can bias competitions, even at Olympic events. Not everyone agreed. In this post we address all questions and criticisms, and provide an extra analysis that looks at within-athlete effects of changes in the ready-start interval on changes in race times. This analysis is robust to differences between skaters’ individual qualities, and has causal power. Our results indicate that there still is evidence that random differences in ready-start intervals might bias competitions. At the very least, this calls for future research into the starting procedure of racing sports. Which is exactly what we intended to provoke with yesterday’s publication.
At Olympic racing sports, the gold goes to whoever is the most talented and has trained the hardest. Or does it? Our new research shows that subtle random differences in starting procedures can bias athletes’ alertness. This makes them slower to respond to the starting shot, resulting in a higher finishing time. This small bias can the difference between winning gold, and not even being on the podium!