Has workedin a cleanlab (on landor on a ship)Speaks>2languagesFlewhere ona planeWorkswithlidarDoesNOT liketo teachbut has toknows 3TaylorSwiftsongsMovedhousewithin thelast yearScubadivesDoesnot likepizzaFliesdronesHas beento thePacificOceanWriteswikipediaarticlesHas beenat sea for>1 weekPlays amusicalinstrumentHas aGitHubHas aparrotHasa catPrefersto codein pythonPrefers tocode inMATLABCan tell afield workdisasterstoryHas beento theSouthernOceanDoes adistancesportIshungryright nowHasinteractedwith a CTD-RosetteKnowswhat asundog isHas beento theAtlanticOceanFilters alot ofseawaterClimberHas beento aconcert inlast monthBrewsbeerHas used asun-photometerLovesaerosolsKnows amagictrickPlays amusicalinstrumentLovesrainbowunicornsKnows moreaboutpolarimetrythan owningthe sunglassesHasconsideredbecomingan astronautHas useda weatherballoonFlew aninstrumenton ER-2Does alot ofoutreachIs anatmosphericscientistStarwarsfanHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingDogpersonHas doneairbornescienceDrove acar >1hour toget herePrefersto codein RDid fieldwork inthe lastyearHas beenat sea for>1 weekModels(data orfashion)Lives >2hoursdrive tothe oceanDoeslakescienceWorkswithcitizenscientistsHas beento theArcticOceanHas workedin a cleanlab (on landor on a ship)Speaks>2languagesFlewhere ona planeWorkswithlidarDoesNOT liketo teachbut has toknows 3TaylorSwiftsongsMovedhousewithin thelast yearScubadivesDoesnot likepizzaFliesdronesHas beento thePacificOceanWriteswikipediaarticlesHas beenat sea for>1 weekPlays amusicalinstrumentHas aGitHubHas aparrotHasa catPrefersto codein pythonPrefers tocode inMATLABCan tell afield workdisasterstoryHas beento theSouthernOceanDoes adistancesportIshungryright nowHasinteractedwith a CTD-RosetteKnowswhat asundog isHas beento theAtlanticOceanFilters alot ofseawaterClimberHas beento aconcert inlast monthBrewsbeerHas used asun-photometerLovesaerosolsKnows amagictrickPlays amusicalinstrumentLovesrainbowunicornsKnows moreaboutpolarimetrythan owningthe sunglassesHasconsideredbecomingan astronautHas useda weatherballoonFlew aninstrumenton ER-2Does alot ofoutreachIs anatmosphericscientistStarwarsfanHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingDogpersonHas doneairbornescienceDrove acar >1hour toget herePrefersto codein RDid fieldwork inthe lastyearHas beenat sea for>1 weekModels(data orfashion)Lives >2hoursdrive tothe oceanDoeslakescienceWorkswithcitizenscientistsHas beento theArcticOcean

Human Bingo: Find someone who... - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
  1. Has worked in a clean lab (on land or on a ship)
  2. Speaks >2 languages
  3. Flew here on a plane
  4. Works with lidar
  5. Does NOT like to teach but has to
  6. knows 3 Taylor Swift songs
  7. Moved house within the last year
  8. Scuba dives
  9. Does not like pizza
  10. Flies drones
  11. Has been to the Pacific Ocean
  12. Writes wikipedia articles
  13. Has been at sea for >1 week
  14. Plays a musical instrument
  15. Has a GitHub
  16. Has a parrot
  17. Has a cat
  18. Prefers to code in python
  19. Prefers to code in MATLAB
  20. Can tell a field work disaster story
  21. Has been to the Southern Ocean
  22. Does a distance sport
  23. Is hungry right now
  24. Has interacted with a CTD-Rosette
  25. Knows what a sundog is
  26. Has been to the Atlantic Ocean
  27. Filters a lot of seawater
  28. Climber
  29. Has been to a concert in last month
  30. Brews beer
  31. Has used a sun-photometer
  32. Loves aerosols
  33. Knows a magic trick
  34. Plays a musical instrument
  35. Loves rainbow unicorns
  36. Knows more about polarimetry than owning the sunglasses
  37. Has considered becoming an astronaut
  38. Has used a weather balloon
  39. Flew an instrument on ER-2
  40. Does a lot of outreach
  41. Is an atmospheric scientist
  42. Star wars fan
  43. Has called into a PACE Science & Applications Team (SAT) Meeting
  44. Dog person
  45. Has done airborne science
  46. Drove a car >1 hour to get here
  47. Prefers to code in R
  48. Did field work in the last year
  49. Has been at sea for >1 week
  50. Models (data or fashion)
  51. Lives >2 hours drive to the ocean
  52. Does lake science
  53. Works with citizen scientists
  54. Has been to the Arctic Ocean