2. Thousands of people around the world participate in teams of 15 members each year, with the winning team being treated to an all-expense paid trip to see Misha Collins.
3. This year, two of the items on the list required the involvement of published and/or bestselling authors.
78.Get a previously published Sci-Fi author to write an original story (140 words max) about Misha, the Queen of England and an Elopus: 59 POINTS.
178. Get A NYT best-selling author or Tony-award winning actor or actress doing a dramatic reading of a section of this [the California Driver Handbook]: 112 POINTS.
4. After multiple requests, YA author Lauren DeStefano took to Facebook to explain why she wouldn’t be writing stories for anyone.
9. On Twitter, other writers posted similar disclaimers.
13. Science fiction author John Scalzi initially wrote that he wouldn’t participate…
14. But he later tweeted this frustrated message:
15. In response, the GISHWHES team updated their rules Tuesday and promised to dock points from any team that exhibited harassing behavior:
Commandment 4 – Harassment – It’s come to our attention that a number of teams have been verbally harassing authors and politicians to achieve items. If someone doesn’t want to help you, this is no reason to verbally attack them. We are trying to create art and change lives, not hurt people. Your team will be docked points if we determine that you are breaking Commandment 4. Perhaps more importantly, you are dinging your karma credit. Be nice to people. Remember, you are representing the global community of GISHWHES and that community believes that through art we can change lives – not hurt them.
16. The contest, which ends August 9th, has already broken three Guinness world records through group events.
- Bernie Sanders and Donald Trump are the winners of the Democratic and Republican New Hampshire primaries 🇺🇸
- The Supreme Court put on hold President Obama's climate change plan, which aims to curb carbon dioxide emissions from power plants.
- And Twitter is now offering an algorithmic version of its timeline that will prioritize some tweets over others.